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The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica

The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are... applied sciences Article The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica 1 1 2 1 , 1 , Jiyou Zhu , Qing Xu , Jiangming Yao , Xinna Zhang * and Chengyang Xu * Research Center for Urban Forestry, Key Laboratory for Forest Silviculture and Conservation of Ministry of Education, Key Laboratory for Silviculture and Forest Ecosystem Research in Arid- and Semi-arid Region of State Forestry Administration, Beijing Forestry University, Beijing 100083, China; joezhu1205@gmail.com (J.Z.); qingzi050656@163.com (Q.X.) College of Forestry, Guangxi University, Nanning 530005, China; jiangming618@gmail.com * Correspondence: zhangxinna0513@163.com (X.Z.); cyxu@bjfu.edu.cn (C.X.); Tel.: +86-010-6233-7082 (C.X.) Abstract: Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results showed that the spectral reflectance was higher than those being parasitized in the visible and near-infrared range. The spectral reflectance in 750~1400 nm was the sensitive range of spectral response of host plant to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y = 65913.323x + 9.783, R = 0.6888) based on the reflectance of red valley, which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral parameters and chlorophyll content index. Through the change of spectral parameters, Citation: Zhu, J.; Xu, Q.; Yao, J.; we can predict the chlorophyll content of Osmanthus fragrans under different parasitic degrees. After Zhang, X.; Xu, C. The Changes of Leaf being parasitized, the leaf functional traits of host plant were generally characterized by large leaf Reflectance Spectrum and Leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter Functional Traits of Osmanthus content and high leaf tissue density. These findings indicate that the host plant have adopted a certain fragrans Are Related to the Parasitism trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, of Cuscuta japonica. Appl. Sci. 2021, 11, we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there 1937. https://doi.org/10.3390/ was a general trend toward the “slow investment-return” type in the global leaf economics spectrum. app11041937 Keywords: leaf reflectance spectrum; leaf functional traits; leaf economics spectrum; parasitic; Received: 1 February 2021 Accepted: 15 February 2021 Cuscuta japonica Choisy; Osmanthus fragrans Published: 23 February 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in 1. Introduction published maps and institutional affil- Parasitic plants are one of the special groups commonly existing in the global ecosys- iations. tems [1–3]. The common parasitic plants include Taxillidae, Mistletoe and Cuscutaceae [4,5]. Among them, Cuscutaceae is one of the most common parasitic plant species in China, and Cuscuta japonica Choisy is widely distributed [6]. Cuscuta japonica Choisy is seriously short of chlorophyll and other important substances to maintain its photosynthesis due to Copyright: © 2021 by the authors. the degradation of its roots and leaves [6,7]. It usually parasitizes the root and stem of the Licensee MDPI, Basel, Switzerland. host plant through its special root absorption, and relies on absorbing carbohydrates, inor- This article is an open access article ganic salts and water from the host to maintain its survival, growth and reproduction [8]. distributed under the terms and Studies have shown that the host range of Cuscuta Japonica Choisy is quite wide, and the vast conditions of the Creative Commons majority of herbaceous dicotyledonous and monotyledonous plants may become parasitic Attribution (CC BY) license (https:// objects of Cuscuta japonica Choisy. Cuscuta japonica Choisy usually grows in a winding way creativecommons.org/licenses/by/ and spreads rapidly [9–11]. Moreover, when the damage is aggravated, the whole host 4.0/). Appl. Sci. 2021, 11, 1937. https://doi.org/10.3390/app11041937 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, 1937 2 of 15 plant is often covered with the stem strips of Cuscuta japonica Choisy, causing the host plant to grow poorly and even causing the whole host plant to die [11]. Therefore, parasitic plants are one of the important factors that harm urban greening plants and threaten the urban