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Physiological and Agronomic Responses of Processing Tomatoes to Deficit Irrigation at Critical Stages in a Semi-Arid Environment

Physiological and Agronomic Responses of Processing Tomatoes to Deficit Irrigation at Critical... agronomy Article Physiological and Agronomic Responses of Processing Tomatoes to Deficit Irrigation at Critical Stages in a Semi-Arid Environment 1 , 2 2 2 Cristina Patanè *, Sebastiano Andrea Corinzia , Giorgio Testa , Danilo Scordia 1 , 2 and Salvatore Luciano Cosentino CNR-Istituto per la BioEconomia (IBE), Sede Secondaria di Catania, Via P. Gaifami 18, 95126 Catania, Italy; sl.cosentino@unict.it Dipartimento di Agricoltura, Alimentazione e Ambiente, Università degli Studi di Catania, via Valdisavoia 5, 95123 Catania, Italy; andrea.corinzia@unict.it (S.A.C.); gtesta@unict.it (G.T.); dscordia@unict.it (D.S.) * Correspondence: cristinamaria.patane@cnr.it; Tel.: +39-095-733-8395 Received: 9 May 2020; Accepted: 1 June 2020; Published: 4 June 2020 Abstract: Deficit irrigation is a valid alternative to conventional irrigation to save water while maintaining high productivity in tomatoes. However, crop sensitivity to water stress due to deficit irrigation may change with the growth stage. To assess the physiological and agronomic responses of processing tomatoes to deficit irrigation applied at critical stages, a field experiment was conducted in a coastal site of Southern Italy, where seven irrigation treatments di ering for daily evapotranspiration (ETc) restored (100%—full or 50%—deficit) and the time of watering (long-season or limited to the vegetative period or to flowering) were applied to processing tomatoes cv. Hypeel F1. Plants continuously irrigated and those irrigated only at flowering maintained higher rates of leaf transpiration (E) and stomatal conductance (g ) over those irrigated only during the vegetative period. Fruit yield was the greatest under long-season full irrigation (51 t ha ). Severe soil water deficit during flowering, more than during the vegetative period, adversely a ected crop productivity. Irrigation water use eciency (IWUE) was maximized under long-season deficit irrigation (>19 kg m ) or deficit irrigation during flowering (>16 kg m ). E and g measured at early or mid-flowering may be adopted as valuable indicators to predict crop productivity; however, they may be altered under high vapor pressure deficit (VPD). Predawn water potential, being little a ected by VPD, is a more reliable parameter than leaf transpiration and stomatal conductance under these climatic conditions. Keywords: processing tomatoes; deficit irrigation; soil water content; leaf transpiration; stomatal conductance; vapor pressure deficit; water use eciency 1. Introduction Tomatoes (Solanum lycopersicum L.) are an important economic crop worldwide, with the greatest area of cultivation among vegetables [1]. In 2018, the total tomato production exceeded 182 million tons over a cultivation area of 4.7 million hectares [2]. Tomatoes have a subtropical origin, thus requiring large amounts of irrigation water during summer, which is the cropping season for processing tomatoes in dry areas of Southern Italy. However, in these areas, the scarce availability of irrigation water resources and the lack of rainfall during summertime limit a sustainable cultivation for high water-demanding crops, such as processing tomatoes; besides, the irrigation issues have seriously been worsened due to climate change e ects. Indeed, to maximize tomato yields, soil water availability at the root zone must be maintained near field capacity throughout the growth period [3]. Under a semi-arid environment, the development of water-saving irrigation strategies may encourage farmers to revise their irrigation scheduling approach towards a more ecient water Agronomy 2020, 10, 800; doi:10.3390/agronomy10060800 www.mdpi.com/journal/agronomy Agronomy 2020, 10, 800 2 of 17 management, in order to limit water consumption and bring to satisfactory yields. Deficit irrigation approaches result in a reduced water application while maintaining adequate yields and enhancing overall fruit quality [4]. This is also for tomatoes, where the validity of the adoption of this water-saving irrigation strategy has been largely documented [4–7]. One of the greatest benefits of deficit irrigation is that, besides saving large amounts of water, it allows to lessen the production costs, to improve water productivity (i.e., the eciency in its use) and, overall, to reduce the impact of the crop to the environment, as compared to conventional irrigation [8]. However, not all stages of the crop-growing season are sensitive to water stress due to deficit irrigation similarly. In tomato crops, the most sensitive phenological phase to water stress is generally flowering [6]. Significant e ects of water deficit at fruit ripening on tomato yields under greenhouse conditions have been also reported [9]. The relationship between soil water deficits at critical stages and the physiological and productive behavior of tomatoes is quite complex and long studied, although controversial results have been reported [1]. Models to estimate the e ects of evapotranspiration (ET) were developed as well, either at each growth stage or for the whole growth period, on crop yields. Some of them, like the date crop water production function (DCWPF) [10] or Minhas model with its water deficit sensitivity indexes [11] can be applied to optimize the irrigation water management in areas of water scarcity. As aforementioned, the e ects of irrigation at di erent stages of the crop growing season have been extensively studied in tomatoes, although mostly upon fruit yield and quality [12–15]. However, detailed studies on the relationships between crop physiology and growth in field-grown tomatoes exposed to di erent deficit irrigation regimes are still lacking. The identification of the most critical stages to water stress through the measurement of some plant water status parameters may contribute to a better manipulation of deficit irrigation in processing tomatoes. Indeed, both soil water and climate conditions may greatly a ect the physiological parameters (stomatal conductance, transpiration and pre-dawn leaf water potential) of the crop, even under unrestricted soil water content conditions [16]. The goal of this study was to assess the e ects of deficit irrigation applied to the crop-growing season or at critical stages on physiology, growth, yield and water use eciency in field-grown processing tomatoes under a semi-arid Mediterranean environment of South Italy, in order to identify the most water stress-sensitive period and optimize irrigation water management under water scarcity conditions. 2. Materials and Methods 2.1. Open-Field Experiment Field experiment was conducted during the 2012 season in a site on the Eastern coast of Sicily 0  0 (South Italy, 10 m a.s.l., 37 03 N Lat, 15 18 E Long) on a moderately deep Calcixerollic Xerochrepts soil. The soil characteristics were: clay 24.0%, sand 35.0%, silt 41.0%, organic matter 1.20%, pH 8.0, total N 1 1 3 0.5%, available P 48 mg kg , exchangeable K 940 mg kg , bulk density 1.3 g cm , field capacity 1 1 (0.03 MPa) 0.25 g g and wilting point (1.5 MPa) 0.15 g g . Fallow preceded the cultivation of tomato crops. In a randomized complete block experimental design with three replicates, seven irrigation treatments were studied (Table 1). The cultivar Hypeel F1 (Seminis Inc., Oxnard, CA, USA) of the processing tomato (Solanum lycopersicum L.) was used for the experiment. Plants were transplanted at the four-leaf stage on June 9 in a single plot of 38.4 m (4.8 m 8 m). Plants were spaced at 0.75 m between rows and 0.40 m within rows, resulting in a plant 2 1 density of approximately 3.3 plants m . Before transplanting 75, 100 and 100 kg ha of N (as ammonium sulphate), P O (as mineral perphosphate) and K O (as potassium sulphate), respectively, 2 5 2 were distributed. Approximately 30 days after transplant (DAT), a further 75 kg ha of N (as ammonium nitrate) was supplied as top dressing. Agronomy 2020, 10, 800 3 of 17 Table 1. Description of the di erent irrigation treatments applied to the processing tomato cv. Hypeel F1. ETc: daily evapotranspiration. Seasonal Volume of Water Irrigation Treatment Description 3 1 (m ha ) NI (no irrigation) Irrigation up to seedling establishment 450 F (full, control) Long-season irrigation, 100% ETc restoration 4050 D (deficit) Long-season irrigation, 50% ETc restoration 2250 Short-season irrigation, early cut-o at the onset of FE (full, early) 1210 flowering, 100% ETc restoration Short-season irrigation, early cut-o at the onset of DE (deficit, early) 830 flowering, 50% ETc restoration FFL (full, flowering) Irrigation only during flowering, 100% ETc restoration 2090 DFL (deficit, flowering) Irrigation only during flowering, 50% ETc restoration 1270 A drip-irrigation system was used. At the time of transplanting, the irrigation water was supplied to fulfil the field capacity at approximately 0.3 m of depth. Thereafter, the volume of irrigation water to supply was determined on the basis of the maximum available soil water content (ASWC) in the first 0.4 m of soil, where most of roots are expected to grow, calculated with the following formula: V = 0.66 (FC WP)   D (1) where V = water amount (approximately 34 mm), 0.66 = fraction of promptly available soil water permitting unrestricted evapotranspiration, FC = soil water at field capacity (25% of soil dry weight), WP = soil water at wilting point (15% of soil dry weight),  = bulk density (g cm ) and D = soil depth (0.4 m). Irrigation water was supplied when the sum of daily evapotranspiration (ET ) corresponded to V: ETc = ET  k  k (2) 0 p c where ET = reference ET, measured by means of a class A pan (mm), k = pan coecient, equal to 0.80 in a semi-arid environment and k = crop coecient [3]. Total amount of water distributed to each irrigation treatment is reported in Table 1. No chemical herbicides were used for weed control. A hand-weeding was performed once only, since the crop covered the soil, and weeds could no longer grow. The following meteorological variables were recorded daily throughout the crop-growing season: air temperature, rainfall, class A pan evaporation, using a data logger (CR10, Campbell Scientific, Logan, UT, USA) located approximately 50 m from the experimental field. Along the experiment from mid-July, when plants started to flower, to the end of August, when they were at the ripening stage of fruits, soil water content was measured, at 2 to 3-day intervals, by means of gypsum blocks (Soilmoisture Equipment Corp., Santa Barbara, CA, USA) located at 0.15 and 0.30-m soil depths in all replicates of each irrigation treatment. Thereafter, the available soil water content (ASWC), as a percentage of the maximum available water and according to the following formula, was calculated [17]: ASWC = (WC WP)/(FC WP) 100 (3) 1 1 where WC = soil water content (g g dry soil), FC = soil water content at field capacity (0.25 g g dry soil) and WP = soil water content at the wilting point (0.15 g g dry soil). ASWC ranged between 100% (field capacity) and 0% (wilting point). 2.2. Physiological Measurements 2 1 2 1 Leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , mol m s ) were 2 s measured along the growing season at 10 subsequent dates after transplanting (DAT) from mid-July to Agronomy 2020, 10, 800 4 of 17 the end of August by means of a null balance “steady-state” porometer (Model LI-1600, Li-Cor, Inc., Lincoln, NE, USA). Measurements were made on clear sunshine hours between 11:00 h and 13:00 (solar time) in fully developed and healthy leaves. One reading was carried out on three randomly chosen, fully expanded young leaves from each plot. Leaf water potential ( , MPa) was also measured before sunrise (03:00–05:00 h solar time, “pre-dawn” water potential) at 3–5-day intervals starting in August up to early September by means of a pressure chamber (Soilmoisture Equipment Corp., Santa Barbara, CA, USA). Briefly, a leaflet was excised at the petiole level from a young fully expanded leaf (on the top part of the plant) using a razor blade. The leaflet was partly sealed in the pressure chamber, with the cut end of the petiole protruding through the seal. The chamber was pressurized with compressor gas until the appearance of water in the cut surface (detectable using a magnifying glass). At that point, the pressure was recorded. As for E and g , one reading was carried out on three randomly chosen, fully expanded young leaves from each plot. 2.3. Plant Measurements At five dates, from middle of July to early August (34, 38, 46, 53 and 60 DAT), two representative plants were sampled destructively from each experimental plot, and flowers and fruits (when present) were counted. After that, plant parts (root, stem, leaves, flowers and fruits when present) were dried in a thermo-ventilated oven at 65 C until constant weight (about 3 days) for dry matter (DW) measurement (g DW plant ). 2.4. Calculations The crop was hand-harvested when the ripe fruit rate reached ~95% (early September). At harvest, 1 3 total fruit yield (t ha ) was measured, and irrigation water use eciency (IWUE, kg m ) was calculated from the di erent irrigation treatments as the ratio of total yield (kg) and total water applied by irrigation (m ) [13]. 2.5. Statistical Analyses Data of physiological (E, g and ) and plant production (number of flowers, number of fruits, shoot dry weight, root dry weight and fruit production) measurements were subjected to a one-way repeated-measures analysis of variance (ANOVA) where date of measurement represents the within-subjects factor and the irrigation treatment the between-subjects factor (SPSS, PASW Statistics 18). When the Mauchly’s sphericity test failed to meet the assumption of sphericity, the univariate results were adjusted by using the Greenhouse-Geisser Epsilon and the Huynh-Feldt Epsilon correction factors. Following the univariate test satisfying the sphericity for within-subject e ects, the F-values and associated p-values for between-subject e ects were tested. Means were separated by the Tukey’s test at a 95% confidence level. For data of the number of flowers and number of fruits per plant, shoot dry weight and root dry weight, a supplemental ANOVA was carried out separately for the date of measurement. Data of final yield and irrigation water use eciency (IWUE) were statistically analyzed by a one-way analysis of variance (ANOVA) using CoStat version 6.003 (CoHort Software, Monterey, CA, USA). Di erences between means were evaluated as described above. Plant dry weight variations over time were interpolated by a nonlinear iterative regression method (SigmaPlot11, Systat Software Inc., San Jose, CA, USA) using the following exponential function: y = (4) 1 + 0 Agronomy 2020, 10, x FOR PEER REVIEW 5 of 18 Data of final yield and irrigation water use efficiency (IWUE) were statistically analyzed by a one-way analysis of variance (ANOVA) using CoStat version 6.003 (CoHort Software, Monterey, CA, USA). Differences between means were evaluated as described above. Plant dry weight variations over time were interpolated by a nonlinear iterative regression method (SigmaPlot11, Systat Software Inc., San Jose, CA, USA) using the following exponential function: Agronomy 2020, 10, 800 5 of 17 𝑦 = (4) 1 + ( ) where a = maximal value of y, x = time (DAT), x = time (DAT) to reach 50% of maximal value a where a = maximal value of y, x = time (DAT), x0 = time (DAT) to reach 50% of maximal value a and and b = fitting parameter of the curve. Thereafter, using values of the curve, crop growth rate (CGR, b = fitting parameter of the curve. Thereafter, using values of the curve, crop growth rate (CGR, g DW 1 1 g DW plant d ) was calculated as follows: −1 −1 plant d ) was calculated as follows: CGR = (W W )/(t t ) (5) 2 1 1 2 𝐶𝐺𝑅 = (𝑊 − 𝑊 )/(𝑡 − 𝑡 ) (5) 2 1 1 2 where W2 and W1 are the values of the plant dry weight (g) at times t2 and t1, respectively, on the where W and W are the values of the plant dry weight (g) at times t and t , respectively, on the 2 1 2 1 curve. Finally, the maximum value of CGR (CGRmax) was considered [18]. curve. Finally, the maximum value of CGR (CGRmax) was considered [18]. The relationships between leaf transpiration and stomatal conductance measured in plants The relationships between leaf transpiration and stomatal conductance measured in plants under under no water limitation (F treatment) and vapor pressure deficit (VPD, kPa) in the atmosphere no water limitation (F treatment) and vapor pressure deficit (VPD, kPa) in the atmosphere were were described by using a nonlinear function (SigmaPlot11, Systat Software Inc., San Jose, CA, USA). described by using a nonlinear function (SigmaPlot11, Systat Software Inc., San Jose, CA, USA). VPD VPD was calculated using air relative humidity (RH, %) and air temperature (°C) recorded by the was calculated using air relative humidity (RH, %) and air temperature ( C) recorded by the same same “steady-state” porometer at the moment of physiological measurements [19]. “steady-state” porometer at the moment of physiological measurements [19]. 