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- Multidisciplinary Digital Publishing Institute
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- © 1996-2019 MDPI (Basel, Switzerland) unless otherwise stated
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- 10.3390/agronomy9040206
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Abstract
agronomy Article Seasonal Variation in Diurnal Photosynthesis and Chlorophyll Fluorescence of Four Genotypes of Cassava (Manihot esculenta Crantz) under Irrigation Conditions in a Tropical Savanna Climate 1 2 3 3 Supranee Santanoo , Kochaphan Vongcharoen , Poramate Banterng , Nimitr Vorasoot , 3 4 1 , 2 , Sanun Jogloy , Sittiruk Roytrakul and Piyada Theerakulpisut * Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand; supranee4705@hotmail.com Salt-Tolerant Rice Research Group, Department of Biology Faculty of Science Khon Kaen University, Khon Kaen 40002, Thailand; kocha_9@hotmail.com Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand; pboram@kku.ac.th (P.B.); nvorasoot1@gmail.com (N.V.); sjogloy@gmail.com (S.J.) The National Center for Genetic Engineering and Biotechnology (BIOTEC), Phahonyothin Road Khlong Nueng, Khlong Luang Pathum Thani 12120, Thailand; sittiruk@biotec.or.th * Correspondence: piythe@kku.ac.th; Tel.: +66-43-202-531; Fax: +66-43-202-530 Received: 22 February 2019; Accepted: 18 April 2019; Published: 23 April 2019 Abstract: Photosynthesis performance during early vegetative growth is an important physiological trait determining yield of cassava, but limited information is currently available for the tropical savanna climate of Asia. Diurnal photosynthesis and chlorophyll fluorescence of the three-month-old plants of four commercial cassava genotypes (Rayong 9, RY9; Rayong 11, RY11; Kasetsart 50, KU50 and CMR38-125-77) grown under irrigation, were investigated in three seasons i.e., rainy, cool and hot. The mean daily net photosynthetic rate (Pn) across genotypes in the rainy season (11.75 molCO /m /s) was significantly lower than that in the cool season (14.60 molCO /m /s). Daily mean Pn in the hot season was 14.32 molCO /m /s. In the rainy season, maximum photochemical quantum yield of PSII (F /F ) and e ective quantum yield of PSII photochemistry (F ) were significantly higher v m PSII than the other seasons, while electron transfer rate (ETR) and non-photochemical quenching (NPQ) were significantly lower. Genotypic variation was observed during the hot season in which RY11 had the highest and CMR38-125-77 the lowest mean daily Pn. The prominent mechanism to avoid damages from stress during afternoon in the hot season was to reduce leaf temperature by enhancing transpiration for RY11; to close stomata early for RY9, and to increase NPQ for CMR38-125-77. Keywords: cassava genotypes; photosynthetic performance; photosystem II eciency; climatic factors 1. Introduction Cassava (Manihot esculenta Crantz) is one of the most significant crops for food security and the main food source for more than 0.8 billion people in Africa and Asia [1,2]. Cassava is also used to produce starch for industrial applications including paper, textile, food and beverages, plywood, glue, animal feed and ethanol [3]. Thailand is ranked as the world’s largest exporter of cassava products, supplying around 67% of the global market with annual production of 31 million tons in 2016 [4]. The country exports cassava products in the form of dry chips, pellets, and native and modified starch [5]. Most of the cassava growing areas in Thailand are in the tropical savanna climate zone with a growing period, from planting to storage root harvesting, of eight to 12 months, which covers almost Agronomy 2019, 9, 206; doi:10.3390/agronomy9040206 www.mdpi.com/journal/agronomy Agronomy 2019, 9, 206 2 of 27 all three seasons in Thailand (hot season, March to May; rainy season, June to October, and cool season, November to February) [6]. Storage root yield of cassava varies considerably depending on cultivars, climate, growing conditions, crop management and planting time [7,8]. While the highest recorded experimental yield potential was 80 to 90 t ha under near optimal edaphic–climatic conditions [9,10], the average yield in Thailand was recorded at 18.83–24.15 t ha [11]. This yield gap might be due to a lack of sucient agro-advisory information about cassava genotypes suitable for planting in di erent seasons and appropriate management practices for the di erent growing seasons [12]. Crop yield is primarily determined by photosynthesis [13,14] and net photosynthetic rate (Pn) of cassava leaves was reported to have a significant correlation with storage root yield across environments [15]. Related photosynthesis parameters such as internal CO concentration (Ci) was also significantly correlated with dry root yield of cassava [16]. In addition, changes in chlorophyll (Chl) fluorescence parameters under di erent environmental conditions can be used as a rapid and sensitive measure of plant health status, photosynthetic competence as well as e ects of stress on plants [17,18]. Information on environmental e ects in di erent seasons on photosynthetic performance of cassava genotypes is seriously lacking for the tropical savanna climate including Thailand. If seasonal variations in environmental conditions and responsive physiological parameters are precisely measured under specific field condition, it would help determine plant-based and/or environmental factors limiting photosynthetic performance as well as providing essential input data for e ective crop growth and photosynthesis modeling [19]. This information will be useful for providing a set of guidelines in improving management of cultural practice of cassava growing in di erent seasons. The e ect of weather variations during di erent periods of growing seasons in Thailand on growth rate and final yield of cassava has been reported [12]. However, the physiological responses, particularly photosynthesis, of cassava genotypes in di erent growing seasons have not been evaluated in Thailand. Therefore, the objectives of this study were to investigate the e ect of weather fluctuation in di erent seasons on diurnal photosynthesis and Chl fluorescence of the three-month-old plants of four commercially important cassava genotypes grown under irrigation to determine appropriate genotypes for planting in di erent seasons based on their growth and photosynthetic performance. 2. Materials and Methods 2.1. Site Description The study site was at the experimental research station, Faculty of Agriculture, Khon Kaen 0 00 0 00 University, Northeast Thailand (16 28 29.7 N, 102 48 37.3 E, altitude 195 m above sea level). Soils were of the Yasothon soil series; fine loamy, siliceous, and Oxic Paleustult [20]. The climate is equatorial savanna with a dry winter [21]. The seasonal mean air temperatures for the Northeastern part of Thailand for 30 years (1981–2010) were 27.6, 24.2 and 28.6 C, with the mean minimum of 24.4, 18.7 and 23.2 C, and mean maximum of 32.6, 30.6 and 35.2 C in rainy, cool and hot seasons, respectively. The average seasonal rainfalls, during 1981–2010, were 1103 mm, 76 mm, and 224 mm in rainy, cool and hot seasons, respectively [22]. The experimental study was conducted during June 2015 to April 2016. Environmental characteristics including ambient PAR (PAR ), air temperature (T ), air relative humidity (RH ) A air air and rainfall were recorded every five minutes by an automatic weather station (Watchdog 2000, Spectrum Technologies Inc., Lincoln, NE, USA). Air vapor pressure deficit (VPD ) was calculated air from air temperature, saturated vapor pressure and RH with the aid of Smithsonian Meteorological Tables prepared by Robert J. List, Smithsonian Institution Press, City of Washington [23] (Figure 1). The weather was under the influence of monsoon winds, specifically the southwest and northeast monsoon. In 2015–2016, the three seasons were divided as follows; rainy season or southwest monsoon season from June to October, cool season or northeast monsoon from November to February, and hot or Agronomy 2019, 9, x FOR PEER REVIEW 3 of 29 Agronomy 2019, 9, 206 3 of 27 92 monsoon. In 2015–2016, the three seasons were divided as follows; rainy season or southwest 93 monsoon season from June to October, cool season or northeast monsoon from November to 94 February, and hot or pre-monsoon from March to May. The monthly mean environmental pre-monsoon from March to May. The monthly mean environmental parameters in the experimental 95 parameters in the experimental field are shown in Figure 1. field are shown in Figure 1. Figure 1. Monthly mean environmental parameters at the experimental site from May, 2015 to May, 97 Figure 1. Monthly mean environmental parameters at the experimental site from May, 2015 to May, 2016. Daytime ambient photosynthetically active radiation (PAR ) and daytime air temperature (T ) A air 98 2016. Daytime ambient photosynthetically active radiation (PARA) and daytime air temperature (Tair) (A), relative humidity (RH ) and total rainfall (B), air vapor pressure deficit (VPD ) and number of air air 99 (A), relative humidity (RHair) and total rainfall (B), air vapor pressure deficit (VPDair) and number of rainy days (C). Rainy season ranged from June to October, cool season from November to February, 100 rainy days (C). Rainy season ranged from June to October, cool season from November to February, and hot from March to May. Dotted vertical lines indicate the timing of photosynthetic measurements 101 and hot from March to May. Dotted vertical lines indicate the timing of photosynthetic measurements made on three-month-old cassava plants in each season. Rainy season measurements were made in 102 made on three-month-old cassava plants in each season. Rainy season measurements were made in October 2015 on plants established on 30 June 2015 (PD-Jun); cool season measurements were made in 103 October 2015 on plants established on 30 June 2015 (PD-Jun); cool season measurements were made February 2016 on plants established on 10 November 2015 (PD-Nov); and hot season measurements 104 in February 2016 on plants established on 10 November 2015 (PD-Nov); and hot season measurements were made in April 2016 on plants established on 15 December 2015 (PD-Dec). 