environment seriously. Research on Cuscuta japonica Choisy parasitism mainly focuses on its own biological and ecological characteristics and its effects on photosynthetic physiology and ecosystem of parasitic objects [11–13]. For example, Beifen Yang et al. study the effects of Cuscuta japonica Choisy parasitism on the growth and reproduction of Solidago canadensis L. Sumin Guo et al. study the growth trade-off mechanism of Alternanthera philoxeroides (Mart.) Griseb. on Cuscuta japonica Choisy parasitism [14,15]. All of these indicate that the host plants often change their growth defense strategies to maintain their own survival and reproduction after being subjected to Cuscuta japonica Choisy parasitism stress. Also, many studies have shown that there are many uncertainties in the impact of parasitic plants on the biomass of the community in which they live, which are often affected by the characteristics of the communities themselves, external environment and other fac- tors [16–18]. Osmanthus fragrans Lour., one of the most common tree species in China, plays an important role in the city’s main ecological, cultural and landscape functions. However, the parasitism of Cuscuta japonica Choisy seriously hinders the normal growth of Osmanthus fragrans. Health diagnosis, monitoring and early warning of urban trees have always been a hot spot in international urban forestry research. Therefore, how to monitor and obtain the growth status and the infringed status of the damaged vegetation is the key to effectively prevent and control the infringement. In recent years, with the rapid development of hyperspectral technology, it has been widely used in forestry monitoring. Hyperspectral data has the advantages of high reso- lution, abundant information and simple data acquisition [19,20]. Different plants have different reflection spectral characteristics, and the same plant has different reflection spectral characteristics under different growth stages conditions [21,22]. Such spectral characteristics vary depending on the type of plant, the growth stage, the chlorophyll content, and the health status (whether or not it is affected by diseases, insect pests or parasitic plants) [21–24]. Plant functional traits refer to a series of internal physiological functions and external morphological characteristics gradually formed during the long- term interaction between plants and environmental factors, thus avoiding and reducing the adverse effects of the environment on them to the greatest extent [25]. In 2004, Wright et al. put forward the concept of leaf economics spectrum (LES) for the first time by analyz- ing the correlation between leaf functional traits. LES is the general internal relationship among functional traits of leaves [26,27]. Leaf functional traits can objectively reflect the influence of environmental changes on plants and the adaptability of plants to the environment [27–29]. Therefore, we speculate that leaf functional traits can also be used to diagnose the relationship between biological interactions. At the same time, spectral remote sensing technology and the change information of plant spectral characteristics can provide a reliable basis for large-scale monitoring of pests and diseases. Related researches based on forestry hyperspectral mainly focuses on plant yield, crop seed vigor, plant diseases, plant feature extraction and so on [29–34]. However, there are few studies on the response of plant leaf functional traits and leaf spectral characteristics to parasitic plant invasion. As plants are harmed by parasitic plants, they will grow badly or even die within a certain period time [31,35,36]. Therefore, how to monitor and acquire the growth status and the invasion of the damaged vegetation is the key to effectively control parasitic diseases. To fully understand the changing characteristics and laws of leaf reflectance and leaf functional traits of host plants after being parasitized, and further explore the response mechanism of leaf reflectance spectrum and plant traits to plant-parasitic stress. In this study, Osmanthus fragrans Lour., a typical greening tree species in China, was taken as the research object. Spectral reflectance characteristics and leaf functional traits of Osmanthus fragrans leaves before and after being parasitized by Cuscuta japonica Choisy and different