3. Results 3. Results 3.1. Meteorological Trend 3.1. Meteorological Trend The meteorological course during the crop-growing season was typical of the semi-arid The meteorological course during the crop-growing season was typical of the semi-arid Mediterranean environment, with a hot and dry summer (Figure 1). Mediterranean environment, with a hot and dry summer (Figure 1). 50 11 rain 10 Tmax Tmin ET 0 1 0 0 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88 92 Days after transplant Figure 1. Meteorological course (maximum and minimum air temperatures, rainfall, and reference Figure 1. Meteorological course (maximum and minimum air temperatures, rainfall, and reference evapotranspiration (ET0)) recorded during the field experiment. evapotranspiration (ET )) recorded during the field experiment. Maximum Maximum temperatur temperature e ranged ranged between betwee 27.6 n 27.6 C (in °C June) (in Ju and ne) 43.4 andC 43.4 (in July), °C (in witJu h the ly), minimum with the between minimum 14.0 between C (in14.0 June) °Cand (in 22.4 June) C and (in 22. July). 4 °C T(i otal n Jul rainfall y). Total up rto ainfall August up to was August <10 mm; was ther <10 efor mm e, ; soil therefore, water soi availability l water avail wasabi totally lity w due as tto otal irrigation. ly due toRefer irriga ence tion. evapotranspiration Reference evapotranspir (ET ) follows ation (ET the 0) −1 course follows of th the e course air temperatur of the air e,tem and perat values ure, exceeding and values 9 mm exceed d ing wer9 e mm recor d ded were in the recorded first 10-day in the period first and 10-dat aythe perio end d a of nd July at t . he end of July. 3.2. Soil Water Content Soil water content fluctuated during the growth season, according to the irrigation time. It maintained the highest levels at both soil depths under the F regime throughout the crop-growing season (Figure 2). However, even under these experimental conditions, despite continuous irrigation, soil water deficits sometimes exceeded 66% (threshold for irrigation). Indeed, the volume of water supplied by irrigation (approximately constant) was indirectly calculated on the ETc basis, not on the actual soil water content at the irrigation time [20]. Therefore, it is likely that this volume of water sometimes was not adequate to fill the soil up to field capacity even under the F regime. Air temperature (°C) Rainfall, ET (mm) 0 Agronomy 2020, 10, x FOR PEER REVIEW 6 of 18 3.2. Soil Water Content Soil water content fluctuated during the growth season, according to the irrigation time. It maintained the highest levels at both soil depths under the F regime throughout the crop-growing season (Figure 2). However, even under these experimental conditions, despite continuous irrigation, soil water deficits sometimes exceeded 66% (threshold for irrigation). Indeed, the volume of water supplied by irrigation (approximately constant) was indirectly calculated on the ETc basis, not on the actual soil water content at the irrigation time [20]. Therefore, it is likely that this volume of water Agronomy 2020, 10, 800 6 of 17 sometimes was not adequate to fill the soil up to field capacity even under the F regime. 15 cm NI 30 cm 100 0 80 F 15 cm Plot 1 Upper specification 100 30 cm 100 0 FE 100 0 DE 100 0 FFL 100 0 DFL 30 35 40 45 50 55 60 65 70 75 80 85 90 Days after transplant Figure 2. Available soil water contents at depths of 15 cm (red line) and 30 cm (blue line) in each Figure 2. Available soil water contents at depths of 15 cm (red line) and 30 cm (blue line) in each irrigation treatment. Constant horizontal short-dash line indicates the minimum threshold of the irrigation treatment. Constant horizontal short-dash line indicates the minimum threshold of the available soil water content. NI: no irrigation, F: full, D: deficit, FE: full early, DE: deficit early, FFL: full available soil water content. NI: no irrigation, F: full, D: deficit, FE: full early, DE: deficit early, FFL: flowering and DFL: deficit flowering. full flowering and DFL: deficit flowering. In the D treatment, irrigation tended to fulfil the upper layers of the soil. Under no irrigation In the D treatment, irrigation tended to fulfil the upper layers of the soil. Under no irrigation during flowering (NI, FE and DE), soil water contents during the measurements period were always during flowering (NI, FE and DE), soil water contents during the measurements period were always beneath the field capacity at both soil depths. In plots irrigated only at flowering, soil water contents beneath the field capacity at both soil depths. In plots irrigated only at flowering, soil water contents exhibited trends similar to that of the F regime, although, in FFL, only in the upper layer of soil. In DFL, the water content kept higher in the upper layers of the soil (15 cm), up to approximately 50 DAT. However, just after irrigation suspension (at 54 DAT), the soil water content in both FFL and DFL dropped to levels lower than the field capacity already at 57 DAT. Available soil water content (%) Agronomy 2020, 10, x FOR PEER REVIEW 7 of 18 exhibited trends similar to that of the F regime, although, in FFL, only in the upper layer of soil. In DFL, the water content kept higher in the upper layers of the soil (15 cm), up to approximately 50 DAT. However, just after irrigation suspension (at 54 DAT), the soil water content in both FFL and DFL dropped to levels lower than the field capacity already at 57 DAT. Agronomy 2020, 10, 800 7 of 17 3.3. Course of Leaf Transpiration and Stomatal Conductance 3.3. Course of Leaf Transpiration and Stomatal Conductance ANOVA evidenced a highly significant effect of the irrigation treatment (I) and time of measurement (T) upon all the physiological parameters examined (p ≤ 0.001) (Table 2). The significant ANOVA evidenced a highly significant e ect of the irrigation treatment (I) and time of measurement interaction I × T (p ≤ 0.001) suggests that the physiological response of tomato plants to changing soil (T) upon all the physiological parameters examined (p 0.001) (Table 2). The significant interaction water contents varies with the time of measurement. I  T (p  0.001) suggests that the physiological response of tomato plants to changing soil water contents varies with the time of measurement. Table 2. Repeated-measures ANOVA for main effects and interactions on the physiological traits. Table 2. Repeated-measures ANOVA for main e ects and interactions on the physiological traits. gs ψ Source df df E Adj MS g Adj MS Source df df Irrigation (I) 6 1615.2 *** 3.829 *** 6 1.350 *** Adj MS Adj MS Time (T) 9 1497.9 *** 3.367 *** 8 0.150 *** Irrigation (I) 6 1615.2 *** 3.829 *** 6 1.350 *** I × T 54 408.6 *** 0.811 *** 48 0.040 *** Time (T) 9 1497.9 *** 3.367 *** 8 0.150 *** I  T 54 408.6 *** 0.811 *** 48 0.040 *** Error (T) 126 267.8 0.823 112 0.011 Error (T) 126 267.8 0.823 112 0.011 Error 14 22.6 0.119 14 0.006 Error 14 22.6 0.119 14 0.006 Leaf transpiration—E, stomatal conductance—gs and predawn water potential—ψ. Degree of Leaf transpiration—E, stomatal conductance—g and predawn water potential— . Degree of freedom (df) and freedom (df) and adjusted mean square (Adj MS). Significant at p ≤ 0.001 (***). adjusted mean square (Adj MS). Significant at p 0.001 (***). Leaf transpiration (E) and stomatal conductance (gs) were measured from approximately a Leaf transpiration (E) and stomatal conductance (g ) were measured from approximately a month after transplanting (when plants were at the floral initiation and water treatments were overall month after transplanting (when plants were at the floral initiation and water treatments were overall differentiated) onward (Figure 3). In all the experimental situations, E exhibited an increasing trend di erentiated) onward (Figure 3). In all the experimental situations, E exhibited an increasing trend from the initial measurement up to approximately 50 DAT, when the first fruit buds were quite from the initial measurement up to approximately 50 DAT, when the first fruit buds were quite visible. −2 −1 visible. After that, E steeply decreased down to values ≤5.55 mmol H2O m s measured at 61 DAT 2 1 After that, E steeply decreased down to values 5.55 mmol H O m s measured at 61 DAT in all in all water treatments. water treatments. 2 1 2 1 Figure 3. Course of leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , mol m s ) during the growth period in processing tomatoes cv. Hypeel F1 under di erent irrigations. This was probably due to quite a low air humidity and quite a high air temperature recorded in that period (between 52 and 62 DAT), which determined a high VPD and, consequently, a high water demand from the atmosphere. This, in turn, induced a partial stomatal closure and a reduced E even Agronomy 2020, 10, x FOR PEER REVIEW 8 of 18 −2 −1 −2 −1 Figure 3. Course of leaf transpiration (E, mmol H2O m s ) and stomatal conductance (gs, mol m s ) during the growth period in processing tomatoes cv. Hypeel F1 under different irrigations. This was probably due to quite a low air humidity and quite a high air temperature recorded in that period (between 52 and 62 DAT), which determined a high VPD and, consequently, a high water Agronomy 2020, 10, 800 8 of 17 demand from the atmosphere. This, in turn, induced a partial stomatal closure and a reduced E even under the unrestricted soil water conditions in F. Indeed, an exponential function well describes the under the unrestricted soil water conditions in F. Indeed, an exponential function well describes the overall changes in E and gs measured in plants under good soil water conditions (those of F), overall changes in E and g measured in plants under good soil water conditions (those of F), according according to the variation in VPD (Figure 4). to the variation in VPD (Figure 4). −2 −1 2 1 Figure 4. Variation of leaf transpiration (E, mmol H2O m s ) and stomatal conductance (gs, mol Figure 4. Variation of leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , 2 s −2 −1 2 1 m s ) in relation to the increase of the vapor pressure deficit (VPD, kPa) in the atmosphere under mol m s ) in relation to the increase of the vapor pressure deficit (VPD, kPa) in the atmosphere under full irrigation (F treatment) in processing tomatoes cv. Hypeel F1. Measurements were made between full irrigation (F treatment) in processing tomatoes cv. Hypeel F1. Measurements were made between 2 −21 −1 11:00 and 13:00, with PAR (Photosynthetic active radiation) varying from 1500 to 2000 μmol m s as 11:00 and 13:00, with PAR (Photosynthetic active radiation) varying from 1500 to 2000 mol m s as measured by the PAR sensor of the porometer. Symbols represent the observed values. Black vertical measured by the PAR sensor of the porometer. Symbols represent the observed values. Black vertical bars bars rrepr epresent esent the the s standar tandard d err eror ror. . The course of this function indicates that an increase in the VPD determines a progressive raise in The course of this function indicates that an increase in the VPD determines a progressive raise both parameters up to a maximum (at a VPD of approximately 1.9 kPa for E and 1.7 kPa for g on the in both parameters up to a maximum (at a VPD of approximately 1.9 kPa for E and 1.7 kPa for gs on curve). Beyond this, the values of E and g start to decline down to a minimum at 2.4 kPa of the VPD. the curve). Beyond this, the values of E an s d gs start to decline down to a minimum at 2.4 kPa of the Later on, the leaf transpiration increased again except under severe soil water deficit conditions VPD. (NI, FE and DE), thus slowly decreasing down to the minimum measured late in the growing season Later on, the leaf transpiration increased again except under severe soil water deficit conditions (82 DAT), when plants started to senesce. (NI, FE and DE), thus slowly decreasing down to the minimum measured late in the growing season Same trend was observed for stomatal conductance, although its maximum value was achieved (82 DAT), when plants started to senesce. later (approximately 55 DAT) than that measured for E. Same trend was observed for stomatal conductance, although its maximum value was achieved According to the water supply, plots continuously irrigated (F and D) and those receiving water at later (approximately 55 DAT) than that measured for E. flowering only (FFL and DFL) maintained higher rates of leaf transpiration and stomatal conductance According to the water supply, plots continuously irrigated (F and D) and those receiving water 2 1 over those exposed to a drying soil (NI, FE and DE), with maximum values11 mmol H O m s at flowering only (FFL and DFL) maintained higher rates of leaf transpiration and stomatal 2 1 (for E) and 0.56 mol m s (for g ) in all. conductance over those exposed to a drying soil (NI, FE and DE), with maximum values ≥11 mmol −2 −1 −2 −1 H2O m s (for E) and 0.56 mol m s (for gs) in all. 3.4. Course of “Predawn” Water Potential 3.4. Course of “Predawn” Water Potential The course of water potential ( ) at the first hours of the day (“predawn”) was measured under nonlimiting air temperature and relative humidity conditions to the plant-water flux (Figure 5). The course of water potential (ψ) at the first hours of the day (“predawn”) was measured under Predawn was measured during the growing season, starting from the first days of August (55 DAT), nonlimiting air temperature and relative humidity conditions to the plant-water flux (Figure 5). when plants were near the end of the flowering period, to early September (88 DAT). Under rainfed Predawn ψ was measured during the growing season, starting from the first days of August (55 conditions (NI), predawn kept always the lowest values (<0.50 MPa), and at the end of growing DAT), when plants were near the end of the flowering period, to early September (88 DAT). Under season, it was1.06 MPa. rainfed conditions (NI), predawn ψ kept always the lowest values (<−0.50 MPa), and at the end of Under no irrigation at flowering (FE and DE), exhibited a fluctuating trend, dropping down growing season, it was −1.06 MPa. to final values <0.70 MPa. Under a continuous water supply, always kept values0.38 MPa in plants fully irrigated (F), which indicated an adequate plant water status. In FFL and DFL, the water potential after the irrigation suspension was kept high, even if the soil water content kept constantly lower than the field capacity from 57 DAT onward. Agronomy 2020, 10, 800 9 of 17 Agronomy 2020, 10, x FOR PEER REVIEW 9 of 18 Figure 5. Course of “predawn” water potential (ψ, MPa) during the growth period in processing Figure 5. Course of “predawn” water potential ( , MPa) during the growth period in processing tomatoes cv. Hypeel F1 under different irrigation treatments. tomatoes cv. Hypeel F1 under di erent irrigation treatments. 