105 were made in April 2016 on plants established on 15 December 2015 (PD-Dec). Agronomy 2019, 9, 206 4 of 27 2.2. Plant Materials Four cassava genotypes were selected for physiological studies, all were improved cultivars or line with high starch content suitable for industrial uses. Two plant types are recognized i.e., one non-branching plant type (cv. Rayong 9, RY9), and one branching plant type (2 cvs. Rayong 11, RY11; and Kasetsart 50, KU50, and one line CMR-38-125-77). The four cassava genotypes were planted at three di erent planting dates (PD), namely, PD-Jun, PD-Nov and PD-Dec. PD-Jun plants were planted on 30 June 2015, PD-Nov on 10 November 2015 and PD-Dec on 15 December 2015. Stem cuttings (20 cm long) were planted with a plant spacing of 1 m 1 m in the plot size of 5 m wide and 7 m long. All cassava plants were fertilized and kept well-watered (soil matric potential was maintained between 0 to 30 kPa) throughout the growing and measurement period. Nitrogen fertilizer ((NH) SO ) 2 4 formula 21-0-0 was applied at one month after planting at the rate of 46.9 kg ha based on soil analysis and nutrient requirements for cassava [23,24]. At two months after planting the compound fertilizer N–P O –K O formula 15-0-18 was applied at a rate of 312.5 kg ha (Chia tai company 2 5 2 limited, Phranakhonsiayutthaya, Krung Thep Maha Nakhon, Thailand). The plants were irrigated by a mini-overhead sprinkler irrigation system. Soil matric potential was continuously monitored by Tensiometer and water mark (Watchdog 1000, Spectrum Technologies Inc., Lincoln, NE, USA) at the soil depths of 20 and 40 cm. Water applications were administered whenever soil matric potential reduced to 30 kPa at 20 cm depth. Rainy season measurements of growth and photosynthesis were performed on PD-Jun plants when they were three months old (in October 2015). Cool and hot season measurements were performed on three-month-old PD-Nov and PD-Dec plants in February and April 2016, respectively. Plant growth rate was measured, on the planting date and after three months of planting, as the 1 1 rate of increase in stem height (cm d ), and rate of leaf production (leaf d ), on six randomly selected plants per genotype. Leaf area index (LAI) of the three-month-old plants was measured by gap fraction analysis using LI-191R line quantum sensor (Li-Cor Inc., Lincoln, NE, USA). Canopy structure was calculated according to the equation LAI = (1/k)ln(Q /Q ) where k is assumed to be close to 0.5, Q is b a b an average below-canopy PAR and Q is an unobstructed PAR reading [25]. 2.3. Physiological Measurement Photosynthetic measurements were made on three-month-old plants on two days in each season. The three-month-old plants were selected for photosynthetic measurements because the most active vegetative growth occurs during the period three to six months after planting, and storage roots begin to be formed at this stage [26]. Rainy season measurements were made on 25 September and 2 October 2015 on plants established on 30 June 2015 (PD-Jun). Cool season measurements were made on 24 and 26 February 2016 on plants established on 10 November 2015 (PD-Nov). Hot season measurements were made on 3 and 5 April 2016 on plants established on 15 December 2015. On each day, diurnal variation in gas exchange and chlorophyll fluorescence were measured at 2 h intervals (eight time points) from 04:30 to 18:30 local time. For each time point, the measurements were performed on the central lobe of a young fully expanded leaf of two randomly selected plants of each genotype. Gas exchange parameters were evaluated using a portable gas exchange system, infrared gas analyzer (LI-6400xt, Li-Cor Inc., Lincoln, NE, USA) equipped with the standard 2 3 cm leaf chamber (6400-08 clear chamber bottom). Pn, Gs, Tr and C were measured under ambient environmental conditions. The instantaneous light use eciency (LUE) was calculated from Pn/absorbed photosynthetically active radiation. Water-use eciency (WUE) was calculated as the ratio of Pn/Tr. Ratio between internal CO concentration and ambient CO (Ci/Ca) was calculated 2 2 to indicate non-stomatal limitation of photosynthesis. Chl fluorescence subtly reflects the primary reactions of photosynthesis and is closely associated with photosystem II (PSII) photochemical eciency. Chl fluorescence parameters were measured using Mini PAM-II Photosynthesis Yield Analyzer (Heinz Walz GmbH, E eltrich, Germany). Minimal fluorescence yield of the dark-adapted state (F ) was measured in complete darkness 0 Agronomy 2019, 9, 206 5 of 27 before sunrise (04:30). Maximal fluorescence of the dark-adapted state (F ) was obtained following a saturating pulse of 4000 mol/m /s lasting 0.8 s. Maximal quantum yield of PSII photochemistry (F /F ) was calculated according to the equation F /F = (F F )/F . Steady state fluorescence v m v m m 0 m in the light-adapted state (F’) and the maximal fluorescence of the light-adapted state (F ) were measured during the day between 06:30–16:30 (every two hours, 6 time points). E ective quantum 0 0 0 yield of PSII photochemistry (F ) was calculated from the equation: F = (F F )/F and m m PSII PSII 0 0 nonphotochemical quenching (NPQ) from: NPQ = (F F )/F . Electron transport rate (ETR) was m m m calculated from the equation: ETR = F 0.84 0.5 PAR [27,28]. PSII 2.4. Data and Statistical Analysis Comparisons among planting dates of mean ambient photosynthetically active radiation (PAR ), air temperature (T ), air relative humidity (RH ) and air vapor pressure deficit (VPD ) were done air air air by using paired t-test. Mean comparisons of growth, environmental, photosynthesis and chlorophyll fluorescence parameters were using one-way ANOVA for comparing means among genotypes within season and among seasons within each genotype, averages of multiple comparisons were determined by a Tukey’s test under Sigmaplot version 11.0 software [29]. The correlation analysis between photosynthesis (Pn, Gs, Tr, F , ETR and NPQ) and environmental parameters including PAR , PSII A T , leaf-to-air vapor pressure deficit (VPD ) and relative humidity in the plant canopy (RH ) were leaf L C analyzed in di erent seasons. Statistical significance was taken at p < 0.05 and p < 0.01 using MSTAT-C Version 1.42 software [30]. All statistical analyses followed the procedure described by Gomez and Gomez [31]. 3. Results 3.1. Environment and Plant Growth The environmental conditions under which the cassava plants of the three planting dates (PD-Jun, PD-Nov and PD-Dec) were growing were recorded from the date of planting until the plants were three-month-old as shown in Table S1 (see Supplementary). The values of mean daily PAR for the three planting dates were similar ranging from 412–429 mol/m /s. Among the three planting dates, the PD-Jun plants experienced the highest daily minimum (23 C) and highest daily mean temperature (28 C). On the other hand, the PD-Nov and PD-Dec plants were exposed to the lowest daily minimum temperature of 19 C. The mean daily temperatures during growth of PD-Nov and PD-Dec plants were 25 and 26 C, respectively. The highest mean daily RH was found for PD-Jun (77%) while those recorded for PD-Nov and PD-Dec were at 57% and 52%, respectively. The lowest daily minimum RH (27–31%) was recorded in the cool season for the PD-Nov and PD-Dec plants. The PD-Jun plants which were growing in the rainy season were exposed to the lowest daily maximum (2.55 kPa) and daily mean (1.02 kPa) VPD . The daily maximum VPD values increased for PD-Nov (3.58 kPa) and air air PD-Dec (4.03 kPa) plants which were growing during the cool and cool-to-hot seasons, respectively. The highest total rainfall was recorded for PD-Jun (614.3 mm) and the lowest (25.6 mm) for PD-Nov plants. In this experiment, irrigation was applied by a mini-overhead sprinkler system to maintain soil matric potential level at approximately 30 kPa or higher. The highest and lowest total irrigation were applied to PD-Dec (41.6 mm) and PD-Jun (7.2 mm) plants, respectively. Cassava plant growth rates during the first three months after planting were measured as the 1 1 rate of increase in plant height (cm d ) and the rate of leaf production (leaf d ) as shown in Figure 2 and Table S2. The rate of increase in plant height of plants established in June (PD-Jun plants) which were growing in the rainy season, averaged across four genotypes (1.28 cm d ), was significantly 1 1 higher (p < 0.001) than the rates for PD-Nov (0.75 cm d ) and PD-Dec (0.72 cm d ) plants which were planted and growing in the cool and cool-to-hot season, respectively (Figure 2A; Table S2). Rates of leaf production across four genotypes for all three planting dates were not significantly di erent. 