parasitic areas were analyzed, and sensitive bands of Osmanthus fragrans response to parasitic stress were obtained. The results provide a reference for the monitoring and early Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 of 15 the research object. Spectral reflectance characteristics and leaf functional traits of Osman- thus fragrans leaves before and after being parasitized by Cuscuta japonica Choisy and dif- Appl. Sci. 2021, 11, 1937 3 of 15 ferent parasitic areas were analyzed, and sensitive bands of Osmanthus fragrans response to parasitic stress were obtained. The results provide a reference for the monitoring and early warning of the parasitism of Cuscuta japonica Choisy. At the same time, it provides a new experimental basis for different measures to control Cuscuta japonica Choisy and pro- warning of the parasitism of Cuscuta japonica Choisy. At the same time, it provides a new vides a theoretical basis for an in-depth understanding of the parasitic damage mecha- experimental basis for different measures to control Cuscuta japonica Choisy and provides a theoretical basis nism o for f an Cuscuta jap in-depth onica Choisy understanding and it of s co the ntparasitic rol stratedamage gies. mechanism of Cuscuta japonica Choisy and its control strategies. 2. Material and Methods 2. Material and Methods 2.1. Research Area and Sample Collection 2.1. Research Area and Sample Collection Nanning city is located in the southwest of Guangxi province, between 107°45′– Nanning city is located in the southwest of Guangxi province, between 107 45 – 108°51′ east longitude and 22°13′–23°32′ north latitude. It is a humid subtropical monsoon 0  0  0 108 51 east longitude and 22 13 –23 32 north latitude. It is a humid subtropical monsoon climate with abundant sunshine and rainfall all year round. The annual average temper- climate with abundant sunshine and rainfall all year round. The annual average tempera- ature is about 21.6 °C, the annual average rainfall is 1304.2 mm, and the average relative ture is about 21.6 C, the annual average rainfall is 1304.2 mm, and the average relative humidity is 79% (Quoted from https://baike.baidu.com (accessed on 15 April 2020)). The humidity is 79% (Quoted from https://baike.baidu.com (accessed on 15 April 2020)). sampling area are located on the campuses of Guangxi University, Guangxi Finance and The sampling area are located on the campuses of Guangxi University, Guangxi Finance Economics University, and Guangxi Nationalities University. The straight-line distance of and Economics University, and Guangxi Nationalities University. The straight-line distance the three sites are about 8 km, which belongs to community-based environment, ensuring of the three sites are about 8 km, which belongs to community-based environment, ensuring the relative consistency of atmosphere, planting, maintenance and management condi- the relative consistency of atmosphere, planting, maintenance and management conditions. tions. According to the proportion of the parasitic area of Cuscuta japonica Choisy to the According to the proportion of the parasitic area of Cuscuta japonica Choisy to the crown crown area of the host plant, it was divided into four parasitic degrees (CK—Without area of the host plant, it was divided into four parasitic degrees (CK—Without parasitic, parasitic, T1—Initial parasitism: less than 50%, T2—Parasitic metaphase: 50 %~80%, T3— T1—Initial parasitism: less than 50%, T2—Parasitic metaphase: 50%~80%, T3—Late para- Late parasitism: more than 80%). Healthy growing 30 Osmanthus fragrans of 15~20 years sitism: more than 80%). Healthy growing 30 Osmanthus fragrans of 15~20 years old were old were selected, and the planting location was away from the influence of tall buildings selected, and the planting location was away from the influence of tall buildings and tall and tall trees. Leaf samples were collected from 10: 00 a.m. to 12: 00 a.m. on June 2019. Ten trees. Leaf samples were collected from 10: 00 a.m. to 12: 00 a.m. on June 2019. Ten mature mature and healthy leaves were cut from each tree, placed in an icebox and immediately and healthy leaves were cut from each tree, placed in an icebox and immediately brought brought back to the laboratory for spectral determination. The time from leaf collection to back to the laboratory for spectral determination. The