3.5. Course of Shoot and Root Dry Biomasses Under no irrigation at flowering (FE and DE), ψ exhibited a fluctuating trend, dropping down to final values <−0.70 MPa. Under a continuous water supply, ψ always kept values ≥−0.38 MPa in The statistical analysis evidenced a significant e ect of the irrigation treatment (I) and time of plants fully irrigated (F), which indicated an adequate plant water status. In FFL and DFL, the water measurement (T) upon both the shoot and root dry biomasses (p  0.001). However, significant potential after the irrigation suspension was kept high, even if the soil water content kept constantly interactions (p 0.01) were also observed (Table 3). lower than the field capacity from 57 DAT onward. Table 3. Repeated-measures ANOVA for the main e ects and interactions on plant production traits. 3.5. Course of Shoot and Root Dry Biomasses Shoot Dry Weight Root Dry Weight Flowers (n) Fruits (n) Plant Production Source df The statistical analysis evidenced a significant effect of the irrigation treatment (I) and time of Adj MS measurement (T) upon both the shoot and root dry biomasses (p ≤ 0.001). However, significant Irrigation (I) 6 10,321.0 *** 531.4 *** 783.2 * 617.0 *** 54,205 *** Time (T) 4 51,653.7 *** 627.2 *** 8567.8 *** 5651.8 *** 544,211 *** interactions (p ≤ 0.01) were also observed (Table 3). I T 24 1581.3 *** 62.51 ** 496.1 * 248.5 *** 28,155 *** Error (T) 56 76.5 32.5 261.5 53.1 2216.0 Table 3. Repeated-measures ANOVA for the main effects and interactions on plant production traits. Error 14 157.0 14.71 246.5 67.2 2240.0 Number of flowers and number of fruits per plant, shoot and root dry weight, fruit plant production. Degree of Shoot Dry Root Dry Flowers Plant freedom (df) and adjusted mean square (Adj MS). Significant at p 0.05 (*), p 0.01 Fruit (**) and s (np) 0.001 (***). Weight Weight (n) Production Source df Adj MS Indeed, the above-ground dry biomass progressively increased in all experimental situations Irrigation 6 10,321.0 *** 531.4 *** 783.2 * 617.0 *** 54,205 *** (Figure 6). Up to approximately 38 DAT, no great di erence was evidenced among the irrigation (I) treatments in the rate of biomass accumulation. After that, plants irrigated up to floral initiation (FE and Time (T) 4 51,653.7 *** 627.2 *** 8567.8 *** 5651.8 *** 544,211 *** DE treatments) accumulated dry biomasses with lower rates and 53 days after transplant; when plants I × T 24 1581.3 *** 62.51 ** 496.1 * 248.5 *** 28,155 *** were near the end of flowering, no further plant growth occurred. Under these experimental situations, Error (T) 56 76.5 32.5 261.5 53.1 2216.0 the total dry biomass started to increase again later on due to the fruit-set contribution. Under full and Error 14 157.0 14.71 246.5 67.2 2240.0 deficit irrigations for the entire season (F and D, respectively) or during flowering only (FFL and DFL, Number of flowers and number of fruits per plant, shoot and root dry weight, fruit plant production. respectively), dry biomasses were progressively accumulated up to the end of the growing season, Degree of freedom (df) and adjusted mean square (Adj MS). Significant at p ≤ 0.05 (*), p ≤ 0.01 (**) and with greater rates, as expected, in F. Under no irrigation conditions (NI), plants accumulated dry p ≤ 0.001 (***). biomasses with low rates until the end of the growing season (low fruit contributions). Root growth was quite proportional to that of shoots in plants fully irrigated for the whole growing Indeed, the above-ground dry biomass progressively increased in all experimental situations season. Di erently, roots stopped growing when plants achieved full flowering (approximately 46 (Figure 6). Up to approximately 38 DAT, no great difference was evidenced among the irrigation DAT onward) in the other water treatments. However, rewatering during flowering in FFL and DFL treatments in the rate of biomass accumulation. After that, plants irrigated up to floral initiation (FE led to a regrowth of root apparatuses. Root growth was scarce under dry conditions (NI). and DE treatments) accumulated dry biomasses with lower rates and 53 days after transplant; when Maximum crop growth rate (CGRmax) calculated from the values of the dry plant biomass vs. plants were near the end of flowering, no further plant growth occurred. Under these experimental time (DAT) on the interpolation curve (0.95 R  0.99) ranged between 1.89 (NI) and 10.97 (FFL) g DW situations, the total dry biomass started to increase again later on due to the fruit-set contribution. 1 1 1 1 plant d . High CGRmax (10.29 g DW plant d ) also corresponded to the F treatment, while under Under full and deficit irrigations for the entire season (F and D, respectively) or during flowering 1 1 deficit irrigation (D), it was lowered to 8.58 g DW plant d . This last value was further reduced (to only (FFL and DFL, respectively), dry biomasses were progressively accumulated up to the end of 1 1 7.64 g DW plant d ). the growing season, with greater rates, as expected, in F. Under no irrigation conditions (NI), plants accumulated dry biomasses with low rates until the end of the growing season (low fruit contributions). Agronomy 2020, 10, 800 10 of 17 Agronomy 2020, 10, x FOR PEER REVIEW 10 of 18 Shoot NI Root 70 ** ** ** ** 0 ** ** ** 20 ** ** 0 0 210 * 20 * FE ** 70 ** 0 0 ** 20 ** DE 140 ** ** 0 0 ** ** FFL 0 0 20 ** DFL ** ** ** 34 38 46 60 Days after transplant −1 Figure Figure 6.6. Course Course ofof shoot shoot and and root root dry dry biomass biomass accumulations accumulation (gsplant (g plant ) during ) during the the growth growth period period in pr in ocessing process tomatoes ing tomato cv. es Hypeel cv. Hypeel F1 under F1di un er de ent r di irrigation fferent irr trigatio eatments. n treat Black ments. vertical Black bars verti repr cal esent bars the repr standar esent t d he s errtor andard . Asterisks, error. As when terisks, present, when prese indicate nt, significance indicate signific at p anc e 0.05 at p (*) ≤ 0an .05 d(*) p and  0.01 p ≤(**) 0.01 respective (**) respec to tive the to corr the esponding corresponding F treatment wi F treatment within each thin e measur ach mement easuremen date.t date. 3.6. Course of Flower and Fruit Number Root growth was quite proportional to that of shoots in plants fully irrigated for the whole growing season. Differently, roots stopped growing when plants achieved full flowering The number of flowers and that of fruits were significantly a ected by the irrigation regime (approximately 46 DAT onward) in the other water treatments. However, rewatering during (p  0.05) and, to greater extent, by the time of measurements (p  0.05). Significant e ects of I  T flowering in FFL and DFL led to a regrowth of root apparatuses. Root growth was scarce under dry were also evidenced by ANOVA (p 0.05). conditions (NI). -1 Dry weight (g plant ) Agronomy 2020, 10, x FOR PEER REVIEW 11 of 18 Maximum crop growth rate (CGRmax) calculated from the values of the dry plant biomass vs. time (DAT) on the interpolation curve (0.95 ≤ R ≤ 0.99) ranged between 1.89 (NI) and 10.97 (FFL) g −1 −1 −1 −1 DW plant d . High CGRmax (10.29 g DW plant d ) also corresponded to the F treatment, while −1 −1 under deficit irrigation (D), it was lowered to 8.58 g DW plant d . This last value was further reduced −1 −1 (to 7.64 g DW plant d ). 3.6. Course of Flower and Fruit Number The number of flowers and that of fruits were significantly affected by the irrigation regime (p ≤ Agronomy 2020, 10, 800 11 of 17 0.05) and, to greater extent, by the time of measurements (p ≤ 0.05). Significant effects of I × T were also evidenced by ANOVA (p ≤ 0.05). In particular, the number of flowers per plant progressively increased with time, up to a In particular, the number of flowers per plant progressively increased with time, up to a maximum maximum that, in NI, FE and DE, was achieved later (at 53 DAT) than the other water treatments (at that, in NI, FE and DE, was achieved later (at 53 DAT) than the other water treatments (at 46 DAT) 46 DAT) (Figure 7). (Figure 7). 160 Flowers NI Fruits ** 180 0 FE ** 180 0 DE ** FFL 180 0 DFL 34 38 46 53 60 Days after transplant Figure Figure 7. 7. Course Course of of the the number number of of flowers flowers and and fr fru uits its per per plant plant during during the the gr growth owth per period iod in in pr proces ocessing sing tomatoes tomatoescv cv. . Hypeel Hypeel F1 under F1 und di er er di ent fferent irrigation irrigatio treatments. n treatmen Black ts. vertical Black verti bars cal repr bar esent s repr the es standar ent the d err standard or. Asterisks, error. As when terispr ksesent, , when indicate present,significance indicate signific at p ance  0.05 at (*) p ≤and 0.05p (*)  a 0.01 nd p (**) ≤ 0r .01 espective (**) respec to the tive corr to the esponding correspo F nding F treatment wi treatment within each thin e measur ach m ement easurdate. ement date. The first fruits appeared approximately 46 days after transplant, when excluding plants under dry conditions (NI) that, at that time, still did not have fruits. In F, after 53 DAT, the sum of flowers and fruits kept constant, indicating no flower drop. In FFL and DFL, rewatering at flowering induced a rise in flower production at 60 DAT. No irrigation at flowering in NI, FE and DE caused a quite pronounced drop of flowers. As a result, less fruits were produced under these experimental conditions. 3.7. Course of Fruit Production According to the course of the number of flowers and fruits with time, the fruit production per plant along the crop season was maintained constantly higher in F and lower in NI after 50 DAT (I e ect significant at p 0.001) (Figure 8). Flowers + fruits (n) Agronomy 2020, 10, x FOR PEER REVIEW 12 of 18 The first fruits appeared approximately 46 days after transplant, when excluding plants under dry conditions (NI) that, at that time, still did not have fruits. In F, after 53 DAT, the sum of flowers and fruits kept constant, indicating no flower drop. In FFL and DFL, rewatering at flowering induced a rise in flower production at 60 DAT. No irrigation at flowering in NI, FE and DE caused a quite pronounced drop of flowers. As a result, less fruits were produced under these experimental conditions. 3.7. Course of Fruit Production According to the course of the number of flowers and fruits with time, the fruit production per plant along the crop season was maintained constantly higher in F and lower in NI after 50 DAT (I Agronomy 2020, 10, 800 12 of 17 effect significant at p ≤ 0.001) (Figure 8). NI FE DE FFL DFL 30 35 40 45 50 55 60 65 Days after transplant Figure 8. Course of fruit production per plant (g fresh weight-FW) during the growth period in Figure 8. Course of fruit production per plant (g fresh weight-FW) during the growth period in processing tomatoes cv. Hypeel F1 under di erent irrigation treatments. Black vertical bars represent processing tomatoes cv. Hypeel F1 under different irrigation treatments. Black vertical bars represent the standard error. the standard error. Under irrigation limited to the flowering period, plants receiving 50% ETc exhibited a fruit Under irrigation limited to the flowering period, plants receiving 50% ETc exhibited a fruit production course similar to that of plants fully irrigated (100% ETc), with a production at 60 DAT production course similar to that of plants fully irrigated (100% ETc), with a production at 60 DAT anyway lower than that of plants under a deficit irrigation for the whole season (D treatment) (I  T, anyway lower than that of plants under a deficit irrigation for the whole season (D treatment) (I × T, p 0.001). In fact, the rise in flower production occurring in response to reirrigation at flowering did p ≤ 0.001). In fact, the rise in flower production occurring in response to reirrigation at flowering did not induce an equal rise in fruit production, since probably the irrigation suspension after flowering not induce an equal rise in fruit production, since probably the irrigation suspension after flowering did not allow most of the new flowers to turn into fruits. Under no irrigation at flowering (FE and DE), did not allow most of the new flowers to turn into fruits. Under no irrigation at flowering (FE and plants produced constantly less than those of the irrigated. DE), plants produced constantly less than those of the irrigated. 3.8. Fruit Yield and Water Productivity 3.8. Fruit Yield and Water Productivity 1 1 Final fruit yields varied from 51.02 t ha (F) to 3.81 t ha (NI), with significant di erences −1 −1 Final fruit yields varied from 51.02 t ha (F) to 3.81 t ha (NI), with significant differences (p ≤ (p  0.01) among treatments (Table 4). Irrigation at a reduced rate in D determined a 16% fruit loss, 0.01) among treatments (Table 4). Irrigation at a reduced rate in D determined a 16% fruit loss, with with a final yield that slightly (p 0.05) but not significantly di ered from that of the F treatment and a final yield that slightly (p ≤ 0.05) but not significantly differed from that of the F treatment and 44% 44% water saved. In FFL and DFL, as mentioned above, the raised number of flowers per plant due to water saved. In FFL and DFL, as mentioned above, the raised number of flowers per plant due to rewatering during the flowering period was not followed by an equal increase in plant productivity. rewatering during the flowering period was not followed by an equal increase in plant productivity. Therefore, irrigation only at flowering resulted in a water consumption that was approximately 48% Therefore, irrigation only at flowering resulted in a water consumption that was approximately 48% and 69% (in FFL and DFL, respectively) lower than that of long-season full irrigation (F); however, 55% and 69% (in FFL and DFL, respectively) lower than that of long-season full irrigation (F); however, (in FFL) and 58% (in DFL) fruit yields were lost. 55% (in FFL) and 58% (in DFL) fruit yields were lost. Table 4. E ects of irrigation treatments on some yield parameters in processing tomatoes cv. Hypeel F1. Table 4. Effects of irrigation treatments on some yield parameters in processing tomatoes cv. Hypeel Values followed by the same letter do not statistically di er at p 0.05 (Tukey’s test). IWUE: irrigation F1. Values followed by the same letter do not statistically differ at p ≤ 0.05 (Tukey’s test). IWUE: water use eciency. irrigation water use efficiency. 