1 1 For PD-Jun plants, leaf production rates for CMR38-125-77 (0.85 leaf d ), RY11 (0.79 leaf d ) and Agronomy 2019, 9, 206 6 of 27 Agronomy 2019, 9, x FOR PEER REVIEW 6 of 29 1 1 RY9 (0.77 leaf d ) were not significantly di erent while that of KU50 (0.53 leaf d ) was significantly lower than the others (p < 0.001). For plants established in December (PD-Dec), CMR38-125-77 showed 207 significantly higher leaf production rate (p = 0.004) than the other genotypes (Table S2). It was noted significantly higher leaf production rate (p = 0.004) than the other genotypes (Table S2). It was noted 208 that KU50 plants established in June and November had significantly lower (p = 0.010) leaf production that KU50 plants established in June and November had significantly lower (p = 0.010) leaf production 209 rate than those in December (Table S2). Mean leaf area index (LAI) of the three-month-old plants rate than those in December (Table S2). Mean leaf area index (LAI) of the three-month-old plants across 210 across genotypes for PD-Jun plants (3.32) was significantly higher than (p < 0.001) those planted in genotypes for PD-Jun plants (3.32) was significantly higher than (p < 0.001) those planted in the cool 211 the cool season (2.32 and 2.61 for PD-Nov and PD-Dec, respectively) (Figure 2C; Table S2). However, season (2.32 and 2.61 for PD-Nov and PD-Dec, respectively) (Figure 2C; Table S2). However, significant 212 significant difference (p < 0.001) among cultivars was observed only in PD-Dec in which CMR38-125- di erence (p < 0.001) among cultivars was observed only in PD-Dec in which CMR38-125-77 had the 213 77 had the highest mean LAI of 3.49 followed by RY11 (2.51), RY9 (2.45) and KU50 (2.00). highest mean LAI of 3.49 followed by RY11 (2.51), RY9 (2.45) and KU50 (2.00). Figure 2. Rate of increase in plant height (A), rate of leaf production (B) and leaf area index (LAI) of 215 Figure 2. Rate of increase in plant height (A), rate of leaf production (B) and leaf area index (LAI) of three-month-old plants (C) of cassava genotypes RY9, RY11, KU50 and CMR38-125-77 planted in June 216 three-month-old plants (C) of cassava genotypes RY9, RY11, KU50 and CMR38-125-77 planted in June 2015 (PD-Jun), November 2015 (PD-Nov) and December 2015 (PD-Dec). Means which are significantly 217 2015 (PD-Jun), November 2015 (PD-Nov) and December 2015 (PD-Dec). Means which are di erent (p < 0.05) among genotypes for each planting date are denoted by di erent lower-case letters. 218 significantly different (p < 0.05) among genotypes for each planting date are denoted by different For each genotype means which are significantly di erent among planting dates are denoted with 219 lower-case letters. For each genotype means which are significantly different among planting dates capital letters. Data shows mean of six replicates standard deviation (SD). 220 are denoted with capital letters. Data shows mean of six replicates ± standard deviation (SD). 3.2. Diurnal Variation in Environmental Conditions during Field Measurements of Photosynthesis 221 3.2. Diurnal Variation in Environmental Conditions during Field Measurements of Photosynthesis Diurnal patterns of environments (PAR , T , RH and VPD ) measured during 04:30–18:30 A air air air 222 on two Disunny urnal pa days tterns of of photo envi synthesis ronments ( measur PARA, T ements air, RHin air and VPD each of the air) m thr ea ee sured during 04 seasons, compar :30–18 ed :30 with on 223 leaf two sunny days of photosynthesis /canopy parameters (PAR , T , me RH asurements and VPD )in each were depicted of the three in Figurseaso e 3. For ns, comp each seare ason, d with the leaf leaf C L 224 diurnal leaf/canopy minima, parmaxima ametersand (PAR means leaf, Tleaf recor , RH ded C and during VPD 06:30 L) wer toe16:30 depict acr ed oss in F two igdays ure 3. For of investigation each season, the were 225 summarized diurnal minima in Table , maxim 1. Diurnal a and mea variation ns recorded duri in ambientng 06 PAR (P :30 AR to 16 ) comp :30 acro ared ss t to wincident o days of P inves AR (Pt AR igation ) A leaf 226 were summarized in Table 1. Diurnal variation in ambient PAR (PARA) compared to incident PAR 227 (PARleaf) were displayed in Figures 3A–B, C–D and E–F for measurements performed in rainy, cool 228 and hot seasons, respectively. Similarly, the comparison between diurnal Tair and Tleaf were shown in 229 Figures 3G–L. Diurnal RHair compared to RHC, and VPDair compared to VPDL were demonstrated in Agronomy 2019, 9, 206 7 of 27 were displayed in Figure 3A–F for measurements performed in rainy, cool and hot seasons, respectively. Similarly, the comparison between diurnal T and T were shown in Figure 3G–L. Diurnal RH air leaf air compared to RH , and VPD compared to VPD were demonstrated in Figure 3M–R,S–X, respectively. C air L The daily minima, maxima and means of the environmental and leaf/canopy parameters recorded over the two days of photosynthesis measurements were shown in Table 1. The PAR which were leaf recorded on the top canopy leaves during gas exchange measurement were similar to PAR over the canopy throughout the day except for the period during 12:00–15:00 when PAR tended to be leaf lower than PAR (Figure 3A–F). There were seasonal di erences (p < 0.001) in the mean daily PAR A leaf across genotypes, with the highest mean PAR in the hot season (930 mol/m /s) followed by the leaf 2 2 cool (863 mol/m /s) and the rainy (518 mol/m /s) seasons (Table 1). In the rainy season, T of all genotypes were higher than T on the first day (Figure 3G) probably leaf air due to high PAR (Figure 3A). However, on the second day (Figure 3H) T tended to be than T A air leaf from 11.30 onwards. On the two days of observation in the cool season, T tended to be warmer than leaf T throughout the day (Figure 3I–J). In the hot season, T tended to be warmer than T in the late air air leaf afternoon from 14.30 to 18.30 (Figure 3K–L). The highest T was noted in the hot season reaching the leaf maximum temperatures of 41.00–44.30 C during 10:30–12:30 (Table 1). It is worth noting that both T air and T were significantly higher (p < 0.001) in the hot season compared to the others. The mean daily leaf T across genotypes (34.48 C) in the hot was significantly higher (p < 0.001) than those in the rainy leaf (31.51 C) and cool (27.70 C) seasons (Table 1). Nevertheless, in any season, no significant di erences in T were found among genotypes. As shown in Table 1, the highest mean relative humidity in leaf the canopy (RH ) across genotypes and air relative humidity (RH ) were recorded in rainy season C air with the mean daily values of 61 and 77% which di ered significantly (p < 0.05). Similarly, in the cool season, RH (29%) was also significantly lower (p < 0.05) than RH (42%). On the contrary, in C air the hot season, mean daily RH (39%) was higher than RH (37%), although the di erence was not C air significant. As shown in Figure 3S–X, VPD and VPD were low (less than 2 kPa) in the morning, L air increased several fold during early afternoon (particularly in the cool and hot seasons), and declined slowly in the late afternoon. As shown in Table 1, the mean daily VPD in the hot season (3.97 kPa) air was significantly higher (p < 0.05) than the other seasons, and was approximately 4.0 and 1.8 fold higher than those in the rainy (0.99 kPa) and cool (2.19 kPa) seasons. The mean daily VPD across genotypes in the cool (2.45 kPa) and hot (2.77 kPa) seasons were significantly higher than (p < 0.001) and approximately double that in the rainy season (1.07 kPa). It is worth noted that the mean daily VPD was similar to VPD in the rainy and cool seasons, but in the hot season VPD was significantly L air L lower (p < 0.05) than VPD . air Agronomy 2019, 9, 206 8 of 27 336 336 337 337 Figure 3.Figure 5. Diurnal Figure 5. variation Diurnal pattern of Diurnal pattern of in physical ne ne parameters t photosynthetic rate t photosynthetic rate including (Pn) P (Pn) AR (A–F (A–F (A ), stomata ), stomata –F), T con ( con G– ductance (Gs) L ductance (Gs) ), RH (M–R () G–L (and G–L ) and transpiration rate VPD ) and transpiration rate (S–X) of cassava (T (T belonging r) ( r) ( M–R M–R ) of ) of to four fou four r cassava cultivars cassava genotypes ( genotypes ( (X, RY9; xx , RY9; , RY9; RY11; RY11; leaf leaf C L 240 Figure 3. Diurnal variation in physical parameters including PARleaf (A–F), Tleaf (G–L), RHC (M -R) and VPDL (S–X) of cassava belonging to four cultivars (x, RY9; , RY11; 337 Figure 5. Diurnal pattern of net photosynthetic rate (Pn) (A–F), stomata conductance (Gs) (G–L) and transpiration rate (Tr) (M–R) of four cassava genotypes (x, RY9; 338 RY11; 338 , RY11; , KU50 and , CMR38-125-77) , , CMR38-125-77) measured from CMR38-125-77) measured from in comparison with ambient 4:30 to 18:30 at 4:30 to 18:30 at conditions (P2-h intervals on two AR 2-h intervals on two , T , RH and VPD sunny days in rainy ( sunny days in rainy ( ) in rainy (A,B,G,A H A ,,B M ,B ,G ,,G N ,H ,,H S ,M ,,T M ), ,N ,cool N ,S ,S and (and C,D T,T ), cool I,), cool J,O,P ( ,U ( CC ,,V D ,D ), ,I,,I J,,J O ,O ,P ,P ,U ,U and and V V ), ), A air air air 241 , KU50 and , CMR38-125-77) in comparison with ambient conditions (PARA, Tair, RHair and VPDair) in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), and hot 338 339 and hot season and hot and hot (E(,E F (E ,,K F ,F ,,K L ,K ,,L Q ,L ,Q ,R ,Q ,,R W ,R ,W ,,X W ). and and The XX )measur sea ) sea son. Data son. Data ement shows was shows performed mean of two replicates mean of two replicates on two sunny ± ± days SD. SD.in each season. Leaf parameters were obtained from leaf gas exchange , CMR38-125-77) measured from 4:30 to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), 242 season (E,F,K,L,Q,R,W and X). The measurement was performed on two sunny days in each season. Leaf parameters were obtained from leaf gas exchange measurements 339 measurements while the environmental parameters were from the weather station. Data shows mean of two replicates SD. and hot (E,F,K,L,Q,R,W and X) season. Data shows mean of two replicates ± SD. 243 while the environmental parameters were from the weather station. Data shows mean of two replicates ± SD. Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy Agronomy 2019 2019 , 9 , , x; 9, x; doi: FOR doi: FOR PE PE ER ER REVI REVI EW EW www. www. mdpi. mdpi. com/ com/ jou jou rnal/agronomy rnal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, 206 9 of 27 Table 1. Seasonal variation in environmental and leaf/canopy parameters during the time of photosynthesis measurements i.e., two days in rainy season (25 Nov and 2 Oct 2015), cool season (24 and 26 Feb 2016) and hot season (3 and 5 Apr 2016). Photosynthetically active radiation (PAR ) and PAR , ambient PAR and over the A leaf leaf surface; T and T , ambient air temperature and leaf temperature; RH and RH , ambient air relative humidity (RH) and RH in the plant canopy; VPD and air leaf air C air VPD , ambient vapor pressure deficit and VPD of the leaf. Daily minima (min), maxima (max) and means for each genotype were from 24 measurements (six time points during 6:30–16:30 h x two leaves x two days). Means which are significantly di erent among seasons are denoted with capital letters. Mean of leaf parameter across genotypes which is significantly di erent from that of the environment is denoted with *. Rainy Cool Hot F-Test Critical P Genotype Parameter 2 2 min max mean min max mean min max mean Value Value 35 2498 704 26 1794 950 116 2038 1105 2.184 0.12 PAR (mol/m /s) PAR (mol/m /s) RY9 27 2115 678 28 1528 909 75 1812 974 1.426 0.247 leaf RY11 12 2002 497 B 6 1517 877 AB 108 1868 956 A 3.822 0.027 KU50 17 2114 423 B 12 1521 800 AB 41 1817 875 A 4.34 0.017 CMR38-125-77 25 1964 473 B 44 1516 875 AB 61 1777 913 A 4.339 0.017 F-test value 0.947 0.148 0.11 Critical-P value 0.421 0.931 0.954 mean 20 2049 518 B 23 1521 863 A 71 1819 930 A 13.385 <0.001 T ( C) 25.10 33.00 28.68 B 16.00 32.80 26.44 B 24.40 40.30 35.04 A 22.687 <0.001 air T ( C) RY9 26.45 37.78 31.26 B 14.85 33.61 28.05 B 25.34 42.52 35.00 A 12.796 <0.001 leaf RY11 25.60 36.06 29.81 C 15.71 33.02 26.57 B 26.14 41.12 35.55 A 19.516 <0.001 KU50 25.80 37.15 30.68 AB 16.02 32.94 27.48 B 23.24 41.00 33.45 A 9.703 <0.001 CMR38-125-77 26.21 37.09 31 B 16.66 33.99 28.69 B 24.26 44.30 34.90 A 10.311 <0.001 0.92 0.729 0.417 F-test value Critical-P value 0.434 0.538 0.741 mean 26.02 37.02 31.51 * B 15.81 33.39 27.70 C 24.75 42.24 34.48 A 41.177 <0.001 RH (%) 59 100 77 A 27 68 42 B 19 82 37 B 45.802 <0.001 air RH (%) RY9 45 76 59 A 1 66 23 C 19 75 38 B 23.805 <0.001 RY11 44 86 64 A 1 88 32 B 19 73 37 B 16.350 <0.001 KU50 45 82 62 A 1 90 30 B 19 84 41 B 13.872 <0.001 CMR38-125-77 45 78 60 A 3 90 30 B 19 78 40 B 14.917 <0.001 F-test value 0.975 0.49 0.201 Critical-P value 0.408 0.69 0.895 mean 45 81 61 * A 2 84 29 * C 19 78 39 B 67.503 <0.001 Agronomy 2019, 9, 206 10 of 27 Table 1. Cont. Rainy Cool Hot F-Test Critical P Parameter Genotype 2 2 min max mean min max mean min max mean Value Value VPD (kPa) 0.01 2.07 0.99 C 0.59 3.37 2.19 B 0.55 6.2 3.97 A 33.359 <0.001 air VPD (kPa) RY9 0.28 2.14 1.17 B 0.3 4.04 2.47 A 0.41 5.61 2.94 A 12.421 <0.001 RY11 0.23 1.76 0.94 B 0.2 4.08 2.12 A 0.49 4.53 2.51 A 14.424 <0.001 KU50 0.26 2.08 1.08 B 0.3 4.65 2.46 A 0.16 5.15 2.47 A 11.041 <0.001 CMR38-125-77 0.28 2.09 1.10 B 0.6 4.15 2.76 A 0.24 7.33 3.15 A 14.401 <0.001 F-test value 1.061 1.000 0.99 Critical-P value 0.37 0.397 0.401 mean 0.26 2.02 1.07 B 0.35 4.23 2.45 A 0.33 5.66 2.77 * A 51.156 <0.001 1 2 F and P value for testing each trait among genotypes within season (the same column). F and P value for testing each trait among seasons of each genotype (the same row). Agronomy 2019, 9, 206 11 of 27 3.3. Diurnal Chl Fluorescence of Cassava Leaves Diurnal patterns of Chl fluorescence parameters (F , ETR and NPQ) of four cassava genotypes PSII measured during 04:30–18:30 on two sunny days in each of the three seasons were depicted in Figure 4. For each season, the diurnal minima, maxima and means of F , ETR and NPQ recorded during PSII 06:30 to 16:30 across two days of investigation were summarized in Table 2. The values for F /F were v m obtained from the measurements in the dark at 04:30. The F /F values were high for all genotypes and in all seasons, although some significant v m di erences were detected. The F /F means among genotypes were significantly di erent (p < 0.001) v m only in the rainy season (Table 2) with RY9 showing the highest F /F (0.866) which was significantly v m higher (p < 0.001) than RY11 (0.845) but not di erent from that of KU50 (0.847) and CMR38-125-77 (0.858). Seasonal variation in F /F was observed i.e., the means across genotypes in rainy (0.854) and v m hot (0.849) seasons were significantly higher (p < 0.001) than that in the cool (0.838) season (Table 2). Diurnal patterns of F displayed the inverted bell-shaped curves, and in the cool and hot PSII seasons, F values during 6:30 to 12:30 tended to decrease more rapidly than those in the rainy PSII season (Figure 4A–F). The di erences in F means across genotypes were noted among seasons PSII being significantly (p < 0.001) higher (0.70) in the rainy than the hot (0.58) and cool (0.56) seasons (Table 2). However, no significance di erences were found among genotypes in any season. Changes in ETR over the course of the day (Figure 4G–L) were related to the intensity of sunlight (Figure 3A–F). As shown in Table 2, daily means for ETR across genotypes in the hot (159 mol(e )/m /s) and cool 2 2 (157 mol(e )/m /s) were significantly higher (p < 0.001) than that in the rainy (90 mol(e )/m /s) season. However, no significance di erences in mean ETR were found among genotypes in any season. Diurnal patterns of NPQ were similar to those of ETR (Figure 4M–R). Cassava genotypes exhibited highest mean NPQ across genotypes (0.45) in the hot season which was significantly di erent (p < 0.001) from that in the rainy season (0.34), and expressed an intermediate value (0.41) in the cool season (Table 2). In any season, mean NPQ among genotypes did not di er significantly. However, it was noted that NPQ of CMR-38-125-77 tended to be higher than those of the other genotypes during 10:30 to 14:30 in the hot season (Figure 4Q,R). Agronomy 2019, 9, 206 12 of 27 336 336 337 337 Figure 5. Figure 5. Diurnal pattern of Diurnal pattern of ne ne t photosynthetic rate t photosynthetic rate (Pn) (Pn) ( ( A–F A–F ), stomata ), stomata con con ductance (Gs) ductance (Gs) ( ( G–L G–L ) and transpiration rate ) and transpiration rate (T (T r) ( r) ( M–R M–R ) of ) of four four cassava cassava genotypes ( genotypes (x x , RY9; , RY9; RY11; RY11; 337 Figure 5. Diurnal pattern of net photosynthetic rate (Pn) (A–F), stomata conductance (Gs) (G–L) and transpiration rate (Tr) (M–R) of four cassava genotypes (x, RY9; RY11; 338 338 Figure 4. Diurnal pattern of Chl fluorescence parameters of four cassava genotypes (X, RY9; , RY11; , KU50 and , CMR3 , , 8-125-77). CMR38-125-77) measured from CMR38-125-77) measured from E ective quantum yield 4:30 to 18:30 at 4:30 to 18:30 at of 2-h intervals on two 2-h intervals on two sunny days in rainy ( sunny days in rainy ( A A ,B ,B ,G ,G ,H ,H ,M ,M ,N ,N ,S ,S and and T T ), cool ), cool ( ( C C ,D ,D ,I ,I ,J ,J ,O ,O ,P ,P ,U ,U and and V V ), ), 315 Figure 4. Diurnal pattern of Chl fluorescence parameters of four cassava genotypes (x, RY9; , RY11; , KU50 and , CMR38-125-77). Effective quantum yield of PSII PSII photochemistry (F ) (A–F), electron transport rate (ETR) (G–L) and non-photochemical 339 339 quenching (NPQ) (M–R). The measurements were performed from 4:30 338 , CMR38-125-77) measured from 4:30 to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), and hot and hot (E (E ,F ,F ,K ,K ,L ,L ,Q ,Q ,R ,R ,W ,W and and X X ) sea ) sea son. Data son. Data shows shows mean of two replicates mean of two replicates ± ± SD. SD. PSII 316 photochemistry (ФPSII) (A–F), electron transport rate (ETR) (G–L) and non-photochemical quenching (NPQ) (M–R). The measurements were performed from 4:30 to 18:30 at 2- to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N), cool (C,D,I,J,O,P), and hot (E,F,K,L,Q,R) season. Data shows mean of two replicates SD. 339 and hot (E,F,K,L,Q,R,W and X) season. Data shows mean of two replicates ± SD. 317 h intervals on two sunny days in rainy (A,B,G,H,M and N), cool (C,D,I,J,O and P), and hot (E,F,K,L,Q and R) season. Data shows mean of two replicates ± SD. Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy Agronomy 2019 2019 , , 99 , x; , x; doi: FOR doi: FOR PE PE EE RR REVI REVI EW EW www. www. mdpi. mdpi. cc om/ om/ jou jou rnal/agronomy rnal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, 206 13 of 27 Table 2. Seasonal variation in Chl fluorescence and leaf gas exchange parameters of four cassava genotypes. F /F , maximal photochemical quantum yield of PSII; v m F , e ective quantum yield of PSII photochemistry; ETR, electron transfer rate; NPQ, non-photochemical quenching; R, respiration rate; Pn; net photosynthetic rate; PSII Gs, stomatal conductance; Tr, transpiration rate; Ci, intercellular CO concentration; Ci/Ca, ratio between intercellular and ambient CO concentration; LUE, light use 2 2 eciency; WUE, water use eciency. Minima (min), maxima (max) and means were from 24 measurements (six time points during 6:30–16:30 h x two leaves x two days in each season), except the values for F /F and R in which 4 measurements were taken from two leaves of each genotype at 04:30 on two days. Means which are v m significantly di erent (p < 0.05) among genotypes are denoted with di erent lower case letters, whereas those among seasons are represented by di erent capital letters. Rainy Cool Hot F-test Critical-P Genotype Parameter 2 2 min max mean min max mean min max mean Value Value RY9 0.862 0.871 0.866 a 0.823 0.878 0.845 0.848 0.856 0.852 2.681 0.122 RY11 0.842 0.849 0.845 b 0.828 0.836 0.833 0.829 0.862 0.845 2.765 0.116 F /F v m KU50 0.844 0.85 0.847 ab A 0.829 0.846 0.837 B 0.842 0.854 0.847 A 4.915 0.036 CMR38-125-77 0.85 0.866 0.858 ab A 0.833 0.843 0.838 B 0.848 0.862 0.854 A 9.950 0.005 F-test value 15.126 0.374 0.974 Critical-P value <0.001 0.773 0.437 mean 0.854 A 0.838 B 0.849 A 11.142 <0.001 RY9 0.51 0.81 0.71 A 0.41 0.82 0.58 B 0.43 0.81 0.59 B 8.852 <0.001 RY11 0.34 0.82 0.70 A 0.33 0.82 0.54 B 0.38 0.8 0.59 AB 7.105 0.002 PSII KU50 0.41 0.85 0.69 A 0.37 0.82 0.54 B 0.35 0.81 0.60 AB 6.476 0.003 CMR38-125-77 0.39 0.82 0.69 A 0.35 0.83 0.56 B 0.19 0.8 0.53 B 6.850 0.002 F-test value 0.135 0.250 1.059 Critical-P value 0.939 0.861 0.352 mean 0.70 A 0.56 B 0.58 B 27.745 <0.001 ETR RY9 8 304 94 B 2 304 173 A 16 343 190 A 6.758 0.002 [mol(e-)/m /s] RY11 5 353 92 B 1 257 144 AB 19 310 158 A 3.351 0.041 KU50 4 327 77 B 1 260 152 A 11 309 155 A 6.325 0.003 CMR38-125-77 6 310 97 2 256 158 14 307 134 3.079 0.052 F-test value 0.252 0.481 1.300 0.860 0.696 0.279 Critical-P value mean 90 B 157 A 159 A 18.251 <0.001 RY9 0.08 0.61 0.37 0.04 0.64 0.42 0.06 0.64 0.44 0.956 0.389 RY11 0.05 0.71 0.32 0.01 0.74 0.42 0.09 0.67 0.44 2.825 0.066 NPQ KU50 0.12 0.59 0.31 0.02 0.63 0.39 0.03 0.65 0.41 2.36 0.102 CMR38-125-77 0.04 0.66 0.34 B 0.03 0.65 0.40 AB 0.06 0.8 0.50 A 4.255 0.018 F-test value 0.951 0.128 1.100 0.419 0.943 0.353 Critical-P value mean 0.34 B 0.41 A 0.45 A 9.55 <0.001 Agronomy 2019, 9, 206 14 of 27 Table 2. Cont. Rainy Cool Hot F-test Critical-P Parameter Genotype 2 2 min max mean min max mean min max mean Value Value R RY9 1.27 1.94 1.63 B 0.85 1.7 1.26 ab B 2.25 3.03 2.61 a A 14.37 0.002 RY11 1.18 2.41 1.65 AB 1.13 1.91 1.52 ab B 2.23 2.64 2.39 ab A 5.296 0.03 [molCO /m /s] KU50 0.74 1.81 1.38 AB 0.68 1.05 0.84 b B 1.3 2.32 1.82 b A 6.599 0.017 CMR38-125-77 0.97 1.58 1.23 B 1.59 4.26 2.96 a A 1.95 2.26 2.14 ab AB 6.164 0.021 F-test value 1.048 7.544 4.95 Critical-P value 0.407 0.004 0.018 mean 1.47 B 1.65B 2.24A 5.701 0.006 Pn RY9 0.20 36.00 14.00 0.78 32.02 16.77 1.33 31.57 14.67 0.895 0.413 (molCO /m /s) RY11 0.70 31.70 11.20 0.72 30.09 17.19 1.81 33.31 17.02 2.036 0.138 KU50 0.10 28.40 9.54 0.22 23.14 11.77 0.1 31.78 14.64 1.835 0.167 CMR38-125-77 0.90 27.50 12.30 0.46 26.51 12.86 0.14 31.99 10.97 0.281 0.756 F-test value 0.397 1.51 1.471 0.755 0.217 0.228 Critical-P value mean 11.75 B 14.60 A 14.32 AB 3.157 0.044 Gs RY9 0.10 1.24 0.58 A 0.01 0.57 0.23 B 0.05 0.59 0.27 B 18.141 <0.001 (molH O/m /s) RY11 0.11 1.71 0.57 A 0.05 0.59 0.26 B 0.08 0.69 0.40 A 9.266 <0.001 KU50 0.08 1.97 0.53 A 0.00 0.41 0.18 B 0.05 0.75 0.34 A 8.253 <0.001 CMR38-125-77 0.02 1.03 0.44 A 0.01 0.36 0.17 B 0.02 1.11 0.26 B 9.397 <0.001 0.67 1.525 2.156 F-test value Critical-P value 0.572 0.213 0.099 mean 0.53 A 0.21 C 0.32 B 40.295 <0.001 Tr RY9 1.43 10.33 5.28 0.09 12.87 5.36 0.74 11.26 6.36 ab 0.730 0.486 RY11 0.75 8.76 4.23 B 0.07 13.33 5.15 B 1.34 15.22 8.52 a A 8.695 <0.001 [mmolH O/m /s) KU50 1.02 8.95 4.08 AB 0.03 11.13 3.88 B 0.34 12.09 6.74 ab A 6.484 0.003 CMR38-125-77 1.11 8.68 4.52 0.1 9.44 4.24 0.53 11.75 4.74 b 0.149 0.862 F-test value 1.074 0.868 3.719 Critical-P value 0.364 0.461 0.014 mean 4.52 B 4.65 B 6.58 A 11.227 <0.001 Ci RY9 183 436 328 A 104 548 250 B 137 455 267 B 4.663 0.013 (molCO /mol air] RY11 198 493 338 97 563 275 201 433 292 2.967 0.058 KU50 215 482 341 A 107 504 257 B 190 476 300 AB 5.795 0.005 CMR38-125-77 213 443 334 A 92 579 252 B 96 468 265 B 4.731 0.012 F-test value 0.131 0.243 0.961 0.941 0.866 0.415 Critical-P value mean 335 A 258 B 281 B 17.73 <0.001 Agronomy 2019, 9, 206 15 of 27 Table 2. Cont. Rainy Cool Hot F-test Critical-P Parameter Genotype 2 2 min max mean min max mean min max mean Value Value Ci/Ca RY9 0.56 1.00 0.86 A 0.28 1.31 0.64 B 0.37 0.98 0.68 B 7.825 <0.001 RY11 0.52 0.99 0.85 A 0.26 1.33 0.69 B 0.57 0.96 0.76 AB 4.239 0.018 KU50 0.64 0.99 0.87 A 0.28 1.20 0.65 B 0.52 0.99 0.75 AB 9.781 <0.001 CMR38-125-77 0.64 0.99 0.86 A 0.28 1.20 0.65 B 0.25 0.99 0.67 B 8.91 <0.001 F-test value 0.0875 0.215 2.036 Critical-P value 0.967 0.886 0.114 mean 0.85 A 0.70 B 0.71 B 29.177 <0.001 LUE RY9 0.009 0.034 0.023 b 0.016 0.04 0.025 0.01 0.035 0.020 ab 1.845 0.166 (molCO /mol photon) RY11 0.015 0.097 0.035 a 0.012 0.116 0.029 0.014 0.036 0.023 a 1.596 0.210 KU50 0.016 0.056 0.030 ab A 0.011 0.039 0.021 AB 0.002 0.038 0.020 ab B 3.509 0.035 CMR38-125-77 0.016 0.058 0.033 a A 0.01 0.035 0.020 B 0.001 0.043 0.016 b B 11.196 <0.001 F-test value 2.791 1.592 2.871 Critical-P value 0.045 0.197 0.041 mean 0.030 A 0.023 B 0.019 B 9.46 <0.001 WUE RY9 0.09 5.26 2.21 B 1.14 10.98 4.76 A 0.84 3.86 2.26 B 14.508 <0.001 (molCO /mmol H O) RY11 0.26 6.15 2.34 B 0.62 12.36 4.79 A 0.55 3.41 1.92 B 7.374 0.001 2 2 KU50 0.14 6.54 2.28 B 0.48 13.79 4.30 A 0.21 3.14 1.86 B 7.770 <0.001 CMR38-125-77 0.37 5.9 2.52 B 1.43 14.82 4.25 A 0.18 4.64 2.18 B 6.903 0.002 F-test value 1.118 0.299 1.135 Critical-P value 0.346 0.826 0.339 mean 2.33 B 4.52 A 2.05 B 26.604 <0.001 1 2 F and P value for testing each trait among genotypes within season (the same column). F and P value for testing each trait among seasons of each genotype (the same row). Agronomy 2019, 9, 206 16 of 27 3.4. Diurnal Leaf Gas Exchange Diurnal responses of leaf gas exchange and related parameters, i.e., Pn, Gs and Tr of four cassava genotypes measured during 04:30–18:30 on the same days as Chl fluorescence measurements were displayed in Figure 5. For each season, the diurnal minima, maxima and means of R, Pn, Gs, Tr, Ci Ci/Ca, LUE and WUE which were recorded during 06:30 to 16:30 across two days of investigation were summarized in Table 2. The values for dark respiration rates (R) in Table 2 were obtained from leaf gas exchange measurements in the dark at 04:30. Seasonal variation in R of cassava leaves was observed in which the mean across genotypes was highest in the hot (2.24 molCO /m /s) followed by the significantly lower rates (p = 0.006) in the cool 2 2 (1.65 molCO /m /s) and the rainy (1.47 molCO /m /s) seasons (Table 2). Significantly di erent R 2 2 among genotypes were observed in the hot and cool seasons with KU50 showing significantly lower R (p < 0.05) than CMR38-125-77 in the cool season, and RY9 in the hot season. Diurnal changes in Pn (Figure 5A–F) were closely related to those of PAR (Figure 3A–F). leaf The highest mean Pn across genotypes was found in the cool season at 14.60 molCO /m /s followed by that of the hot season at 14.32 molCO /m /s. The lowest mean Pn across genotypes was found in the rainy season (11.75 molCO /m /s) which was significantly lower (p = 0.044) than that in the cool (14.60 molCO /m /s) season. However, Pn among the four genotypes were not significantly di erent in any season. The patterns of diurnal response in Gs (Figure 5G–L) were related to variation in Pn (Figure 5A–F). Means of Gs across genotypes significantly (p < 0.001) di ered among the three seasons being highest in 2 2 2 the rainy (0.53 molH O/m /s) followed by the hot (0.32 molH O/m /s) and the cool (0.21 molH O/m /s) 2 2 2 seasons (Table 2). In any season Gs among the four genotypes were not significantly di erent. Diurnal responses of Tr (Figure 5M–R) followed similar patterns as those of Pn (Figure 5A–F), ETR (Figure 4G–L) and NPQ (Figure 4M–R). Cassava leaves displayed the highest mean Tr across genotypes (6.58 mmolH O/m /s) in the hot season which was significantly higher (p < 0.001) than 2 2 that in the cool (4.65 mmolH O/m /s) and rainy (4.52 mmolH O/m /s) seasons (Table 2). Significant 2 2 di erences in mean Tr among genotypes were detected only in the hot season, with RY11 showing significantly higher mean (p = 0.014) than CMR38-125-77. Diurnal pattern of changes in Ci/Ca was depicted in Figure 6A–F showing that Ci/Ca was high in the early morning, declining to reach minimum values mostly at 12.30, then slowly increased in the afternoon. Means of diurnal Ci/Ca across genotypes were similar in the cool and hot seasons (0.70 and 0.71, respectively) which were significantly lower (p < 0.001) than that in the rainy season (0.85) (Table 2). However, in any season, mean Ci/Ca among genotypes did not di er significantly. It was apparent that cassava plants utilized light energy for photosynthesis at di erent eciencies in di erent seasons (Figure 6G–L). The means of LUE across genotypes was highest in rainy season (0.030) and significantly higher (p < 0.001) than that in the cool (0.023) and hot (0.019) seasons (Table 2). The means of LUE among genotypes were noted in the rainy and hot seasons. In the rainy season, RY9 had lowest LUE (0.023) which was significantly di erent (p = 0.045) from that of RY11 (0.035) and CMR38-125-77 (0.033). In the hot season, LUE of CMR38-125-77 was lowest (0.016) which was significantly lower (p = 0.041) than that of RY11 (0.023). In general, WUE tended to be higher in the early morning then declining throughout the day (Figure 6M–R). Cassava leaves expressed highest means of diurnal WUE across genotypes in the cool (4.52 molCO /mmolH O) season which was significantly higher 2 2 (p < 0.001) than that in the rainy and hot season (2.33 and 2.05 molCO /mmolH O, respectively). 