time from leaf collection to spectral spectral measurement was controlled within 15 min, thus ensuring the original growth measurement was controlled within 15 min, thus ensuring the original growth activity of activity of leaf samples. As shown in Figure 1, Figure 1a is a plant that is not parasitic and leaf samples. As shown in Figure 1, Figure 1a is a plant that is not parasitic and Figure 1b Figure 1b is a plant that is parasitic by Cuscuta japonica Choisy. Professor Wei Jiguang from is a plant that is parasitic by Cuscuta japonica Choisy. Professor Wei Jiguang from Agricul- Agricultural College of Guangxi University identified the plants and plant diseases in- tural College of Guangxi University identified the plants and plant diseases involved in volved in this study. this study. Figure 1. (a) Osmanthus fragrans without parasitism of Cuscuta japonica Choisy (healthy plant). (b) Osman- thus fragrans with parasitism of Cuscuta japonica Choisy. Appl. Sci. 2021, 11, x FOR PEER REVIEW 4 of 15 Figure 1. (a) Osmanthus fragrans without parasitism of Cuscuta japonica Choisy (healthy plant). (b) Osmanthus fragrans with parasitism of Cuscuta japonica Choisy. 2.2. Leaf Reflectance Spectrum Collection and Calculation Method of Leaf Functional Traits The FieldSpec3 near-infrared spectrometer (ASD, Almero, Netherlands, USA) was used to collect spectral data. The spectral band obtained by this instrument ranges from 300 nm to 2500 nm. The reflectivity curve of the final output spectrum is the average value of 10 repetitions. The flow chart of spectral measurement is shown in Figure 2. The light source is the solar light source at 12: 00–13: 00. Whiteboard is made of sintered polytetra- fluoroethylene-based material. In order to reduce human interference, instrument opera- tors wear cotton overalls. In July, 2019, 30 Osmanthus fragrans with different degrees of damage were selected at each test site, and thirty mature and healthy leaves were randomly collected from each plant during 9:00–12:00 in fine weather. The relative chlorophyll content index (CCI) was measured by CCM-200 plus chlorophyll meter (OPTI-Science, Massachusetts, USA). The instrument is recalibrated once every 15 min. Use FA/JA electronic balance (Changzhou Xingyun Electronic Equipment Co., Ltd., Changzhou, China) to weigh the fresh weight of Appl. Sci. 2021, 11, 1937 4 of 15 leaves (LFW, g). Leaf thickness (LT, mm) was measured by CD-15AX caliper rule (Mi- tutoyo, Shanghai, China). The leaf area (LA, cm ) was measured by a DS-310/360W scan- ner (Epson (China) co., ltd, Beijing, China), and then put into 9030A electric constant tem- perature air-blowing drying oven (Yiheng, Shanghai, China), the temperature was 60 °C, 2.2. Leaf Reflectance Spectrum Collection and Calculation Method of Leaf Functional Traits and the leaf dry weight (LDW, g) was weighed by FA/JA electronic balance. The FieldSpec3 near-infrared spectrometer (ASD, Almero, Netherlands, USA) was Specific leaf area (SLA, m /g) = LA/LDW (1) used to collect spectral data. The spectral band obtained by this instrument ranges from 300 nm to 2500 nm. The reflectivity curve of the final output spectrum is the average Leaf volume (LV, cm ) = LT × LA (2) value of 10 repetitions. The flow chart of spectral measurement is shown in Figure 2. The light source is the solarLeaf tissue light sour de ce at nsity 12:00–13:00. (LTD, g/cm Whiteboar ) = LDW/ d LV is made of sintered (3) polytetrafluoroethylene-based material. In order to reduce human interference, instrument Leaf dry matter content (LDMC, g/g) = LDW/LFW (4) operators wear cotton overalls. Figure 2. The operation flow of ASD spectrometer for measuring leaf surface spectrum. (a) is the operation flow of ASD Figure 2. The operation flow of ASD spectrometer for measuring leaf surface spectrum. (a) is the operation flow of ASD spectrometer. (b) is a schematic diagram of the operation of the spectrometry of the blade. spectrometer. (b) is a schematic diagram of the operation of the spectrometry of the blade. In July, 2019, 30 Osmanthus fragrans with different degrees of damage were selected As shown in Table 1, we selected 8 typical spectral characteristic parameters of plants at each test site, and thirty mature and healthy leaves were randomly collected from [37–39], including the slope of red edge (RES), the position of red edge (REP), the reflec- each plant during 9:00–12:00 in fine weather. The relative chlorophyll content index tance of red valley (RRV), the reflectance of green peak (RGP), the position of green peak (CCI) was measured by CCM-200 plus chlorophyll meter (OPTI-Science, Massachusetts, USA). The instrument is recalibrated once every 15 min. Use FA/JA electronic balance (Changzhou Xingyun Electronic Equipment Co., Ltd., Changzhou, China) to weigh the fresh weight of leaves (LFW, g). Leaf thickness (LT, mm) was measured by CD-15AX caliper rule (Mitutoyo, Shanghai, China). The leaf area (LA, cm ) was measured by a DS-310/360W scanner (Epson (China) Co., ltd, Beijing, China), and then put into 9030A electric constant temperature air-blowing drying oven (Yiheng, Shanghai, China), the temperature was 60 C, and the leaf dry weight (LDW, g) was weighed by FA/JA electronic balance. Specific leaf area (SLA, m /g) = LA/LDW (1) Leaf volume LV, cm = LT  LA (2) Leaf tissue density (LTD, g/cm ) = LDW/LV (3) Leaf dry matter content (LDMC, g/g) = LDW/LFW (4) As shown in Table 1, we selected 8 typical spectral characteristic parameters of plants [37–39], including the slope of red edge (RES), the position of red edge (REP), the reflectance of red valley (RRV), the reflectance of green peak (RGP), the position of green peak (GPP), the reflectance of water stress band (RWSB), the slope of yellow edge (YES), the position of yellow edge (YEP). Appl. Sci. 2021, 11, 1937 5 of 15 Table 1. Spectral parameters and their description. Spectral Parameter Description The maximum 1st derivative of reflectance in the red band RES (680~750 nm). The wavelength position corresponding to the maximum REP reflectance in the wavelength band 680~750 nm. RRV The minimum band reflectance in the range of 640~700 nm. RGP The maximum band reflectance in the range of 510~580 nm. The wavelength position corresponding to the green peak GPP reflectance in the wavelength band 510~580 nm. The maximum band reflectance in the range of wavelengths from RWSB 1550~1750 nm. The maximum 1st derivative of reflectance in the yellow band YES (550–582 nm). The wavelength position corresponding to the maximum YEP reflectance in the wavelength band 550~582 nm. 2.3. Data Analysis Analysis and processing of spectral data were based on ViewSpecPro 6.0 software. We use ViewSpecPro software to analyze the original spectral data and the first-order differential spectral data. Leaf functional traits data processing was based on origin2019b software and Excel 2020 software. 3. Results and Discussion 3.1. Changes in Leaf Functional Traits of Osmanthus Fragrans Leaves Parasitized by Cuscuta japonica Choisy In this study, six plant functional traits that are sensitive to environmental changes and external stress were selected, including chlorophyll content, leaf area, leaf thickness, specific leaf area, leaf dry matter content and leaf tissue density. As shown in Figure 3, there were significant differences in leaf functional traits of Osmanthus fragrans between healthy leaves and the leaves being parasitic by Cuscuta japonica Choisy. The chlorophyll content index, leaf area and specific leaf area of Osmanthus fragrans were significantly lower than those after parasitism, and these indexes gradually decreased (CK > T1 > T2 > T3) with the increase of parasitism intensity. There were significant differences between healthy leaves and parasitic leaves (chlorophyll content index, leaf area and specific leaf area) (Figure 3a,b,e). The reason for the poor growth of Osmanthus fragrans was that Cuscuta japonica plundered water and nutrients of Osmanthus fragrans [40–44]. In addition, due to the overgrowth of the parasitic plant Cuscuta japonica, the host plant lacks sufficient light. It is also an important reason for the decrease of chlorophyll content index, leaf area and specific leaf area in plants. Leaf thickness, dry matter content and leaf tissue density of Osmanthus fragrans were significantly higher than those after parasitism, and these indexes gradually increased with the increase of parasitism intensity (CK < T1 < T2 < T3) (Figure 3c,d,f). In this study, the increase of leaf dry matter content and leaf tissue density was the adjustment of Osmanthus fragrans resources after being parasitized by Cuscuta japonica. This was an ecological strategy for plants to cope with external