1 3 Irrigation Treatment Yield Losses (%) Water Saving (%) Fruit Yield (t ha ) IWUE (kg m ) NI 3.81 d 92.5 88.9 8.46 e F 51.02 a - - 12.60 cd D 42.96 a 15.8 44.4 19.09 a FE 15.85 c 68.9 70.1 13.10 cd DE 12.06 cd 76.4 79.5 14.53 c FFL 23.10 b 54.7 48.4 11.05 d DFL 21.41 bc 58.0 68.6 16.86 b No significant di erence in final yield was observed between the two rates of irrigation (full and deficit), irrespective of the irrigation scheduling (irrigation cut-o before the start of flowering or irrigation at flowering only). -1 Fruit production (g plant ) Agronomy 2020, 10, 800 13 of 17 Irrigation water use eciency (IWUE) was maximized in D treatments (IWUE >19 kg m ). IWUE in FE and DE was greater than 13 kg m ; however, yields were not economically convenient (yield losses >69%). Irrigation limited to the flowering period had low eciency at a 100% rate (FFL, 3 3 IWUE 11.05 kg m ) but high at a 50% rate (DFL, IWUE >16 kg m ). 3.9. Relationships of Physiological Parameters vs. Plant Production Traits Plant water status significantly influenced the rate of dry biomass accumulation along the crop season. Positive relationships were described between the water potential, leaf transpiration and stomatal conductance at 55 DAT vs. a maximum value of CGR, i.e., that calculated between 53 and 60 DAT (r = 0.90 ** for and 0.97 *** for both E and g ) (Table 5). Table 5. Correlation coecients (r) among the physiological and productive traits in processing tomatoes cv. Hypeel F1. CGRmax: maximum crop growth rate. vs. CGRmax 0.90 ** 55DAT E vs. CGRmax 0.97 *** 55DAT g vs. CGRmax 0.97 *** s55DAT E vs. n. flowers 0.91 ** 41DAT 46DAT g vs. n. flowers 0.91 ** s41DAT 46DAT E vs. n. fruits 0.92 ** 41DAT 60DAT g vs. n. fruits 0.96 *** s41DAT 60DAT Flowers (n) vs. fruits (n) 0.97 *** 46DAT 60DAT ns Flowers (n) vs. fruits (n) 0.31 55DAT 60DAT Flowers (n) vs. yield 0.88 ** 46DAT ns Flowers (n) vs. yield 0.19 53DAT ns Flowers (n) vs. yield 0.17 60DAT E vs. fruit yield 0.88 ** 41DAT E vs. fruit yield 0.84 ** 48DAT E vs. fruit yield 0.88 ** 55DAT g vs. fruit yield 0.88 ** s41DAT g vs. fruit yield 0.85 ** s48DAT g vs. fruit yield 0.86 ** s55DAT vs. fruit yield 0.96 *** 63DAT ** and ** significant at p 0.01 (**) and p 0.001 (***); ns: not significant. The plant water status significantly a ected the reproductive process. Indeed, positive relationships (r = 0.91**) were described between leaf transpiration at 41 DAT (a few days after the restart of irrigation in FFL and DFL) and the number of flowers measured at 46 DAT, indicating that good soil water conditions during flowering positively a ect the plant water status and, thus, the reproductive activity. As a result, those plants highly transpiring produced more flowers than those less transpiring. Flowers produced at 46 DAT were also positively correlated with stomatal conductance at 41 DAT (r = 0.91**). Even closer positive relationships of leaf transpiration (r = 0.92**) and stomatal conductance (r = 0.96***) at 41 DAT were described vs. the number of fruits at 60 DAT, i.e., those deriving from flowers produced earlier (at 46 DAT). Indeed, the number of fruits produced at 60 DAT was in turn positively correlated with that of flowers measured at 46 DAT (r = 0.97***) but not with that of flowers ns produced later on (53 DAT, r = 0.31 ). This indicates that, irrespective of the experimental conditions, more or less all flowers first produced turned into fruits, but only a portion of those produced later (after 53 DAT) in response to reirrigation at flowering (as occurred in FFL and DFL treatments) produced fruits. Indeed, the final yield result positively correlated with the number of flowers produced early ns (r = 0.88**) but not with those produced late (at 53–60 DAT, r < 0.2 ). Plant water status greatly a ected the final fruit yield. Indeed, the leaf transpiration and stomatal conductance measured during flowering (up to approximately 55 DAT) well predicted the final plant productivity, being well-correlated with the final fruit yield (r > 0.84**). As well, good plant water Agronomy 2020, 10, 800 14 of 17 conditions later on, at fruit onset, as indicated by a low predawn water potential at 63 DAT, positively influenced the final fruit yield (r = 0.96***). 4. Discussion Tomatoes are reported as moderately sensitive to water stress, with sensitivity mostly depending on the cultivar and the growing stage at which soil water deficit occurs [3,4]. In this research, the physiological responses of processing tomatoes to irrigation at di erent rates and critical stages were examined in a semi-arid environment. Under full irrigation conditions over the growth season, the plants exhibited the highest rates of both leaf transpiration and stomatal conductance; this was mostly because of the high turgor capacity [21]. Conversely, under water-stressful conditions, plants tended to close the stomata (low g ) in order to limit water losses through transpiration (low E) [7]. Nevertheless, according to the observed level of ASWC, close to the wilting point all along the flowering period and later on (from 40 DAT onward), plants not irrigated from flowering (FE and DE) 2 1 still survived, as revealed by the high values of E (>4.44 mmol H O m s ) up to 55 DAT, even at the long-term 100% soil water deficit. These observations suggest that tomato plants, although sensitive to water stress, may survive to a prolonged soil water deficit. The relationships among the di erent traits were also examined for a better comprehension on how the physiological parameters are associated with plant productivity in processing tomatoes when irrigation is applied at critical stages. However, it is well-known that the soil texture greatly a ects water availability and, thus, the plant hydraulic status [22]; therefore, it is feasible to expect the same physiological response in tomato plants under soil features similar to those of the present study. According to what was observed in a cultivar of processing tomatoes cultivated under climatic conditions similar to those of the present research [16], the plant water status is not the only factor regulating stomatal aperture. Indeed, the atmospheric conditions experienced by tomato plants during the growing season strongly influenced their physiological response to irrigation, and even in well-watered plants, the vapor pressure deficit (VPD), when exceeding 1.8 kPa, limited the stomatal opening, thus reducing the plant-water flux to the atmosphere. As a result, both the stomatal conductance and leaf transpiration were strongly reduced in the F treatment, although the corresponding predawn water potential was still quite high (0.2 MPa). Similarly, Thompson et al. [23] reported that low humidity (i.e., high VPD) reduces g in tomatoes, with a di erent extent depending on the genotype. Besides seasonal trends, the same e ects of a changing VPD upon leaf transpiration, stomatal conductance and assimilation patterns were observed in well-irrigated plants of a grapevine. In particular, while no clear daily changes occurred in gas exchanges under a low atmospheric evaporative water demand (i.e., low VPD), a decrease in both E and g , as well as in the assimilation rate, occurred under a high atmospheric evaporative water demand (i.e., high VPD) [24]. Close positive relationships between the leaf transpiration and stomatal conductance measured at early flowering vs. the number of flowers produced indicated how the plant water status at flowering greatly a ected its reproductive behavior (the higher the leaf transpiration and stomatal conductance, the greater the number of flowers produced). Indeed, flowering has been reported as the most sensitive stage of tomatoes to water stress [25,26]. Torrecillas et al. [27] noticed that, di erently than what happened in wild types, plants of domesticated tomatoes promptly reacted to temporary rewatering after su ering a prolonged period of water stress through a fast stomata reopening. This did not occur in wild tomatoes, where six days after rewatering, stomata were still closed, allowing plants to retain turgor. The high E and g measured in the current research in FFL and DFL during flowering after a long-term soil water deficit may reveal a prompt reaction of tomato plants to rewatering but, at the same time, an inecient stomatal control for water losses, which involves an inadequate plant recovery once irrigation is suspended again. In fact, high levels of E and g as measured at the end of flowering or even later did not involve high yields, basically because not all flowers produced in large amounts later on in response to rewatering (as in FFL and DFL treatments) produced fruits. With this in mind, E and g measured at early or mid-flowering, more than those measured at the end of this stage or s Agronomy 2020, 10, 800 15 of 17 later on, may be considered as valuable indicators to predict crop productivity in processing tomatoes. Similar results were obtained in a germplasm of local tomatoes cultivated in a semi-arid environment of Sicily, where the greatest yields were achieved with those genotypes with the highest levels of leaf transpiration measured at 50 DAT [28]. The water potential was not measured at the floral initiation. However, when values of at 55 DAT (beyond mid-flowering) were regressed vs. E and g measured at the same time, strict relationships were observed (r = 0.93 ** in both cases); i.e., the plant water status greatly a ects its physiological behavior. Therefore, it is likely that the water potential, if measured previously (e.g., at 41 DAT, as for E and g ), would be correlated to the final yield even more strictly than the leaf transpiration and stomata conductance were. Moreover, a high VPD depresses the rates of both the leaf transpiration and stomatal conductance, therefore altering the physiological response of the crop even under unrestricted soil water conditions. Contrastingly, the predawn was less influenced by high temperatures and low air humidity, keeping low values under full irrigation, even at a high VPD. In this research, the fruit yield was maximized when irrigation was applied at the highest rate (100% ETc) for the whole season. However, the adoption of a deficit irrigation strategy where irrigation at a lower rate (50% ETc) for the whole season is applied allowed to reduce yield losses to a minimum (<16%) while saving a great amount of water (up to 44%). This result somehow provides evidence that deficit irrigation at flowering did not significantly compromise the allocation of the plant energy sources, resulting in only very limited productivity losses. Irrigation only at the vegetative stage adversely a ected the crop productivity, causing yield losses >68%. In turn, irrigation limited to the flowering period, even at a reduced rate (50% ETc), slightly alleviated the water stress induced by a very early cut-o of irrigation, leading to a final yield that, although moderate, was anyway greater than that obtained with an early suspension of irrigation at the flowering onset. This is consistent with the literature, where a greater impact of water stress during flowering than during the vegetative stage, on the fruit yield, mainly ascribable to floral abortion, has been reported on tomatoes [1,6]. However, irrigation limited to the flowering period was not as beneficial to the tomato crop as expected, especially when irrigation was applied at the highest rate (100%). Indeed, in FFL and DFL treatments, although the number of fruits measured at 60 DAT was even higher than that of the D treatment, the final yield was significantly lower. In particular, in FFL, yield losses (55%) were greater than water saving (48%) (low IWUE). Studies evidenced how, in tomatoes, the water deficit at any growth stage does not adversely a ect the number of fruits produced but significantly reduces their single weight [8,14]. According to the literature [4,5,14], the IWUE was positively a ected by the water deficit. A high water productivity (IWUE >13 kg m ) corresponded to the plot with irrigation during the vegetative stage only (FE and DE). Similarly, da Silva et al. [15] observed that the highest levels of water productivity in tomatoes occurring with a 50% irrigation replacement, and in relation to irrigation suspension, the longer the number of days without the irrigation before a harvest, the higher the water productivity. In the current study, yields in FE and DE were not economically sustainable (<16 t ha ). This fact highlights how irrigation for the whole season, even at reduced rates, is important to minimize fruit losses in processing tomatoes. Similar findings were reported for some cultivars of processing tomatoes cultivated under the same climatic conditions of Eastern Sicily [3,4,29]. 5. Conclusions The results of the present study reveal how the irrigation limited to the vegetative stage or to flowering, at a full (100% ETc) or reduced rate (50% ETc), greatly influences the physiological behavior of tomato plants cultivated under a semi-arid environment. Leaf transpiration and stomatal conductance measured at early or mid-flowering, more than that measured later on, may be adopted as valuable indicators to predict the crop productivity. However, their accuracy may be altered under particular environmental conditions (i.e., a high vapor pressure deficit (VPD)), being strongly hindered even under unrestricted soil water conditions. In this sense, the predawn water potential, being little Agronomy 2020, 10, 800 16 of 17 a ected by the VPD, is more reliable than the leaf transpiration and stomatal conductance under these climatic conditions. The results also confirm that, in tomatoes, irrigation for the whole season is important to maximize the fruit yield. However, a balance between the improved irrigation water use eciency (IWUE) and satisfactory yield can be achieved through the adoption of a deficit irrigation strategy where a moderate water stress is induced by irrigation at a 50% ETc rate. Indeed, the adoption of irrigation strategies that optimize (reaching the most sustainable value), more than maximizing (reaching the overall maximum value) the IWUE, may contribute to making the crop more profitable. The flowering stage is confirmed as sensitive to drought stress; therefore, severe soil water deficits during this stage adversely a ect crop productivity, leading to final low fruit yields. Indeed, yield losses were greater when the irrigation was suspended during flowering. Alternatively, in areas of dry summers where irrigation water is scarcely available, as that of the present experiment, irrigation could be omitted during the vegetative stage and limited (at a reduced rate, e.g., 50% ETc) to the flowering period, keeping in mind that water-saving is more or less proportional to yield losses. Author Contributions: Conceptualization, S.L.C.; Data curation, C.P., G.T. and D.S.; Formal analysis, C.P. and S.A.C.; Investigation, C.P., G.T. and S.L.C.; Methodology, C.P., G.T., D.S. and S.L.C.; Software, S.A.C. and D.S.; Validation, D.S.; Writing—original draft, C.P.; Writing—review & editing, C.P., S.L.C. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: The authors are gratefu l to Giancarlo Patanè, University of Catania, for his technical assistance in the field. Conflicts of Interest: The authors declare no conflicts of interest. References 1. Nangare, D.D.; Singh, Y.; Kumar, P.S.; Minhas, P.S. Growth, fruit yield and quality of tomato (Lycopersicon esculentum Mill.) as a ected by deficit irrigation regulated on phenological basis. Agric. Water Manag. 2016, 171, 73–79. [CrossRef] 2. FAOSTAT. (Food and Agriculture Organization of the United Nations), Statistics Division. 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Physiological screening for drought tolerance in Mediterranean long-storage tomato. Plant Sci. 2016, 249, 25–34. [CrossRef] 29. Patanè, C.; Saita, A. Biomass, fruit yield, water productivity and quality response of processing tomato to plant density and deficit irrigation under a semi-arid Mediterranean climate. Crop Pasture Sci. 2015, 66, 224–234. [CrossRef] © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agronomy Multidisciplinary Digital Publishing Institute