2 2 In any season, no significance di erences in WUE among genotypes were found. Agronomy 2019, 9, 206 17 of 27 336 336 337 337 Figure 5. Diurnal Figure 5. Figure 5. pattern Diurnal pattern of Diurnal pattern of of net photosynthetic ne net photosynthetic rate t photosynthetic rate rate (Pn) (A–F), (Pn) (Pn) stomata ( (A–F A–F), stomata conductance ), stomata con con (Gs) ductance (Gs) ductance (Gs) (G–L) and ( ( transpiration G–L G–L) and transpiration rate ) and transpiration rate rate (Tr) (M–R) (T (T of r) ( r) ( four M–R M–R cassava ) of ) of four four genotypes cassava cassava genotypes ( ( genotypes ( X, RY9; x x, RY9; , RY9; RY11; RY11; 337 Figure 5. Diurnal pattern of net photosynthetic rate (Pn) (A–F), stomata conductance (Gs) (G–L) and transpiration rate (Tr) (M–R) of four cassava genotypes (x, RY9; RY11; 337 Figure 5. Diurnal pattern of net photosynthetic rate (Pn) (A–F), stomata conductance (Gs) (G–L) and transpiration rate (Tr) (M–R) of four cassava genotypes (x, RY9; RY11; 338 338 , RY11; , KU50 and , CMR38-125-77) , , CMR38-125-77) measured from CMR38-125-77) measured from measured from 4:30 to4:30 to 18:30 at 4:30 to 18:30 at 18:30 at 2-h inte2-h intervals on two rvals 2-h intervals on two on two sunny days sunny days in rainy ( sunny days in rainy ( in rainy (A,B,G,HA ,A M ,,B B ,N ,,G G ),,,H H cool ,,M M,,( N N C,,,S S D and ,and I,J,O T T ,P ), cool ), cool ), and ( (hot C C,,D D,,II,,JJ,,O O,,P P,,U U and and V V), ), , CMR38-125-77) measured from 4:30 to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), 338 339 339 (E,F,K,L,Qand hot ,and hot R) season. ((E E,,F Data F,,K K,,L L,shows ,Q Q,,R R,,W W mean and and X X of )) sea sea two son. Data son. Data replicates shows shows SD.mean of two replicates mean of two replicates ± ± SD. SD. , CMR38-125-77) measured from 4:30 to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), 339 and hot (E,F,K,L,Q,R,W and X) season. Data shows mean of two replicates ± SD. and hot (E,F,K,L,Q,R,W and X) season. Data shows mean of two replicates ± SD. Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, 206 18 of 27 336 336 370 Figure 6. Figure Diurnal pattern of 6. Diurnal pattern ratio betwe of ratio betwe en in enternal CO internal CO 2 concentration concentration 337 337 and ambient and ambient Figure 5. Figure 5. COCO 2 (Ci / Diurnal pattern of (Ci Ca Diurnal pattern of )/ ( Ca) A–F (A ),– iF n), stantaneou instantaneous ne ne t photosynthetic rate t photosynthetic rate s lighlight t use efficien use eciency cy (LUE) ( (Pn) (Pn) ((LUE) ( A–F A–F G–L ), stomata ), stomata (G ) and –L) and instantaneous water con con instantaneous ductance (Gs) ductance (Gs) ( ( G–L G–L ) and transpiration rate ) and transpiration rate (T (T r) ( r) ( M–R M–R ) of ) of four four cassava cassava genotypes ( genotypes ( xx , RY9; , RY9; RY11; RY11; 2 2 337 Figure 5. Diurnal pattern of net photosynthetic rate (Pn) (A–F), stomata conductance (Gs) (G–L) and transpiration rate (Tr) (M–R) of four cassava genotypes (x, RY9; RY11; 338 338 water use eciency (WUE) (M–R) of four cassava cultivars (X, RY9; , RY11; , KU50 and , CMR38-125-77) , , CMR38-125-77) measured from CMR38-125-77) measured from measured on two sunny4:30 to 18:30 at d4:30 to 18:30 at ays in rainy (A,2-h intervals on two B2-h intervals on two ,G,H,M,N), sunny days in rainy ( sunny days in rainy ( A A ,B ,B ,G ,G ,H ,H ,M ,M ,N ,N ,S ,S and and TT ), cool ), cool ( ( CC ,D ,D ,I,,IJ,,JO ,O ,P ,P ,U ,U and and V V ), ), 371 use efficiency (WUE) (M–R) of four cassava cultivars (x, RY9; , RY11; , KU50 and , CMR38-125-77) measured on two sunny days in rainy (A,B,G,H,M,N,S and T), cool cool (C,D,I,J,O,P), and hot (E,F,K,L,Q,R) season. 339 339 338 , CMR38-125-77) measured from 4:30 to 18:30 at 2-h intervals on two sunny days in rainy (A,B,G,H,M,N,S and T), cool (C,D,I,J,O,P,U and V), and hot and hot (E (E ,F ,F ,K ,K ,L ,L ,Q ,Q ,R ,R ,W ,W and and XX ) sea ) sea son. Data son. Data shows shows mean of two replicates mean of two replicates ± ± SD. SD. 372 (C,D,I,J,O,P,U and V), and hot (E,F,K,L,Q,R, W and X) season. and hot (E,F,K,L,Q,R,W and X) season. Data shows mean of two replicates ± SD. Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy Agronomy 2019 2019 , 9 , , x; 9, x; doi: FOR doi: FOR PE PE EE RR REVI REVI EW EW www. www. mdpi. mdpi. com/ com/ jou jou rnal/agronomy rnal/agronomy Agronomy 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/agronomy Agronomy 2019, 9, 206 19 of 27 3.5. The Relationship between Cassava Leaf Photosynthesis and Environmental Field Conditions The relationships between leaf gas exchange and environmental parameters are demonstrated by the matrix of correlation coecient values (r) for each season in Table 3. Among the four environmental parameters, PAR showed the highest positive correlations with Pn across all seasons. The correlation leaf was highest in the rainy (r = 0.93, p < 0.01) followed by the cool (r = 0.82, p < 0.01) and the hot (r = 0.73, p < 0.01) seasons. T also expressed highly significant correlations with Pn i.e., 0.76, 0.48 and 0.46 leaf in the rainy, cool and hot seasons, respectively. RH , on the other hand, showed highly significant negative correlations with Pn in all seasons. Pn had significant positive correlations with VPD only in the rainy (r = 0.57, p < 0.01) and cool (r = 0.33, p < 0.01) seasons. The relationships between Tr and all four environmental parameters were highly significant and occurred in the same ways as those for Pn. It is worth noted that the relationships between Tr and PAR had lower correlations than leaf between Pn and PAR but the opposite occurred for RH . The relationships between Ci and all leaf C four environmental parameters were also highly significant but occurred in the opposite directions as compared to those for Pn and Tr. The absolute values of correlation coecient were highest between Ci and T especially in the rainy and hot seasons (r = 0.90, p < 0.01). The relationships between Pn leaf and Tr were positively correlated in all seasons being higher in the hot (r = 0.75, p < 0.01) and cool (r = 0.74, p < 0.01) and lower in the rainy season (r = 0.67, p < 0.01). The positive correlations between Pn and Gs were highly significant only during the cool and hot seasons, whereas those between Tr and Gs were highly significant in all seasons i.e., r = 0.73, 0.45 and 0.39 in the cool, hot and rainy season, respectively. Negative correlations between Pn and Ci were highest in the rainy season (r = 0.84, p < 0.01) followed by the cool (r = 0.63, p < 0.01) and the hot (r = 0.50, p < 0.01) seasons. Table 3. A correlation matrix of net photosynthetic rate (Pn), stomata conductance (Gs), transpiration rate (Tr), intercellular CO concentration (Ci), photosynthetically active radiation (PAR ), leaf temperature 2 leaf (T ), leaf vapor pressure deficit (VPD ) and canopy relative humidity (RH ). The correlations which leaf L C are significantly di erent (p < 0.05 and p < 0.01) are denoted with * and **. Parameter Season Pn Gs Tr Ci PAR T RH leaf leaf C Gs Rainy 0.59 ** Cool 0.74 ** Hot 0.50 ** Tr Rainy 0.67 ** 0.39 ** Cool 0.74 ** 0.73 ** Hot 0.75 ** 0.45 ** Ci Rainy 0.84 ** 0.27 ** 0.50 ** Cool 0.63 ** 0.21 0.37 ** Hot 0.50 ** 0.18 0.54 ** PAR Rainy 0.93 ** 0.01 0.69 ** 0.79 ** leaf Cool 0.82 ** 0.53 ** 0.62 ** 0.67 ** Hot 0.73 ** 0.18 0.77 ** 0.79 ** T Rainy 0.76 ** 0.34 ** 0.49 ** 0.90 ** 0.80 ** leaf Cool 0.48 ** 0.28 ** 0.66 ** 0.74 ** 0.58 ** Hot 0.46 ** 0.22 0.58 ** 0.90 ** 0.76 ** RH Rainy 0.30 ** 0.19 ** 0.76 ** 0.37 ** 0.31 ** 0.34 ** Cool 0.54 ** 0.32 ** 0.69 ** 0.69 ** 0.61 ** 0.93 ** Hot 0.50 ** 0.13 0.56 ** 0.63 ** 0.48 ** 0.71 ** VPD Rainy 0.57 ** 0.35 ** 0.53 ** 0.78 ** 0.65 ** 0.86 ** 0.63 ** Cool 0.33 ** 0.04 0.48 ** 0.61 ** 0.43 ** 0.85 ** 0.83 ** Hot 0.16 0.50 ** 0.26 ** 0.79 ** 0.57 ** 0.91 ** 0.44 ** 4. Discussion The results reported here clearly demonstrated cassava resiliency under variable climatic conditions, a trait of great importance for adaptation of the crop to future climate change/global Agronomy 2019, 9, 206 20 of 27 warming in the tropics/subtropics where other staple crops might fail [32,33]. The seasonal climatic pattern at the study site varied considerably during the study period. The monthly mean temperature fluctuated from 24 C in February 2016 to 32 C in April 2016, RH from 80% in October 2015 to 40% in April 2016 and rainfall from 323 mm in August 2015 to zero in December 2015 and February 2016 (Figure 1). However, diurnal patterns of photosynthesis (leaf Pn) of field-grown cassava under full irrigation (Figure 5A–F) displayed similar response pattern in di erent seasons which more or less paralleled with diurnal changes in PAR (Figure 3A–F), despite di erences in air temperature and RH. In the rainy season, the daily peaks of Pn occurred at 10:30 or 12:30, depending on genotypes, showing maximum Pn between 27.50 and 36.0 molCO /m /s (Table 2). Much higher temperature and VPD in the hot season could be the major causes of the shift in daily peak of Pn to 8:30 or air 10:30 (Figure 5E,F) depending on genotypes while maximum Pn remained high between 31.57 and 33.31 molCO /m /s (Table 2). Rosenthal et al. [34] measured diurnal Pn of field-grown cassava in Illinois, USA during mild summer (June–August), where total rainfalls were 377 mm, mean daily minimum and maximum temperatures were 18 and 30 C, and found that these cassava plants also exhibited the Pn peaks around noon with Pn values varying from 18–28 molCO /m /s. In contrast, in a seasonally dry environment, cassava had maximum Pn of 33 molCO /m /s (average of 10 cultivars) in the early morning (08:00) and decreased thereafter [16]. Therefore, the diurnal patterns of Pn and the range of maximum Pn values in the current study were in accordance with earlier reports. Variations in diurnal photosynthesis were apparent among genotypes in the cool and hot season. In general, the pre-noon environments were favorable for all four genotypes with small variations in Pn (Figure 