disturbances, which aims to improve the nutrient preservation and defense ability of leaves by increasing the leaf dry matter content and leaf tissue density. Appl. Sci. 2021, 11, 1937 6 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 6 of 15 Figure 3. Changes in leaf functional traits under different parasitic intensities. Different lowercase letters indicate signifi- Figure 3. Changes in leaf functional traits under different parasitic intensities. Different lowercase letters indicate significant cant differences in parameters at the p < 0.05 level. (a) Chlorophyll content index, (b) leaf area, (c) leaf dry matter content, differences in parameters at the p < 0.05 level. (a) Chlorophyll content index, (b) leaf area, (c) leaf dry matter content, (d) leaf (d) leaf tissue density, (e) specific leaf area, (f) leaf thickness. tissue density, (e) specific leaf area, (f) leaf thickness. 3.2. Spectral Characteristics of Osmanthus Fragrans Leaves under the Different Parasitic 3.2. Spectral Characteristics of Osmanthus Fragrans Leaves under the Different Parasitic Intensity Intensity of Cuscuta japonica Choisy of Cuscuta japonica Choisy Under different parasitic intensities of Cuscuta japonica Choisy, the leaf surface spec- Under different parasitic intensities of Cuscuta japonica Choisy, the leaf surface spectral tral reflectance curves of Osmanthus fragrans were basically the same, but the spectral re- reflectance curves of Osmanthus fragrans were basically the same, but the spectral reflectance flectance values were significantly different (Figure 4). Spectral reflectance values gener- values were significantly different (Figure 4). Spectral reflectance values generally decreas- ally decreasing with the deepening of parasitic intensity, and the reflectance values were ing with the deepening of parasitic intensity, and the reflectance values were CK > T1 > T2 > CK > T1 > T2 > T3. In the visible light to near-infrared 350~1800 nm band, the spectral T3. In the visible light to near-infrared 350~1800 nm band, the spectral reflectance of Osman- reflectance of Osmanthus fragrans leaves under different parasitic intensities was the most thus fragrans leaves under different parasitic intensities was the most easily distinguished easily distinguished in the range of 750~1400 nm, which indicate that this band was the in the range of 750~1400 nm, which indicate that this band was the sensitive range of host sensit plants’ ive spectral range o response f host plto ants’ spectral r parasitic infection. esponse to p At the a same rasititime, c infethis ction. change At the same ti characterime, stic twas his ch common ange ch under aractedif rist fer ic en was t parasitic commoconditions. n under differ In addition, ent parasitic the spectral conditions. In reflectance addit curve ion, slope of Osmanthus fragrans leaves has a sharp increasing trend in the range of 700~780 nm. the spectral reflectance curve slope of Osmanthus fragrans leaves has a sharp increasing trend i In the range n the of range of 350~1800 700~7 nm,80 nm. In t the spectral he ra reflection nge of curves 350~1800 of Osmanthus nm, the spectral ref fragrans leaves lection for curves of all treatments Osmanthus fra have four grmain ans leaves fo reflection r all treatments have peaks and five main fouabsorption r main reflect valleys, ion peak and s and the positions were basically the same. The reflection peaks were located at 560 nm, 1150 nm, five main absorption valleys, and the positions were basically the same. The reflection 1300 nm and 1650 nm, and the absorption valleys were located at 350–560 nm, 600–700 nm, peaks were located at 560 nm, 1150 nm, 1300 nm and 1650 nm, and the absorption valleys 950–1050 nm, 1150~1250 nm, and 1400~1500 nm, respectively. were located at 350–560 nm, 600–700 nm, 950–1050 nm, 1150~1250 nm, and 1400~1500 nm, respectively. Chlorophyll content index of Osmanthus fragrans gradually decreased with the deep- ening of parasitism (Figure 3). Previous studies show that chlorophyll content index can better characterize the light reflection curve of plant leaves [31,45]. Therefore, the spectral reflectance curve of the parasitized Osmanthus fragrans leaves was higher than that of the non-parasitized healthy Osmanthus fragrans leaves, which may be related to the decrease of chlorophyll content index. With the deepening of