Physiological and Agronomic Responses of Processing Tomatoes to Deficit Irrigation at Critical Stages in a Semi-Arid Environment

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agronomy Article Physiological and Agronomic Responses of Processing Tomatoes to Deficit Irrigation at Critical Stages in a Semi-Arid Environment 1 , 2 2 2 Cristina Patanè *, Sebastiano Andrea Corinzia , Giorgio Testa , Danilo Scordia 1 , 2 and Salvatore Luciano Cosentino CNR-Istituto per la BioEconomia (IBE), Sede Secondaria di Catania, Via P. Gaifami 18, 95126 Catania, Italy; sl.cosentino@unict.it Dipartimento di Agricoltura, Alimentazione e Ambiente, Università degli Studi di Catania, via Valdisavoia 5, 95123 Catania, Italy; andrea.corinzia@unict.it (S.A.C.); gtesta@unict.it (G.T.); dscordia@unict.it (D.S.) * Correspondence: cristinamaria.patane@cnr.it; Tel.: +39-095-733-8395 Received: 9 May 2020; Accepted: 1 June 2020; Published: 4 June 2020 Abstract: Deficit irrigation is a valid alternative to conventional irrigation to save water while maintaining high productivity in tomatoes. However, crop sensitivity to water stress due to deficit irrigation may change with the growth stage. To assess the physiological and agronomic responses of processing tomatoes to deficit irrigation applied at critical stages, a field experiment was conducted in a coastal site of Southern Italy, where seven irrigation treatments di ering for daily evapotranspiration (ETc) restored (100%—full or 50%—deficit) and the time of watering (long-season or limited to the vegetative period or to flowering) were applied to processing tomatoes cv. Hypeel F1. Plants continuously irrigated and those irrigated only at flowering maintained higher rates of leaf transpiration (E) and stomatal conductance (g ) over those irrigated only during the vegetative period. Fruit yield was the greatest under long-season full irrigation (51 t ha ). Severe soil water deficit during flowering, more than during the vegetative period, adversely a ected crop productivity. Irrigation water use eciency (IWUE) was maximized under long-season deficit irrigation (>19 kg m ) or deficit irrigation during flowering (>16 kg m ). E and g measured at early or mid-flowering may be adopted as valuable indicators to predict crop productivity; however, they may be altered under high vapor pressure deficit (VPD). Predawn water potential, being little a ected by VPD, is a more reliable parameter than leaf transpiration and stomatal conductance under these climatic conditions. Keywords: processing tomatoes; deficit irrigation; soil water content; leaf transpiration; stomatal conductance; vapor pressure deficit; water use eciency 1. Introduction Tomatoes (Solanum lycopersicum L.) are an important economic crop worldwide, with the greatest area of cultivation among vegetables [1]. In 2018, the total tomato production exceeded 182 million tons over a cultivation area of 4.7 million hectares [2]. Tomatoes have a subtropical origin, thus requiring large amounts of irrigation water during summer, which is the cropping season for processing tomatoes in dry areas of Southern Italy. However, in these areas, the scarce availability of irrigation water resources and the lack of rainfall during summertime limit a sustainable cultivation for high water-demanding crops, such as processing tomatoes; besides, the irrigation issues have seriously been worsened due to climate change e ects. Indeed, to maximize tomato yields, soil water availability at the root zone must be maintained near field capacity throughout the growth period [3]. Under a semi-arid environment, the development of water-saving irrigation strategies may encourage farmers to revise their irrigation scheduling approach towards a more ecient water Agronomy 2020, 10, 800; doi:10.3390/agronomy10060800 www.mdpi.com/journal/agronomy Agronomy 2020, 10, 800 2 of 17 management, in order to limit water consumption and bring to satisfactory yields. Deficit irrigation approaches result in a reduced water application while maintaining adequate yields and enhancing overall fruit quality [4]. This is also for tomatoes, where the validity of the adoption of this water-saving irrigation strategy has been largely documented [4–7]. One of the greatest benefits of deficit irrigation is that, besides saving large amounts of water, it allows to lessen the production costs, to improve water productivity (i.e., the eciency in its use) and, overall, to reduce the impact of the crop to the environment, as compared to conventional irrigation [8]. However, not all stages of the crop-growing season are sensitive to water stress due to deficit irrigation similarly. In tomato crops, the most sensitive phenological phase to water stress is generally flowering [6]. Significant e ects of water deficit at fruit ripening on tomato yields under greenhouse conditions have been also reported [9]. The relationship between soil water deficits at critical stages and the physiological and productive behavior of tomatoes is quite complex and long studied, although controversial results have been reported [1]. Models to estimate the e ects of evapotranspiration (ET) were developed as well, either at each growth stage or for the whole growth period, on crop yields. Some of them, like the date crop water production function (DCWPF) [10] or Minhas model with its water deficit sensitivity indexes [11] can be applied to optimize the irrigation water management in areas of water scarcity. As aforementioned, the e ects of irrigation at di erent stages of the crop growing season have been extensively studied in tomatoes, although mostly upon fruit yield and quality [12–15]. However, detailed studies on the relationships between crop physiology and growth in field-grown tomatoes exposed to di erent deficit irrigation regimes are still lacking. The identification of the most critical stages to water stress through the measurement of some plant water status parameters may contribute to a better manipulation of deficit irrigation in processing tomatoes. Indeed, both soil water and climate conditions may greatly a ect the physiological parameters (stomatal conductance, transpiration and pre-dawn leaf water potential) of the crop, even under unrestricted soil water content conditions [16]. The goal of this study was to assess the e ects of deficit irrigation applied to the crop-growing season or at critical stages on physiology, growth, yield and water use eciency in field-grown processing tomatoes under a semi-arid Mediterranean environment of South Italy, in order to identify the most water stress-sensitive period and optimize irrigation water management under water scarcity conditions. 2. Materials and Methods 2.1. Open-Field Experiment Field experiment was conducted during the 2012 season in a site on the Eastern coast of Sicily 0  0 (South Italy, 10 m a.s.l., 37 03 N Lat, 15 18 E Long) on a moderately deep Calcixerollic Xerochrepts soil. The soil characteristics were: clay 24.0%, sand 35.0%, silt 41.0%, organic matter 1.20%, pH 8.0, total N 1 1 3 0.5%, available P 48 mg kg , exchangeable K 940 mg kg , bulk density 1.3 g cm , field capacity 1 1 (0.03 MPa) 0.25 g g and wilting point (1.5 MPa) 0.15 g g . Fallow preceded the cultivation of tomato crops. In a randomized complete block experimental design with three replicates, seven irrigation treatments were studied (Table 1). The cultivar Hypeel F1 (Seminis Inc., Oxnard, CA, USA) of the processing tomato (Solanum lycopersicum L.) was used for the experiment. Plants were transplanted at the four-leaf stage on June 9 in a single plot of 38.4 m (4.8 m 8 m). Plants were spaced at 0.75 m between rows and 0.40 m within rows, resulting in a plant 2 1 density of approximately 3.3 plants m . Before transplanting 75, 100 and 100 kg ha of N (as ammonium sulphate), P O (as mineral perphosphate) and K O (as potassium sulphate), respectively, 2 5 2 were distributed. Approximately 30 days after transplant (DAT), a further 75 kg ha of N (as ammonium nitrate) was supplied as top dressing. Agronomy 2020, 10, 800 3 of 17 Table 1. Description of the di erent irrigation treatments applied to the processing tomato cv. Hypeel F1. ETc: daily evapotranspiration. Seasonal Volume of Water Irrigation Treatment Description 3 1 (m ha ) NI (no irrigation) Irrigation up to seedling establishment 450 F (full, control) Long-season irrigation, 100% ETc restoration 4050 D (deficit) Long-season irrigation, 50% ETc restoration 2250 Short-season irrigation, early cut-o at the onset of FE (full, early) 1210 flowering, 100% ETc restoration Short-season irrigation, early cut-o at the onset of DE (deficit, early) 830 flowering, 50% ETc restoration FFL (full, flowering) Irrigation only during flowering, 100% ETc restoration 2090 DFL (deficit, flowering) Irrigation only during flowering, 50% ETc restoration 1270 A drip-irrigation system was used. At the time of transplanting, the irrigation water was supplied to fulfil the field capacity at approximately 0.3 m of depth. Thereafter, the volume of irrigation water to supply was determined on the basis of the maximum available soil water content (ASWC) in the first 0.4 m of soil, where most of roots are expected to grow, calculated with the following formula: V = 0.66 (FC WP)   D (1) where V = water amount (approximately 34 mm), 0.66 = fraction of promptly available soil water permitting unrestricted evapotranspiration, FC = soil water at field capacity (25% of soil dry weight), WP = soil water at wilting point (15% of soil dry weight),  = bulk density (g cm ) and D = soil depth (0.4 m). Irrigation water was supplied when the sum of daily evapotranspiration (ET ) corresponded to V: ETc = ET  k  k (2) 0 p c where ET = reference ET, measured by means of a class A pan (mm), k = pan coecient, equal to 0.80 in a semi-arid environment and k = crop coecient [3]. Total amount of water distributed to each irrigation treatment is reported in Table 1. No chemical herbicides were used for weed control. A hand-weeding was performed once only, since the crop covered the soil, and weeds could no longer grow. The following meteorological variables were recorded daily throughout the crop-growing season: air temperature, rainfall, class A pan evaporation, using a data logger (CR10, Campbell Scientific, Logan, UT, USA) located approximately 50 m from the experimental field. Along the experiment from mid-July, when plants started to flower, to the end of August, when they were at the ripening stage of fruits, soil water content was measured, at 2 to 3-day intervals, by means of gypsum blocks (Soilmoisture Equipment Corp., Santa Barbara, CA, USA) located at 0.15 and 0.30-m soil depths in all replicates of each irrigation treatment. Thereafter, the available soil water content (ASWC), as a percentage of the maximum available water and according to the following formula, was calculated [17]: ASWC = (WC WP)/(FC WP) 100 (3) 1 1 where WC = soil water content (g g dry soil), FC = soil water content at field capacity (0.25 g g dry soil) and WP = soil water content at the wilting point (0.15 g g dry soil). ASWC ranged between 100% (field capacity) and 0% (wilting point). 2.2. Physiological Measurements 2 1 2 1 Leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , mol m s ) were 2 s measured along the growing season at 10 subsequent dates after transplanting (DAT) from mid-July to Agronomy 2020, 10, 800 4 of 17 the end of August by means of a null balance “steady-state” porometer (Model LI-1600, Li-Cor, Inc., Lincoln, NE, USA). Measurements were made on clear sunshine hours between 11:00 h and 13:00 (solar time) in fully developed and healthy leaves. One reading was carried out on three randomly chosen, fully expanded young leaves from each plot. Leaf water potential ( , MPa) was also measured before sunrise (03:00–05:00 h solar time, “pre-dawn” water potential) at 3–5-day intervals starting in August up to early September by means of a pressure chamber (Soilmoisture Equipment Corp., Santa Barbara, CA, USA). Briefly, a leaflet was excised at the petiole level from a young fully expanded leaf (on the top part of the plant) using a razor blade. The leaflet was partly sealed in the pressure chamber, with the cut end of the petiole protruding through the seal. The chamber was pressurized with compressor gas until the appearance of water in the cut surface (detectable using a magnifying glass). At that point, the pressure was recorded. As for E and g , one reading was carried out on three randomly chosen, fully expanded young leaves from each plot. 2.3. Plant Measurements At five dates, from middle of July to early August (34, 38, 46, 53 and 60 DAT), two representative plants were sampled destructively from each experimental plot, and flowers and fruits (when present) were counted. After that, plant parts (root, stem, leaves, flowers and fruits when present) were dried in a thermo-ventilated oven at 65 C until constant weight (about 3 days) for dry matter (DW) measurement (g DW plant ). 2.4. Calculations The crop was hand-harvested when the ripe fruit rate reached ~95% (early September). At harvest, 1 3 total fruit yield (t ha ) was measured, and irrigation water use eciency (IWUE, kg m ) was calculated from the di erent irrigation treatments as the ratio of total yield (kg) and total water applied by irrigation (m ) [13]. 