5A–F). Nevertheless, during the afternoon Pn of KU50 and CMR38-125-77 tended to be slightly lower than the others particularly in the cool season, while afternoon Pn of CMR38-125-77 had a tendency to be lower than the others in both cool and hot seasons (Figure 5C–F). This could partly be due to lower light incidence on the leaf surface of KU50 and CMR38-125-77 as a result of their prominent leaf-drooping behavior under high light intensity compared to RY9 and RY11 which hardly showed any drooping (see Supplementary Figure S1). Leaf movement in cassava is known as a stress avoidance mechanism in both well-watered and stressed plants [35,36]. Genotypic variation in seasonal Pn of field-grown cassava was well-documented in earlier reports [37–39]. A recent study in four African cultivars of cassava (two landraces and two improved lines) under a greenhouse condition showed almost perfect bell-shaped diurnal response with Pn peak at 12:30 and maximum Pn varying from 22 to 27 molCO /m /s [40]. The relationships between physical parameters of leaf including PAR T , RH , and VPD leaf, leaf C L and photosynthetic parameters (Pn, Gs, Tr, and Ci) in di erent seasons are expressed in a correlation matrix shown in Table 3. In each season, Pn had the strongest positive correlations with PAR leaf (Table 3). Among ecological factors, PAR together with temperature and VPD have been shown to be highly correlated with Pn [41,42]. Diurnal variation in PAR di ered in di erent seasons, and Pn showed a bell-shaped response parallel with PAR during the mild spring while Pn peaked very early in the morning during hot summer [40]. In this study, although maximum PAR and PAR occurred A leaf in the rainy followed by the hot and the cool season (Table 1), the mean daily PAR values were leaf lowest in the rainy season (p < 0.001, Table 1) due to frequent cloud cover causing highly fluctuating PAR (Figure 3A,B). Lowest mean daily PAR in the rainy season may attribute to lower mean daily A leaf Pn (11.75 molCO /m /s, p = 0.044) than the cool and hot seasons (Table 2). A recent report [43] also pointed out that solar radiation is a limiting factor in rainy season based on comparison between maximum net photosynthetic rates (Pnmax) from light response curve and the predicted Pn from actual solar radiation data. It is known that Pn in fully expanded young cassava leaves developed under sunny warm climate does not reach light saturation even up to 1800 mol/m /s [41]. In each season, Pn were significantly correlated with PAR as well as T , RH and VPD (Table 3). In spite leaf leaf C L of the significant di erences (p < 0.001) in mean T and VPD between the cool and hot seasons air air (Table 1), well-watered cassava in this study performed equally well showing the daily mean Pn of 14.60 and 14.32 molCO /m /s, respectively (Table 2). Moreover, it is worth noting that in the 2 Agronomy 2019, 9, 206 21 of 27 hot season cassava genotype RY11 could maintain maximum daily Pn at 28.9 molCO /m /s while leaf temperature reached 39.8 C. Previous studies reported optimum temperature range for cassava photosynthesis in tropical environments between 30–35 C [38,44]. This indicated that these improved cassava genotypes have been well-adapted to environments in di erent seasons in this climatic zone. Cassava can be widely adapted to environments and usually requires a warm climate with high solar radiation for optimum photosynthesis, growth and productivity [44]. Among leaf gas exchange parameters, in the rainy season under fluctuating light intensity but high RH, higher correlation was found between Pn and Ci ( 0.84, p < 0.01) than between Pn and Gs (0.59, p < 0.01) (Table 3) indicating a stronger role of photosynthetic capacity on CO fixation or non-stomatal regulation as compared to stomatal control of photosynthesis. Gas exchange measurements of 15 cassava cultivars mostly during high rainfall periods also found higher correlation between Pn and Ci ( 0.84) than Pn and Gs (0.40) [39]. Non-stomatal limitation may be attributed to mesophyll resistance to CO flux, carboxylation eciency of Rubisco and RuBP regeneration [45]. The extent to which Rubisco limits photosynthesis depends largely on irradiance [46]. Therefore, low mean daily Pn in the rainy season could be attributed to low activity of Rubisco under fluctuating and low mean daily PAR (Figure 3A,B; Table 1). In the cool and hot seasons, Pn was influenced by both stomatal and non-stomatal controls as indicated by highly significant correlations (p < 0.01) between Pn and Gs, and Pn and Ci (Table 3). In the cool season, higher correlation between Pn and Gs (0.74, p < 0.01) than Pn and Ci (0.63, p < 0.01) may indicate stronger role of stomatal limitation inferred by lowest Gs (0.21 molH O/m /s; p < 0.001) in the cool season (Table 3). In the cool and hot season, RH was significantly lower (p < 0.001) than that in the rainy season (Table 1). Cassava is very air sensitive to low air humidity and its stomatal conductance rapidly decreases in response to dry air irrespective of soil water conditions [44,47]. In the cool and hot season, maximum Gs of approximately 0.5 molH O/m /s occurred at 08:30 or 10:30 (Figure 5I–L) coinciding with high RH and low VPD 2 L in the early morning (Figure 3O–R,U–X), thereafter Gs declined in parallel with decreasing RH and increasing VPD resulting in decreasing Pn during the afternoon. Nevertheless, under irrigation, cassava was able to maintain relatively high mean daily Pn (14.60 and 14.32 molCO /m /s; Table 2) while mean Gs values were higher than 0.15 molH O/m /s (Table 2) which is the threshold value above which the plants would be considered under non- or mild water stress conditions [48]. It has been suggested that photosynthesis metabolism is substantially resistant to water stress until Gs is below 0.1–0.15 molH O/m /s [49]. Diurnal changes in transpiration rates (Tr) paralleled closely those of Pn (Figure 3A–F,M–R) and had highly significant correlations with Gs (Table 3). This indicated that transpiration was greatly influenced by stomatal regulation particularly in the hot season. Transpiration rates were similar in the rainy and cool seasons (4.52 and 4.65 mmolH O/m /s), and significantly higher (p < 0.001) in the hot (6.58 mmolH O/m /s) season (Figure 5M–R, Table 2) coinciding with increasing VPD 2 air and VPD in the latter (Figure 3S–X, Table 1). Pronounced e ects of VPD on stomatal movement L L and transpiration rates were classically demonstrated in cassava [47]. Similar seasonal variation was reported in orange trees in which transpiration rates of well-watered orange plants in summer were about 2.5 folds higher than that in winter [50]. Highest Tr in the hot season resulted in lowest WUE (2.05 molCO /mmol H O) in the hot which was significantly lower (p < 0.001) than that in the cool 2 2 season (Table 2). High WUE in the cool season (4.52 molCO /mmol H O) was due to lower Tr 2 2 (4.65 mmol/m /s) as a result of partially closed stomata in response to dry air (Table 2). El-Sharkawy and De Tafur [39] reported similar WUE value of 4.5 molCO /mmol H O which was averaged from 2 2 numerous measurements performed from upper canopy leaves of 15 cassava cultivars. Mean Tr among genotypes were significantly di erent (p = 0.014) only in the hot season i.e., the values appeared in the order RY11 > KU50 = RY9 > CMR38-125-7, the same order as for Gs (Table 2). High Tr played crucial role in heat dissipation, therefore maximum T in the hot season was highest in CMR38-125-77 leaf (44.3 C) and lowest (41.0 C) in RY11 and KU50 (Table 1). Lower Tr in RY9 and CMR38-125-77 was related to higher WUE, although not statistically significant, than RY11 and KU50 (Table 2). Agronomy 2019, 9, 206 22 of 27 When measured under natural rainfed environments, 15 cultivars of cassava exhibited large variations in WUE from 3.89 to 4.74 molCO /mmol H O [39]. 2 2 The observation that maximum quantum yield of PSII photochemistry (F /F ) values of all v m four cassava genotypes at 04:30 (predawn) were between 0.823–0.878 (Table 2) across all three seasons indicated that cassava leaves were healthy, and no chronic damages occurred in PSII [51]. However, significantly (p < 0.001) lower F /F was observed in the cool season compared to the others. v m Negative e ects of low temperature (in winter and spring) on reduction of F /F have been reported v m in roses [52] and temperate bamboo [53]. Energy utilization by a leaf is indicated by diurnal changes in the e ective quantum yield of PSII photochemistry (F ) which changed in the opposite direction as PSII PAR and showed similar patterns in all seasons. However, as shown in Figure 4A–F, the recovery of F in the afternoon occurred much earlier in rainy season (average F at 14:30 was 0.77) than in the PSII PSII cool and hot seasons (average F at 14:30 were 0.43 and 0.53 in the cool and hot season, respectively). PSII In addition, mean daily F across genotypes was significantly higher (p < 0.001) than in the hot PSII and cool seasons (Table 2). This indicated the interactive e ects between light intensity and other environmental parameters such as temperature and VPD in the cool and hot seasons. Even though the soil moistures were optimized due to irrigation, stressful environments in the cool and hot season clearly posed negative e ects on energy utilization [40,54]. The patterns of diurnal changes in ETR (Figure 4G–R) were similar and parallel to the curves of PAR (Figure 3A–F). The F and the derived ETR are dependent on ambient PAR. Hence, mean PSII daily ETR across genotypes in the rainy season was significantly lower (p < 0.001) than the others (Table 2). Theoretically, under controlled conditions