parasitism, the chlorophyll content Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 of 15 index gradually decreases, so the absorption of sunlight decreases and the reflectivity in- creases [46]. Studies have shown that the phenomenon of plants increasing suddenly in this waveband belongs to the typical “red edge effect” characteristic of plants [46]. At the same time, the spectral reflectance of the leaves of the host plant (Osmanthus fragrans) with different relative chlorophyll contents has a higher reflection platform in the range of 750~1400 nm, which was wavy and may be affected by the cell structure of the leaves [46,47]. Among them, the sample with the lowest reflection coefficient was the sample with the lowest chlorophyll content index (the highest parasitic intensity). The reflectance of the sample with the highest chlorophyll content (without parasitism) was the highest Appl. Sci. 2021, 11, 1937 7 of 15 at 1150 nm, which was 0.958. There was a significant valley at 1350~1800 nm, which may be closely related to light absorption by water [48–51]. Figure 4. Spectral reflectance of healthy Osmanthus fragrans leaves and spectral reflectance of Osman- Figure 4. Spectral reflectance of healthy Osmanthus fragrans leaves and spectral reflectance of Os- thus fragrans with different parasitic degrees. manthus fragrans with different parasitic degrees. Chlorophyll content index of Osmanthus fragrans gradually decreased with the deep- 3.3. Dynamic Changes of Spectral Characteristic Parameters of Osmanthus fragrans in Different ening of parasitism (Figure 3). Previous studies show that chlorophyll content index can Parasitic Stages better characterize the light reflection curve of plant leaves [31,45]. Therefore, the spectral After first-order differentiation of the reflectance original spectral curve, the first-or- reflectance curve of the parasitized Osmanthus fragrans leaves was higher than that of the der differential reflection coefficients under different parasitic intensities were obtained non-parasitized healthy Osmanthus fragrans leaves, which may be related to the decrease (Figure 5). We calculated eight typical spectral parameters under different parasitic inten- of chlorophyll content index. With the deepening of parasitism, the chlorophyll content sities (Figure 6), and the parameter description was shown in Table 1. After Osmanthus index gradually decreases, so the absorption of sunlight decreases and the reflectivity fragrans was parasitized by Cuscuta japonica Choisy, there was an obvious “blue shift” in increases [46]. Studies have shown that the phenomenon of plants increasing suddenly the red edge of its leaf surface spectral curve (Figures 5 and 6a). With the deepening of in this waveband belongs to the typical “red edge effect” characteristic of plants [46]. parasitic intensity, the degree of “blue shift” also increased, indicating that with the in- At the same time, the spectral reflectance of the leaves of the host plant (Osmanthus fra- crea grans se of pa ) with rasi differ tic i ent ntensi relative ty, the chlor inflophyll uence on contents the red has edge o a higher f the r le eflection af surface platform became more in the severe. In addition, the slope of the red edge of the host plant decreased obviously after range of 750~1400 nm, which was wavy and may be affected by the cell structure of the pa leaves rasitiza [46 ti ,47 on wi ]. Among th CK (0 them, .01557the ) > T1 (0 sample .0152 with 4) > T2 the (0 lowest .01469)r eflection > T3 (0.0136 coef 8)ficient (Figures was 5 athe nd 6b). sample Many with stu the dies lowest show that the red chlorophyll edg content e slope h indexa(the s a good in highest dic parasitic ation of chloroph intensity).yll con- The re- flectance of the sample with the highest chlorophyll content (without parasitism) was the tent [52]. Combined with Figure 3, with the deepening of parasitic intensity, chlorophyll highest at 1150 nm, which was 0.958. There was a significant valley at 1350~1800 nm, content index is decreasing. Therefore, we suspect that the cause of this phenomenon was which may be closely related to light absorption by water [48–51]. related to the influence of Cuscuta japonica Choisy on the photosynthesis of host plants. As can be seen from Figures 5 and 6c, with the deepening of parasitic intensity, the spectral 3.3. Dynamic