2.5. Statistical Analyses Data of physiological (E, g and ) and plant production (number of flowers, number of fruits, shoot dry weight, root dry weight and fruit production) measurements were subjected to a one-way repeated-measures analysis of variance (ANOVA) where date of measurement represents the within-subjects factor and the irrigation treatment the between-subjects factor (SPSS, PASW Statistics 18). When the Mauchly’s sphericity test failed to meet the assumption of sphericity, the univariate results were adjusted by using the Greenhouse-Geisser Epsilon and the Huynh-Feldt Epsilon correction factors. Following the univariate test satisfying the sphericity for within-subject e ects, the F-values and associated p-values for between-subject e ects were tested. Means were separated by the Tukey’s test at a 95% confidence level. For data of the number of flowers and number of fruits per plant, shoot dry weight and root dry weight, a supplemental ANOVA was carried out separately for the date of measurement. Data of final yield and irrigation water use eciency (IWUE) were statistically analyzed by a one-way analysis of variance (ANOVA) using CoStat version 6.003 (CoHort Software, Monterey, CA, USA). Di erences between means were evaluated as described above. Plant dry weight variations over time were interpolated by a nonlinear iterative regression method (SigmaPlot11, Systat Software Inc., San Jose, CA, USA) using the following exponential function: y = (4) 1 + 0 Agronomy 2020, 10, x FOR PEER REVIEW 5 of 18 Data of final yield and irrigation water use efficiency (IWUE) were statistically analyzed by a one-way analysis of variance (ANOVA) using CoStat version 6.003 (CoHort Software, Monterey, CA, USA). Differences between means were evaluated as described above. Plant dry weight variations over time were interpolated by a nonlinear iterative regression method (SigmaPlot11, Systat Software Inc., San Jose, CA, USA) using the following exponential function: Agronomy 2020, 10, 800 5 of 17 𝑦 = (4) 1 + ( ) where a = maximal value of y, x = time (DAT), x = time (DAT) to reach 50% of maximal value a where a = maximal value of y, x = time (DAT), x0 = time (DAT) to reach 50% of maximal value a and and b = fitting parameter of the curve. Thereafter, using values of the curve, crop growth rate (CGR, b = fitting parameter of the curve. Thereafter, using values of the curve, crop growth rate (CGR, g DW 1 1 g DW plant d ) was calculated as follows: −1 −1 plant d ) was calculated as follows: CGR = (W W )/(t t ) (5) 2 1 1 2 𝐶𝐺𝑅 = (𝑊 − 𝑊 )/(𝑡 − 𝑡 ) (5) 2 1 1 2 where W2 and W1 are the values of the plant dry weight (g) at times t2 and t1, respectively, on the where W and W are the values of the plant dry weight (g) at times t and t , respectively, on the 2 1 2 1 curve. Finally, the maximum value of CGR (CGRmax) was considered [18]. curve. Finally, the maximum value of CGR (CGRmax) was considered [18]. The relationships between leaf transpiration and stomatal conductance measured in plants The relationships between leaf transpiration and stomatal conductance measured in plants under under no water limitation (F treatment) and vapor pressure deficit (VPD, kPa) in the atmosphere no water limitation (F treatment) and vapor pressure deficit (VPD, kPa) in the atmosphere were were described by using a nonlinear function (SigmaPlot11, Systat Software Inc., San Jose, CA, USA). described by using a nonlinear function (SigmaPlot11, Systat Software Inc., San Jose, CA, USA). VPD VPD was calculated using air relative humidity (RH, %) and air temperature (°C) recorded by the was calculated using air relative humidity (RH, %) and air temperature ( C) recorded by the same same “steady-state” porometer at the moment of physiological measurements [19]. “steady-state” porometer at the moment of physiological measurements [19]. 3. Results 3. Results 3.1. Meteorological Trend 3.1. Meteorological Trend The meteorological course during the crop-growing season was typical of the semi-arid The meteorological course during the crop-growing season was typical of the semi-arid Mediterranean environment, with a hot and dry summer (Figure 1). Mediterranean environment, with a hot and dry summer (Figure 1). 50 11 rain 10 Tmax Tmin ET 0 1 0 0 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88 92 Days after transplant Figure 1. Meteorological course (maximum and minimum air temperatures, rainfall, and reference Figure 1. Meteorological course (maximum and minimum air temperatures, rainfall, and reference evapotranspiration (ET0)) recorded during the field experiment. evapotranspiration (ET )) recorded during the field experiment. Maximum Maximum temperatur temperature e ranged ranged between betwee 27.6 n 27.6 C (in °C June) (in Ju and ne) 43.4 andC 43.4 (in July), °C (in witJu h the ly), minimum with the between minimum 14.0 between C (in14.0 June) °Cand (in 22.4 June) C and (in 22. July). 4 °C T(i otal n Jul rainfall y). Total up rto ainfall August up to was August <10 mm; was ther <10 efor mm e, ; soil therefore, water soi availability l water avail wasabi totally lity w due as tto otal irrigation. ly due toRefer irriga ence tion. evapotranspiration Reference evapotranspir (ET ) follows ation (ET the 0) −1 course follows of th the e course air temperatur of the air e,tem and perat values ure, exceeding and values 9 mm exceed d ing wer9 e mm recor d ded were in the recorded first 10-day in the period first and 10-dat aythe perio end d a of nd July at t . he end of July. 3.2. Soil Water Content Soil water content fluctuated during the growth season, according to the irrigation time. It maintained the highest levels at both soil depths under the F regime throughout the crop-growing season (Figure 2). However, even under these experimental conditions, despite continuous irrigation, soil water deficits sometimes exceeded 66% (threshold for irrigation). Indeed, the volume of water supplied by irrigation (approximately constant) was indirectly calculated on the ETc basis, not on the actual soil water content at the irrigation time [20]. Therefore, it is likely that this volume of water sometimes was not adequate to fill the soil up to field capacity even under the F regime. Air temperature (°C) Rainfall, ET (mm) 0 Agronomy 2020, 10, x FOR PEER REVIEW 6 of 18 3.2. Soil Water Content Soil water content fluctuated during the growth season, according to the irrigation time. It maintained the highest levels at both soil depths under the F regime throughout the crop-growing season (Figure 2). However, even under these experimental conditions, despite continuous irrigation, soil water deficits sometimes exceeded 66% (threshold for irrigation). Indeed, the volume of water supplied by irrigation (approximately constant) was indirectly calculated on the ETc basis, not on the actual soil water content at the irrigation time [20]. Therefore, it is likely that this volume of water Agronomy 2020, 10, 800 6 of 17 sometimes was not adequate to fill the soil up to field capacity even under the F regime. 15 cm NI 30 cm 100 0 80 F 15 cm Plot 1 Upper specification 100 30 cm 100 0 FE 100 0 DE 100 0 FFL 100 0 DFL 30 35 40 45 50 55 60 65 70 75 80 85 90 Days after transplant Figure 2. Available soil water contents at depths of 15 cm (red line) and 30 cm (blue line) in each Figure 2. Available soil water contents at depths of 15 cm (red line) and 30 cm (blue line) in each irrigation treatment. Constant horizontal short-dash line indicates the minimum threshold of the irrigation treatment. Constant horizontal short-dash line indicates the minimum threshold of the available soil water content. NI: no irrigation, F: full, D: deficit, FE: full early, DE: deficit early, FFL: full available soil water content. NI: no irrigation, F: full, D: deficit, FE: full early, DE: deficit early, FFL: flowering and DFL: deficit flowering. full flowering and DFL: deficit flowering. In the D treatment, irrigation tended to fulfil the upper layers of the soil. Under no irrigation In the D treatment, irrigation tended to fulfil the upper layers of the soil. Under no irrigation during flowering (NI, FE and DE), soil water contents during the measurements period were always during flowering (NI, FE and DE), soil water contents during the measurements period were always beneath the field capacity at both soil depths. In plots irrigated only at flowering, soil water contents beneath the field capacity at both soil depths. In plots irrigated only at flowering, soil water contents exhibited trends similar to that of the F regime, although, in FFL, only in the upper layer of soil. In DFL, the water content kept higher in the upper layers of the soil (15 cm), up to approximately 50 DAT. However, just after irrigation suspension (at 54 DAT), the soil water content in both FFL and DFL dropped to levels lower than the field capacity already at 57 DAT. Available soil water content (%) Agronomy 2020, 10, x FOR PEER REVIEW 7 of 18 exhibited trends similar to that of the F regime, although, in FFL, only in the upper layer of soil. In DFL, the water content kept higher in the upper layers of the soil (15 cm), up to approximately 50 DAT. However, just after irrigation suspension (at 54 DAT), the soil water content in both FFL and DFL dropped to levels lower than the field capacity already at 57 DAT. Agronomy 2020, 10, 800 7 of 17 3.3. Course of Leaf Transpiration and Stomatal Conductance 3.3. Course of Leaf Transpiration and Stomatal Conductance ANOVA evidenced a highly significant effect of the irrigation treatment (I) and time of measurement (T) upon all the physiological parameters examined (p ≤ 0.001) (Table 2). The significant ANOVA evidenced a highly significant e ect of the irrigation treatment (I) and time of measurement interaction I × T (p ≤ 0.001) suggests that the physiological response of tomato plants to changing soil (T) upon all the physiological parameters examined (p 0.001) (Table 2). The significant interaction water contents varies with the time of measurement. I  T (p  0.001) suggests that the physiological response of tomato plants to changing soil water contents varies with the time of measurement. Table 2. Repeated-measures ANOVA for main effects and interactions on the physiological traits. Table 2. Repeated-measures ANOVA for main e ects and interactions on the physiological traits. gs ψ Source df df E Adj MS g Adj MS Source df df Irrigation (I) 6 1615.2 *** 3.829 *** 6 1.350 *** Adj MS Adj MS Time (T) 9 1497.9 *** 3.367 *** 8 0.150 *** Irrigation (I) 6 1615.2 *** 3.829 *** 6 1.350 *** I × T 54 408.6 *** 0.811 *** 48 0.040 *** Time (T) 9 1497.9 *** 3.367 *** 8 0.150 *** I  T 54 408.6 *** 0.811 *** 48 0.040 *** Error (T) 126 267.8 0.823 112 0.011 Error (T) 126 267.8 0.823 112 0.011 Error 14 22.6 0.119 14 0.006 Error 14 22.6 0.119 14 0.006 Leaf transpiration—E, stomatal conductance—gs and predawn water potential—ψ. Degree of Leaf transpiration—E, stomatal conductance—g and predawn water potential— . Degree of freedom (df) and freedom (df) and adjusted mean square (Adj MS). Significant at p ≤ 0.001 (***). adjusted mean square (Adj MS). Significant at p 0.001 (***). Leaf transpiration (E) and stomatal conductance (gs) were measured from approximately a Leaf transpiration (E) and stomatal conductance (g ) were measured from approximately a month after transplanting (when plants were at the floral initiation and water treatments were overall month after transplanting (when plants were at the floral initiation and water treatments were overall differentiated) onward (Figure 3). In all the experimental situations, E exhibited an increasing trend di erentiated) onward (Figure 3). In all the experimental situations, E exhibited an increasing trend from the initial measurement up to approximately 50 DAT, when the first fruit buds were quite from the initial measurement up to approximately 50 DAT, when the first fruit buds were quite visible. −2 −1 visible. After that, E steeply decreased down to values ≤5.55 mmol H2O m s measured at 61 DAT 2 1 After that, E steeply decreased down to values 5.55 mmol H O m s measured at 61 DAT in all in all water treatments. water treatments. 2 1 2 1 Figure 3. Course of leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , mol m s ) during the growth period in processing tomatoes cv. Hypeel F1 under di erent irrigations. This was probably due to quite a low air humidity and quite a high air temperature recorded in that period (between 52 and 62 DAT), which determined a high VPD and, consequently, a high water demand from the atmosphere. This, in turn, induced a partial stomatal closure and a reduced E even Agronomy 2020, 10, x FOR PEER REVIEW 8 of 18 −2 −1 −2 −1 Figure 3. Course of leaf transpiration (E, mmol H2O m s ) and stomatal conductance (gs, mol m s ) during the growth period in processing tomatoes cv. Hypeel F1 under different irrigations. This was probably due to quite a low air humidity and quite a high air temperature recorded in that period (between 52 and 62 DAT), which determined a high VPD and, consequently, a high water Agronomy 2020, 10, 800 8 of 17 demand from the atmosphere. This, in turn, induced a partial stomatal closure and a reduced E even under the unrestricted soil water conditions in F. Indeed, an exponential function well describes the under the unrestricted soil water conditions in F. Indeed, an exponential function well describes the overall changes in E and gs measured in plants under good soil water conditions (those of F), overall changes in E and g measured in plants under good soil water conditions (those of F), according according to the variation in VPD (Figure 4). to the variation in VPD (Figure 4). −2 −1 2 1 Figure 4. Variation of leaf transpiration (E, mmol H2O m s ) and stomatal conductance (gs, mol Figure 4. Variation of leaf transpiration (E, mmol H O m s ) and stomatal conductance (g , 2 s −2 −1 2 1 m s ) in relation to the increase of the vapor pressure deficit (VPD, kPa) in the atmosphere under mol m s ) in relation to the increase of the vapor pressure deficit (VPD, kPa) in the atmosphere under full irrigation (F treatment) in processing tomatoes cv. Hypeel F1. Measurements were made between full irrigation (F treatment) in processing tomatoes cv. Hypeel F1. Measurements were made between 2 −21 −1 11:00 and 13:00, with PAR (Photosynthetic active radiation) varying from 1500 to 2000 μmol m s as 11:00 and 13:00, with PAR (Photosynthetic active radiation) varying from 1500 to 2000 mol m s as measured by the PAR sensor of the porometer. Symbols represent the observed values. Black vertical measured by the PAR sensor of the porometer. Symbols represent the observed values. Black vertical bars bars rrepr epresent esent the the s standar tandard d err eror ror. . The course of this function indicates that an increase in the VPD determines a progressive raise in The course of this function indicates that an increase in the VPD determines a progressive raise both parameters up to a maximum (at a VPD of approximately 1.9 kPa for E and 1.7 kPa for g on the in both parameters up to a maximum (at a VPD of approximately 1.9 kPa for E and 1.7 kPa for gs on curve). Beyond this, the values of E and g start to decline down to a minimum at 2.4 kPa of the VPD. the curve). Beyond this, the values of E an s d gs start to decline down to a minimum at 2.4 kPa of the Later on, the leaf transpiration increased again except under severe soil water deficit conditions VPD. (NI, FE and DE), thus slowly decreasing down to the minimum measured late in the growing season Later on, the leaf transpiration increased again except under severe soil water deficit conditions (82 DAT), when plants started to senesce. (NI, FE and DE), thus slowly decreasing down to the minimum measured late in the growing season Same trend was observed for stomatal conductance, although its maximum value was achieved (82 DAT), when plants started to senesce. later (approximately 55 DAT) than that measured for E. Same trend was observed for stomatal conductance, although its maximum value was achieved According to the water supply, plots continuously irrigated (F and D) and those receiving water at later (approximately 55 DAT) than that measured for E. flowering only (FFL and DFL) maintained higher rates of leaf transpiration and stomatal conductance According to the water supply, plots continuously irrigated (F and D) and those receiving water 2 1 over those exposed to a drying soil (NI, FE and DE), with maximum values11 mmol H O m s at flowering only (FFL and DFL) maintained higher rates of leaf transpiration and stomatal 2 1 (for E) and 0.56 mol m s (for g ) in all. conductance over those exposed to a drying soil (NI, FE and DE), with maximum values ≥11 mmol −2 −1 −2 −1 H2O m s (for E) and 0.56 mol m s (for gs) in all. 3.4. Course of “Predawn” Water Potential 3.4. Course of “Predawn” Water Potential The course of water potential ( ) at the first hours of the day (“predawn”) was measured under nonlimiting air temperature and relative humidity conditions to the plant-water flux (Figure 5). The course of water potential (ψ) at the first hours of the day (“predawn”) was measured under Predawn was measured during the growing season, starting from the first days of August (55 DAT), nonlimiting air temperature and relative humidity conditions to the plant-water flux (Figure 5). when plants were near the end of the flowering period, to early September (88 DAT). Under rainfed Predawn ψ was measured during the growing season, starting from the first days of August (55 conditions (NI), predawn kept always the lowest values (<0.50 MPa), and at the end of growing DAT), when plants were near the end of the flowering period, to early September (88 DAT). Under season, it was1.06 MPa. rainfed conditions (NI), predawn ψ kept always the lowest values (<−0.50 MPa), and at the end of Under no irrigation at flowering (FE and DE), exhibited a fluctuating trend, dropping down growing season, it was −1.06 MPa. to final values <0.70 MPa. Under a continuous water supply, always kept values0.38 MPa in plants fully irrigated (F), which indicated an adequate plant water status. In FFL and DFL, the water potential after the irrigation suspension was kept high, even if the soil water content kept constantly lower than the field capacity from 57 DAT onward. Agronomy 2020, 10, 800 9 of 17 Agronomy 2020, 10, x FOR PEER REVIEW 9 of 18 Figure 5. Course of “predawn” water potential (ψ, MPa) during the growth period in processing Figure 5. Course of “predawn” water potential ( , MPa) during the growth period in processing tomatoes cv. Hypeel F1 under different irrigation treatments. tomatoes cv. Hypeel F1 under di erent irrigation treatments. 