F and ETR are accurately correlated with PSII Pn and can be used to predict CO assimilation and hence productivity [28]. Nevertheless, under stressful environments during the afternoon in the hot season, Pn of RY9 peaked at 08:30 on the 5 April 2016 which was the hotter day (Figure 5F) while ETR continued to increase to reach maximum at 12:30 (Figure 4L). Similar results were observed in cassava cv. RY9 under both irrigated and rainfed conditions [55] and also in other plants under irrigation such as soybean [56] and peach palms [57]. This indicated that after 08:30, under limited CO availability due to stomatal closure after 8.30 (Figure 5K,L), higher proportion of reductants generated from electron transport could be allocated to alternative electron sinks most commonly photorespiration, Mehler reactions and cyclic electron flow [58,59]. These alternative pathways served to balance photosynthesis electron transfer so that light energy is optimally used for CO fixation and over-reduction of electron carriers and excess generation of reactive oxygen species are prevented [60]. The diurnal patterns of NPQ curves were parallel to the curves of PAR because NPQ operated to dissipate excess light energy as heat to protect PSII from photodamage [61,62]. Both PAR and NPQ across genotypes were highest in the hot followed by the cool and significantly lower (p < 0.001) in the rainy season (Tables 1 and 2). Moreover, similar to other previously mentioned parameters (Pn, F and ETR), genotypic variations in NPQ were more PSII apparent in the hot season than the others. Compared with the others CMR38-125-77 had a tendency to have lowest F and ETR but highest NPQ (Figure 4E,F,K,L,Q,R) during 10:30–14:30 in the hot PSII season, indicating the most active photoprotective mechanisms. The most prominent component of NPQ is qE which harmlessly dissipated excess light energy as heat through functioning of the xanthophyll cycle and PsbS protein [63]. It was suggested that more PsbS protein and hence increasing qE capacity might improve crop production in adverse environments [64]. Despite lowest leaf-level Pn in the hot season (Table 2), CMR-38-125-77 had better growth than the others as evidenced by significantly higher leaf production rate and LAI (Figure 2). A recent report in rice showed that rice transgenic line overexpressing PsbS protein which regulated qE had higher NPQ than wild type but comparable leaf-level ETR and Pn. Higher NPQ in the transgenic rice line eciently protected PSII from photodamage, hence displayed better growth, higher leaf area per plant, higher photosynthetic performance, greater total biomass and finally higher grain yield than the wild type [65]. Although leaf-level Pn was lowest in the rainy season cassava plants had much better growth, as indicated by significantly higher (p < 0.001) means across genotypes of rate of increase in plant height Agronomy 2019, 9, 206 23 of 27 and LAI than in the cool and hot seasons (Figure 2; Table S2). In relation to photosynthesis and early vegetative growth (0–3 months), all four genotypes performed equally well in the rainy and cool season (Figure 2). However, in the hot season, CMR-38-125-77 showed significantly higher leaf production rate and LAI than the others (Figure 2). Importantly, at the age of 3 months CMR38-125-77 growing in the 2 2 hot season had LAI of 3.49 m m , not significantly di erent from those growing in the rainy season 2 2 (LAI = 3.57 m m ), whereas hot-season LAI values of the other genotypes showed 20–37% reduction from those in the rainy season crop (Figure 2, Table S2). Although CMR38-125-77 had a moderate leaf-level Pn, its high WUE as well as ecient protective mechanisms (high NPQ and leaf drooping) were beneficial for its growth performance and canopy development. Since analyses of cassava growth and yield are usually evaluated on the basis of both LAI and Pn [14,66], it can be concluded that among the studied genotypes CMR38-125-77 is most suitable for planting in the post-rainy season (in December) to obtain good vegetative growth during the first 3 months. Cock et al. [9] suggested 2 2 that cassava plants should reach LAI of 3.0 m m as quickly as possible in order to obtain good root yield. Similar results were obtained in a parallel experiment at the same site that CMR38-125-77 planted in December had highest LAI at 4 months after planting and subsequently gave highest storage root yield [12]. Moreover, Sawatraksa et al. [67], who studied the same set of genotypes planted in December under rain-fed paddy field conditions, found that CMR38-125-77 had the highest biomass during early vegetative growth. 5. Conclusions Growing cassava in the tropical savanna climate under irrigation, the environmental conditions in the rainy season were the most favorable for early vegetative growth of all four cassava genotypes, based on rate of increase in plant height and LAI at 3 MAP. Among the four genotypes, CMR38-125-77 was the most suitable genotype to be planted in December and growing during the period from cool to hot season, based on its highest rate of leaf production and LAI at 3 MAP. Mean daily net photosynthesis and electron transport rates in the rainy season were slightly lower than those in the cool and hot season due to fluctuating light intensity. Cassava plants displayed several morphological and physiological mechanisms in the hot season, to protect photosynthesis machinery from being damaged under the conditions of high light intensity, temperature and VPD, by leaf drooping, early stomatal closure, enhanced transpiration, thermal dissipation by NPQ and diversion of electrons to alternative sinks, and di erent genotypes may employ di erent strategies to varying extent. Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4395/9/4/206/s1, Figure S1: leaf drooping at midday of cassava cultivars; RY9 (A), RY11 (B), KU50 (C) and CMR38-125-77 (D) growing in the field under irrigated condition. Table S1: ambient photosynthetically active radiation (PAR ), air temperature (T ), relative humidity (RH ), air vapor pressure deficit (VPD ), rainfall and irrigation for air air air the three planting dates (PD). The environmental parameters were recorded from the date of planting until the date when photosynthesis measurements were performed on the three-month-old plants. Environmental parameters for PD-Jun, PD-Nov and PD-Dec were measured during 30 June–27 September 2015, 10 November 2015–23 February 2016 and 15 December 2015–2 April 2016, respectively. The values are daily minima, maxima and means of data collected every 5 min on each day, and the data were then averaged over days. Lower case letters indicate significance di erences (p < 0.05) among planting dates. Table S2: the minima, maxima and means of growth parameters including rate of increase in plant height, rate of leaf production and leaf area index (LAI) of three-month-old plants of cassava genotypes RY9, RY11, KU50 and CMR38-125-77 planted in June 2015 (PD-Jun), November 2015 (PD-Nov) and December 2015 (PD-Dec). Means which are significantly di erent (p < 0.05) among seasons are denoted with capital letters. Means which are significantly di erent (p < 0.05) among genotypes are denoted with di erent lower case letters. Author Contributions: Conceptualization, S.S., P.T., K.V., P.B., N.V., and S.J.; investigation and data collection, S.S.; data analysis, S.S. and P.T.; methodology, S.S., P.T., K.V., P.B., N.V., and S.J.; supervision, P.T.; writing (original draft preparation), S.S. and P.T.; writing (review and editing), S.S., P.T., K.V., P.B., N.V., S.J. and S.R. Funding: This project was financially supported by the Thailand Research Organizations Network (TRON) administered by the National Science and Technology Development Agency (NSTDA). The first author is supported by Ph.D. scholarship from the National Science and Technology Development Agency (NSTDA) under the Thailand Graduate Institute of Science and Technology (TGIST), Grant no. TG-44-12-60-009D. The authors Agronomy 2019, 9, 206 24 of 27 also acknowledge the Thailand Research Fund (Project code: IRG5780003) and Faculty of Agriculture, Khon Kaen University for providing financial support for manuscript preparation activities. Acknowledgments: We would like to thank the member of cassava team project and salt-tolerant rice research group at KKU for field and data collection. Conflicts of Interest: The authors declare no conflict of interest. Abbreviations APAR absorbed photosynthetically active radiation Ca ambient CO concentration Ci intercellular CO concentration Chl chlorophyll Tr transpiration rate ETR electron transfer rate F minimal fluorescence yield of the dark-adapted state F steady state fluorescence in the light-adapted state F the maximal fluorescence of the dark-adapted state F the maximal fluorescence of the light-adapted state F /F the maximal photochemical quantum yield of PSII v m Gs stomatal conductance LUE light-use eciency (=Pn/APAR) LAI leaf area index NPQ nonphotochemical quenching Pn net photosynthetic rate F e ective quantum yield of PSII photochemistry PSII PAR photosynthetically active radiation PAR photosynthetically active radiation on the leaf surface leaf PAR ambient photosynthetically active radiation PSII photosystem II r correlation coecient R respiration rate RH air relative humidity air RH canopy relative humidity T air temperature air T leaf temperature leaf VPD air vapor pressure deficit VPD leaf-to-air vapor pressure deficit WUE water-use eciency (=Pn/Tr) References 1. 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Journal
Agronomy – Multidisciplinary Digital Publishing Institute
Published: Apr 23, 2019