3.5. Course of Shoot and Root Dry Biomasses Under no irrigation at flowering (FE and DE), ψ exhibited a fluctuating trend, dropping down to final values <−0.70 MPa. Under a continuous water supply, ψ always kept values ≥−0.38 MPa in The statistical analysis evidenced a significant e ect of the irrigation treatment (I) and time of plants fully irrigated (F), which indicated an adequate plant water status. In FFL and DFL, the water measurement (T) upon both the shoot and root dry biomasses (p  0.001). However, significant potential after the irrigation suspension was kept high, even if the soil water content kept constantly interactions (p 0.01) were also observed (Table 3). lower than the field capacity from 57 DAT onward. Table 3. Repeated-measures ANOVA for the main e ects and interactions on plant production traits. 3.5. Course of Shoot and Root Dry Biomasses Shoot Dry Weight Root Dry Weight Flowers (n) Fruits (n) Plant Production Source df The statistical analysis evidenced a significant effect of the irrigation treatment (I) and time of Adj MS measurement (T) upon both the shoot and root dry biomasses (p ≤ 0.001). However, significant Irrigation (I) 6 10,321.0 *** 531.4 *** 783.2 * 617.0 *** 54,205 *** Time (T) 4 51,653.7 *** 627.2 *** 8567.8 *** 5651.8 *** 544,211 *** interactions (p ≤ 0.01) were also observed (Table 3). I T 24 1581.3 *** 62.51 ** 496.1 * 248.5 *** 28,155 *** Error (T) 56 76.5 32.5 261.5 53.1 2216.0 Table 3. Repeated-measures ANOVA for the main effects and interactions on plant production traits. Error 14 157.0 14.71 246.5 67.2 2240.0 Number of flowers and number of fruits per plant, shoot and root dry weight, fruit plant production. Degree of Shoot Dry Root Dry Flowers Plant freedom (df) and adjusted mean square (Adj MS). Significant at p 0.05 (*), p 0.01 Fruit (**) and s (np) 0.001 (***). Weight Weight (n) Production Source df Adj MS Indeed, the above-ground dry biomass progressively increased in all experimental situations Irrigation 6 10,321.0 *** 531.4 *** 783.2 * 617.0 *** 54,205 *** (Figure 6). Up to approximately 38 DAT, no great di erence was evidenced among the irrigation (I) treatments in the rate of biomass accumulation. After that, plants irrigated up to floral initiation (FE and Time (T) 4 51,653.7 *** 627.2 *** 8567.8 *** 5651.8 *** 544,211 *** DE treatments) accumulated dry biomasses with lower rates and 53 days after transplant; when plants I × T 24 1581.3 *** 62.51 ** 496.1 * 248.5 *** 28,155 *** were near the end of flowering, no further plant growth occurred. Under these experimental situations, Error (T) 56 76.5 32.5 261.5 53.1 2216.0 the total dry biomass started to increase again later on due to the fruit-set contribution. Under full and Error 14 157.0 14.71 246.5 67.2 2240.0 deficit irrigations for the entire season (F and D, respectively) or during flowering only (FFL and DFL, Number of flowers and number of fruits per plant, shoot and root dry weight, fruit plant production. respectively), dry biomasses were progressively accumulated up to the end of the growing season, Degree of freedom (df) and adjusted mean square (Adj MS). Significant at p ≤ 0.05 (*), p ≤ 0.01 (**) and with greater rates, as expected, in F. Under no irrigation conditions (NI), plants accumulated dry p ≤ 0.001 (***). biomasses with low rates until the end of the growing season (low fruit contributions). Root growth was quite proportional to that of shoots in plants fully irrigated for the whole growing Indeed, the above-ground dry biomass progressively increased in all experimental situations season. Di erently, roots stopped growing when plants achieved full flowering (approximately 46 (Figure 6). Up to approximately 38 DAT, no great difference was evidenced among the irrigation DAT onward) in the other water treatments. However, rewatering during flowering in FFL and DFL treatments in the rate of biomass accumulation. After that, plants irrigated up to floral initiation (FE led to a regrowth of root apparatuses. Root growth was scarce under dry conditions (NI). and DE treatments) accumulated dry biomasses with lower rates and 53 days after transplant; when Maximum crop growth rate (CGRmax) calculated from the values of the dry plant biomass vs. plants were near the end of flowering, no further plant growth occurred. Under these experimental time (DAT) on the interpolation curve (0.95 R  0.99) ranged between 1.89 (NI) and 10.97 (FFL) g DW situations, the total dry biomass started to increase again later on due to the fruit-set contribution. 1 1 1 1 plant d . High CGRmax (10.29 g DW plant d ) also corresponded to the F treatment, while under Under full and deficit irrigations for the entire season (F and D, respectively) or during flowering 1 1 deficit irrigation (D), it was lowered to 8.58 g DW plant d . This last value was further reduced (to only (FFL and DFL, respectively), dry biomasses were progressively accumulated up to the end of 1 1 7.64 g DW plant d ). the growing season, with greater rates, as expected, in F. Under no irrigation conditions (NI), plants accumulated dry biomasses with low rates until the end of the growing season (low fruit contributions). Agronomy 2020, 10, 800 10 of 17 Agronomy 2020, 10, x FOR PEER REVIEW 10 of 18 Shoot NI Root 70 ** ** ** ** 0 ** ** ** 20 ** ** 0 0 210 * 20 * FE ** 70 ** 0 0 ** 20 ** DE 140 ** ** 0 0 ** ** FFL 0 0 20 ** DFL ** ** ** 34 38 46 60 Days after transplant −1 Figure Figure 6.6. Course Course ofof shoot shoot and and root root dry dry biomass biomass accumulations accumulation (gsplant (g plant ) during ) during the the growth growth period period in pr in ocessing process tomatoes ing tomato cv. es Hypeel cv. Hypeel F1 under F1di un er de ent r di irrigation fferent irr trigatio eatments. n treat Black ments. vertical Black bars verti repr cal esent bars the repr standar esent t d he s errtor andard . Asterisks, error. As when terisks, present, when prese indicate nt, significance indicate signific at p anc e 0.05 at p (*) ≤ 0an .05 d(*) p and  0.01 p ≤(**) 0.01 respective (**) respec to tive the to corr the esponding corresponding F treatment wi F treatment within each thin e measur ach mement easuremen date.t date. 3.6. Course of Flower and Fruit Number Root growth was quite proportional to that of shoots in plants fully irrigated for the whole growing season. Differently, roots stopped growing when plants achieved full flowering The number of flowers and that of fruits were significantly a ected by the irrigation regime (approximately 46 DAT onward) in the other water treatments. However, rewatering during (p  0.05) and, to greater extent, by the time of measurements (p  0.05). Significant e ects of I  T flowering in FFL and DFL led to a regrowth of root apparatuses. Root growth was scarce under dry were also evidenced by ANOVA (p 0.05). conditions (NI). -1 Dry weight (g plant ) Agronomy 2020, 10, x FOR PEER REVIEW 11 of 18 Maximum crop growth rate (CGRmax) calculated from the values of the dry plant biomass vs. time (DAT) on the interpolation curve (0.95 ≤ R ≤ 0.99) ranged between 1.89 (NI) and 10.97 (FFL) g −1 −1 −1 −1 DW plant d . High CGRmax (10.29 g DW plant d ) also corresponded to the F treatment, while −1 −1 under deficit irrigation (D), it was lowered to 8.58 g DW plant d . This last value was further reduced −1 −1 (to 7.64 g DW plant d ). 3.6. Course of Flower and Fruit Number The number of flowers and that of fruits were significantly affected by the irrigation regime (p ≤ Agronomy 2020, 10, 800 11 of 17 0.05) and, to greater extent, by the time of measurements (p ≤ 0.05). Significant effects of I × T were also evidenced by ANOVA (p ≤ 0.05). In particular, the number of flowers per plant progressively increased with time, up to a In particular, the number of flowers per plant progressively increased with time, up to a maximum maximum that, in NI, FE and DE, was achieved later (at 53 DAT) than the other water treatments (at that, in NI, FE and DE, was achieved later (at 53 DAT) than the other water treatments (at 46 DAT) 46 DAT) (Figure 7). (Figure 7). 160 Flowers NI Fruits ** 180 0 FE ** 180 0 DE ** FFL 180 0 DFL 34 38 46 53 60 Days after transplant Figure Figure 7. 7. Course Course of of the the number number of of flowers flowers and and fr fru uits its per per plant plant during during the the gr growth owth per period iod in in pr proces ocessing sing tomatoes tomatoescv cv. . Hypeel Hypeel F1 under F1 und di er er di ent fferent irrigation irrigatio treatments. n treatmen Black ts. vertical Black verti bars cal repr bar esent s repr the es standar ent the d err standard or. Asterisks, error. As when terispr ksesent, , when indicate present,significance indicate signific at p ance  0.05 at (*) p ≤and 0.05p (*)  a 0.01 nd p (**) ≤ 0r .01 espective (**) respec to the tive corr to the esponding correspo F nding F treatment wi treatment within each thin e measur ach m ement easurdate. ement date. The first fruits appeared approximately 46 days after transplant, when excluding plants under dry conditions (NI) that, at that time, still did not have fruits. In F, after 53 DAT, the sum of flowers and fruits kept constant, indicating no flower drop. In FFL and DFL, rewatering at flowering induced a rise in flower production at 60 DAT. No irrigation at flowering in NI, FE and DE caused a quite pronounced drop of flowers. As a result, less fruits were produced under these experimental conditions. 3.7. Course of Fruit Production According to the course of the number of flowers and fruits with time, the fruit production per plant along the crop season was maintained constantly higher in F and lower in NI after 50 DAT (I e ect significant at p 0.001) (Figure 8). Flowers + fruits (n) Agronomy 2020, 10, x FOR PEER REVIEW 12 of 18 The first fruits appeared approximately 46 days after transplant, when excluding plants under dry conditions (NI) that, at that time, still did not have fruits. In F, after 53 DAT, the sum of flowers and fruits kept constant, indicating no flower drop. In FFL and DFL, rewatering at flowering induced a rise in flower production at 60 DAT. No irrigation at flowering in NI, FE and DE caused a quite pronounced drop of flowers. As a result, less fruits were produced under these experimental conditions. 3.7. Course of Fruit Production According to the course of the number of flowers and fruits with time, the fruit production per plant along the crop season was maintained constantly higher in F and lower in NI after 50 DAT (I Agronomy 2020, 10, 800 12 of 17 effect significant at p ≤ 0.001) (Figure 8). NI FE DE FFL DFL 30 35 40 45 50 55 60 65 Days after transplant Figure 8. Course of fruit production per plant (g fresh weight-FW) during the growth period in Figure 8. Course of fruit production per plant (g fresh weight-FW) during the growth period in processing tomatoes cv. Hypeel F1 under di erent irrigation treatments. Black vertical bars represent processing tomatoes cv. Hypeel F1 under different irrigation treatments. Black vertical bars represent the standard error. the standard error. Under irrigation limited to the flowering period, plants receiving 50% ETc exhibited a fruit Under irrigation limited to the flowering period, plants receiving 50% ETc exhibited a fruit production course similar to that of plants fully irrigated (100% ETc), with a production at 60 DAT production course similar to that of plants fully irrigated (100% ETc), with a production at 60 DAT anyway lower than that of plants under a deficit irrigation for the whole season (D treatment) (I  T, anyway lower than that of plants under a deficit irrigation for the whole season (D treatment) (I × T, p 0.001). In fact, the rise in flower production occurring in response to reirrigation at flowering did p ≤ 0.001). In fact, the rise in flower production occurring in response to reirrigation at flowering did not induce an equal rise in fruit production, since probably the irrigation suspension after flowering not induce an equal rise in fruit production, since probably the irrigation suspension after flowering did not allow most of the new flowers to turn into fruits. Under no irrigation at flowering (FE and DE), did not allow most of the new flowers to turn into fruits. Under no irrigation at flowering (FE and plants produced constantly less than those of the irrigated. DE), plants produced constantly less than those of the irrigated. 3.8. Fruit Yield and Water Productivity 3.8. Fruit Yield and Water Productivity 1 1 Final fruit yields varied from 51.02 t ha (F) to 3.81 t ha (NI), with significant di erences −1 −1 Final fruit yields varied from 51.02 t ha (F) to 3.81 t ha (NI), with significant differences (p ≤ (p  0.01) among treatments (Table 4). Irrigation at a reduced rate in D determined a 16% fruit loss, 0.01) among treatments (Table 4). Irrigation at a reduced rate in D determined a 16% fruit loss, with with a final yield that slightly (p 0.05) but not significantly di ered from that of the F treatment and a final yield that slightly (p ≤ 0.05) but not significantly differed from that of the F treatment and 44% 44% water saved. In FFL and DFL, as mentioned above, the raised number of flowers per plant due to water saved. In FFL and DFL, as mentioned above, the raised number of flowers per plant due to rewatering during the flowering period was not followed by an equal increase in plant productivity. rewatering during the flowering period was not followed by an equal increase in plant productivity. Therefore, irrigation only at flowering resulted in a water consumption that was approximately 48% Therefore, irrigation only at flowering resulted in a water consumption that was approximately 48% and 69% (in FFL and DFL, respectively) lower than that of long-season full irrigation (F); however, 55% and 69% (in FFL and DFL, respectively) lower than that of long-season full irrigation (F); however, (in FFL) and 58% (in DFL) fruit yields were lost. 55% (in FFL) and 58% (in DFL) fruit yields were lost. Table 4. E ects of irrigation treatments on some yield parameters in processing tomatoes cv. Hypeel F1. Table 4. Effects of irrigation treatments on some yield parameters in processing tomatoes cv. Hypeel Values followed by the same letter do not statistically di er at p 0.05 (Tukey’s test). IWUE: irrigation F1. Values followed by the same letter do not statistically differ at p ≤ 0.05 (Tukey’s test). IWUE: water use eciency. irrigation water use efficiency. 1 3 Irrigation Treatment Yield Losses (%) Water Saving (%) Fruit Yield (t ha ) IWUE (kg m ) NI 3.81 d 92.5 88.9 8.46 e F 51.02 a - - 12.60 cd D 42.96 a 15.8 44.4 19.09 a FE 15.85 c 68.9 70.1 13.10 cd DE 12.06 cd 76.4 79.5 14.53 c FFL 23.10 b 54.7 48.4 11.05 d DFL 21.41 bc 58.0 68.6 16.86 b No significant di erence in final yield was observed between the two rates of irrigation (full and deficit), irrespective of the irrigation scheduling (irrigation cut-o before the start of flowering or irrigation at flowering only). -1 Fruit production (g plant ) Agronomy 2020, 10, 800 13 of 17 Irrigation water use eciency (IWUE) was maximized in D treatments (IWUE >19 kg m ). IWUE in FE and DE was greater than 13 kg m ; however, yields were not economically convenient (yield losses >69%). Irrigation limited to the flowering period had low eciency at a 100% rate (FFL, 3 3 IWUE 11.05 kg m ) but high at a 50% rate (DFL, IWUE >16 kg m ). 3.9. Relationships of Physiological Parameters vs. Plant Production Traits Plant water status significantly influenced the rate of dry biomass accumulation along the crop season. Positive relationships were described between the water potential, leaf transpiration and stomatal conductance at 55 DAT vs. a maximum value of CGR, i.e., that calculated between 53 and 60 DAT (r = 0.90 ** for and 0.97 *** for both E and g ) (Table 5). Table 5. Correlation coecients (r) among the physiological and productive traits in processing tomatoes cv. Hypeel F1. CGRmax: maximum crop growth rate. vs. CGRmax 0.90 ** 55DAT E vs. CGRmax 0.97 *** 55DAT g vs. CGRmax 0.97 *** s55DAT E vs. n. flowers 0.91 ** 41DAT 46DAT g vs. n. flowers 0.91 ** s41DAT 46DAT E vs. n. fruits 0.92 ** 41DAT 60DAT g vs. n. fruits 0.96 *** s41DAT 60DAT Flowers (n) vs. fruits (n) 0.97 *** 46DAT 60DAT ns Flowers (n) vs. fruits (n) 0.31 55DAT 60DAT Flowers (n) vs. yield 0.88 ** 46DAT ns Flowers (n) vs. yield 0.19 53DAT ns Flowers (n) vs. yield 0.17 60DAT E vs. fruit yield 0.88 ** 41DAT E vs. fruit yield 0.84 ** 48DAT E vs. fruit yield 0.88 ** 55DAT g vs. fruit yield 0.88 ** s41DAT g vs. fruit yield 0.85 ** s48DAT g vs. fruit yield 0.86 ** s55DAT vs. fruit yield 0.96 *** 63DAT ** and ** significant at p 0.01 (**) and p 0.001 (***); ns: not significant. The plant water status significantly a ected the reproductive process. Indeed, positive relationships (r = 0.91**) were described between leaf transpiration at 41 DAT (a few days after the restart of irrigation in FFL and DFL) and the number of flowers measured at 46 DAT, indicating that good soil water conditions during flowering positively a ect the plant water status and, thus, the reproductive activity. As a result, those plants highly transpiring produced more flowers than those less transpiring. Flowers produced at 46 DAT were also positively correlated with stomatal conductance at 41 DAT (r = 0.91**). Even closer positive relationships of leaf transpiration (r = 0.92**) and stomatal conductance (r = 0.96***) at 41 DAT were described vs. the number of fruits at 60 DAT, i.e., those deriving from flowers produced earlier (at 46 DAT). Indeed, the number of fruits produced at 60 DAT was in turn positively correlated with that of flowers measured at 46 DAT (r = 0.97***) but not with that of flowers ns produced later on (53 DAT, r = 0.31 ). This indicates that, irrespective of the experimental conditions, more or less all flowers first produced turned into fruits, but only a portion of those produced later (after 53 DAT) in response to reirrigation at flowering (as occurred in FFL and DFL treatments) produced fruits. Indeed, the final yield result positively correlated with the number of flowers produced early ns (r = 0.88**) but not with those produced late (at 53–60 DAT, r < 0.2 ). Plant water status greatly a ected the final fruit yield. Indeed, the leaf transpiration and stomatal conductance measured during flowering (up to approximately 55 DAT) well predicted the final plant productivity, being well-correlated with the final fruit yield (r > 0.84**). As well, good plant water Agronomy 2020, 10, 800 14 of 17 conditions later on, at fruit onset, as indicated by a low predawn water potential at 63 DAT, positively influenced the final fruit yield (r = 0.96***). 4. Discussion Tomatoes are reported as moderately sensitive to water stress, with sensitivity mostly depending on the cultivar and the growing stage at which soil water deficit occurs [3,4]. In this research, the physiological responses of processing tomatoes to irrigation at di erent rates and critical stages were examined in a semi-arid environment. Under full irrigation conditions over the growth season, the plants exhibited the highest rates of both leaf transpiration and stomatal conductance; this was mostly because of the high turgor capacity [21]. Conversely, under water-stressful conditions, plants tended to close the stomata (low g ) in order to limit water losses through transpiration (low E) [7]. Nevertheless, according to the observed level of ASWC, close to the wilting point all along the flowering period and later on (from 40 DAT onward), plants not irrigated from flowering (FE and DE) 2 1 still survived, as revealed by the high values of E (>4.44 mmol H O m s ) up to 55 DAT, even at the long-term 100% soil water deficit. These observations suggest that tomato plants, although sensitive to water stress, may survive to a prolonged soil water deficit. The relationships among the di erent traits were also examined for a better comprehension on how the physiological parameters are associated with plant productivity in processing tomatoes when irrigation is applied at critical stages. However, it is well-known that the soil texture greatly a ects water availability and, thus, the plant hydraulic status [22]; therefore, it is feasible to expect the same physiological response in tomato plants under soil features similar to those of the present study. According to what was observed in a cultivar of processing tomatoes cultivated under climatic conditions similar to those of the present research [16], the plant water status is not the only factor regulating stomatal aperture. Indeed, the atmospheric conditions experienced by tomato plants during the growing season strongly influenced their physiological response to irrigation, and even in well-watered plants, the vapor pressure deficit (VPD), when exceeding 1.8 kPa, limited the stomatal opening, thus reducing the plant-water flux to the atmosphere. As a result, both the stomatal conductance and leaf transpiration were strongly reduced in the F treatment, although the corresponding predawn water potential was still quite high (0.2 MPa). Similarly, Thompson et al. [23] reported that low humidity (i.e., high VPD) reduces g in tomatoes, with a di erent extent depending on the genotype. Besides seasonal trends, the same e ects of a changing VPD upon leaf transpiration, stomatal conductance and assimilation patterns were observed in well-irrigated plants of a grapevine. In particular, while no clear daily changes occurred in gas exchanges under a low atmospheric evaporative water demand (i.e., low VPD), a decrease in both E and g , as well as in the assimilation rate, occurred under a high atmospheric evaporative water demand (i.e., high VPD) [24]. Close positive relationships between the leaf transpiration and stomatal conductance measured at early flowering vs. the number of flowers produced indicated how the plant water status at flowering greatly a ected its reproductive behavior (the higher the leaf transpiration and stomatal conductance, the greater the number of flowers produced). Indeed, flowering has been reported as the most sensitive stage of tomatoes to water stress [25,26]. Torrecillas et al. [27] noticed that, di erently than what happened in wild types, plants of domesticated tomatoes promptly reacted to temporary rewatering after su ering a prolonged period of water stress through a fast stomata reopening. This did not occur in wild tomatoes, where six days after rewatering, stomata were still closed, allowing plants to retain turgor. The high E and g measured in the current research in FFL and DFL during flowering after a long-term soil water deficit may reveal a prompt reaction of tomato plants to rewatering but, at the same time, an inecient stomatal control for water losses, which involves an inadequate plant recovery once irrigation is suspended again. In fact, high levels of E and g as measured at the end of flowering or even later did not involve high yields, basically because not all flowers produced in large amounts later on in response to rewatering (as in FFL and DFL treatments) produced fruits. With this in mind, E and g measured at early or mid-flowering, more than those measured at the end of this stage or s Agronomy 2020, 10, 800 15 of 17 later on, may be considered as valuable indicators to predict crop productivity in processing tomatoes. Similar results were obtained in a germplasm of local tomatoes cultivated in a semi-arid environment of Sicily, where the greatest yields were achieved with those genotypes with the highest levels of leaf transpiration measured at 50 DAT [28]. The water potential was not measured at the floral initiation. However, when values of at 55 DAT (beyond mid-flowering) were regressed vs. E and g measured at the same time, strict relationships were observed (r = 0.93 ** in both cases); i.e., the plant water status greatly a ects its physiological behavior. Therefore, it is likely that the water potential, if measured previously (e.g., at 41 DAT, as for E and g ), would be correlated to the final yield even more strictly than the leaf transpiration and stomata conductance were. Moreover, a high VPD depresses the rates of both the leaf transpiration and stomatal conductance, therefore altering the physiological response of the crop even under unrestricted soil water conditions. Contrastingly, the predawn was less influenced by high temperatures and low air humidity, keeping low values under full irrigation, even at a high VPD. In this research, the fruit yield was maximized when irrigation was applied at the highest rate (100% ETc) for the whole season. However, the adoption of a deficit irrigation strategy where irrigation at a lower rate (50% ETc) for the whole season is applied allowed to reduce yield losses to a minimum (<16%) while saving a great amount of water (up to 44%). This result somehow provides evidence that deficit irrigation at flowering did not significantly compromise the allocation of the plant energy sources, resulting in only very limited productivity losses. Irrigation only at the vegetative stage adversely a ected the crop productivity, causing yield losses >68%. In turn, irrigation limited to the flowering period, even at a reduced rate (50% ETc), slightly alleviated the water stress induced by a very early cut-o of irrigation, leading to a final yield that, although moderate, was anyway greater than that obtained with an early suspension of irrigation at the flowering onset. This is consistent with the literature, where a greater impact of water stress during flowering than during the vegetative stage, on the fruit yield, mainly ascribable to floral abortion, has been reported on tomatoes [1,6]. However, irrigation limited to the flowering period was not as beneficial to the tomato crop as expected, especially when irrigation was applied at the highest rate (100%). Indeed, in FFL and DFL treatments, although the number of fruits measured at 60 DAT was even higher than that of the D treatment, the final yield was significantly lower. In particular, in FFL, yield losses (55%) were greater than water saving (48%) (low IWUE). Studies evidenced how, in tomatoes, the water deficit at any growth stage does not adversely a ect the number of fruits produced but significantly reduces their single weight [8,14]. According to the literature [4,5,14], the IWUE was positively a ected by the water deficit. A high water productivity (IWUE >13 kg m ) corresponded to the plot with irrigation during the vegetative stage only (FE and DE). Similarly, da Silva et al. [15] observed that the highest levels of water productivity in tomatoes occurring with a 50% irrigation replacement, and in relation to irrigation suspension, the longer the number of days without the irrigation before a harvest, the higher the water productivity. In the current study, yields in FE and DE were not economically sustainable (<16 t ha ). This fact highlights how irrigation for the whole season, even at reduced rates, is important to minimize fruit losses in processing tomatoes. Similar findings were reported for some cultivars of processing tomatoes cultivated under the same climatic conditions of Eastern Sicily [3,4,29]. 5. Conclusions The results of the present study reveal how the irrigation limited to the vegetative stage or to flowering, at a full (100% ETc) or reduced rate (50% ETc), greatly influences the physiological behavior of tomato plants cultivated under a semi-arid environment. Leaf transpiration and stomatal conductance measured at early or mid-flowering, more than that measured later on, may be adopted as valuable indicators to predict the crop productivity. However, their accuracy may be altered under particular environmental conditions (i.e., a high vapor pressure deficit (VPD)), being strongly hindered even under unrestricted soil water conditions. In this sense, the predawn water potential, being little Agronomy 2020, 10, 800 16 of 17 a ected by the VPD, is more reliable than the leaf transpiration and stomatal conductance under these climatic conditions. The results also confirm that, in tomatoes, irrigation for the whole season is important to maximize the fruit yield. However, a balance between the improved irrigation water use eciency (IWUE) and satisfactory yield can be achieved through the adoption of a deficit irrigation strategy where a moderate water stress is induced by irrigation at a 50% ETc rate. Indeed, the adoption of irrigation strategies that optimize (reaching the most sustainable value), more than maximizing (reaching the overall maximum value) the IWUE, may contribute to making the crop more profitable. The flowering stage is confirmed as sensitive to drought stress; therefore, severe soil water deficits during this stage adversely a ect crop productivity, leading to final low fruit yields. Indeed, yield losses were greater when the irrigation was suspended during flowering. Alternatively, in areas of dry summers where irrigation water is scarcely available, as that of the present experiment, irrigation could be omitted during the vegetative stage and limited (at a reduced rate, e.g., 50% ETc) to the flowering period, keeping in mind that water-saving is more or less proportional to yield losses. 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Journal

Agronomy – Multidisciplinary Digital Publishing Institute

Published: Jun 4, 2020

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