Changes of Spectral Characteristic Parameters of Osmanthus fragrans in Different Parasitic Stages After first-order differentiation of the reflectance original spectral curve, the first- order differential reflection coefficients under different parasitic intensities were obtained (Figure 5). We calculated eight typical spectral parameters under different parasitic inten- sities (Figure 6), and the parameter description was shown in Table 1. After Osmanthus fragrans was parasitized by Cuscuta japonica Choisy, there was an obvious “blue shift” in the red edge of its leaf surface spectral curve (Figures 5 and 6a). With the deepening of parasitic intensity, the degree of “blue shift” also increased, indicating that with the increase of parasitic intensity, the influence on the red edge of the leaf surface became more severe. In addition, the slope of the red edge of the host plant decreased obvi- ously after parasitization with CK (0.01557) > T1 (0.01524) > T2 (0.01469) > T3 (0.01368) Appl. Sci. 2021, 11, 1937 8 of 15 (Figures 5 and 6b). Many studies show that the red edge slope has a good indication of Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 of 15 chlorophyll content [52]. Combined with Figure 3, with the deepening of parasitic intensity, chlorophyll content index is decreasing. Therefore, we suspect that the cause of this phe- nomenon was related to the influence of Cuscuta japonica Choisy on the photosynthesis of host plants. As can be seen from Figures 5 and 6c, with the deepening of parasitic intensity, red valley reflectance of host plants Table 1 shows a trend of increasing at first and then the spectral red valley reflectance of host plants Table 1 shows a trend of increasing at first decreasing (T1 (0.07912) > T2 (0.07153) > CK (0.0672) > T3 (0.0298)). In the initial stage of and then decreasing (T1 (0.07912) > T2 (0.07153) > CK (0.0672) > T3 (0.0298)). In the initial parasitism, due to the shielding of parasitic plants, the sun burns the leaves of host plants stage of parasitism, due to the shielding of parasitic plants, the sun burns the leaves of less, and the spectral reflectance tends to increase. However, in the middle and late stage host plants less, and the spectral reflectance tends to increase. However, in the middle of parasitism, the nutrient deficiency of the host plant leaves led to the weakening of sun- and late stage of parasitism, the nutrient deficiency of the host plant leaves led to the light reflection in this band [51,52]. Under different parasitic conditions, the position of weakening of sunlight reflection in this band [51,52]. Under different parasitic conditions, the yellow edge is not affected, and it is all at 570 nm (Figures 5 and 6g). With the deep- the position of the yellow edge is not affected, and it is all at 570 nm (Figures 5 and 6g). ening of parasitic intensity, the slope of the yellow edge (CK (−0.00143) > T1 (−0.00213) > With the deepening of parasitic intensity, the slope of the yellow edge (CK (0.00143) > T2 (−0.00249) >T3 (−0.00264)) and the reflectivity of the green peak (CK (0.0017), T1 T1 (0.00213) > T2 (0.00249) >T3 (0.00264)) and the reflectivity of the green peak (CK (0.0028), T2 (0.0039) and T3 (0.0043)) gradually decreases (Figures 5 and 6h,d). The posi- (0.0017), T1 (0.0028), T2 (0.0039) and T3 (0.0043)) gradually decreases (Figures 5 and 6h,d). tion of the green peak presents shifts to long wave direction (CK (519), T1(519), T2(520), The position of the green peak presents shifts to long wave direction (CK (519), T1(519), T3(522)) (Figures 5 and 6e). At this time, the reflectivity of the water stress wave band T2(520), T3(522)) (Figures 5 and 6e). At this time, the reflectivity of the water stress wave (Figures 4 and 6f) decreases gradually with CK (0.5425) > T1 (0.5182) > T2 (0.4938) > T3 band (Figures 4 and 6f) decreases gradually with CK (0.5425) > T1 (0.5182) > T2 (0.4938) > (0.3483). Studies have shown that the spectral reflectance of vegetation in the range of T3 (0.3483). Studies have shown that the spectral reflectance of vegetation in the range of 1550~1750 nm is usually closely related to the cell structure and water content of plants, 1550~1750 nm is usually closely related to the cell structure and water content of plants, which indicate the water absorption characteristics [53]. Therefore, with the deepening of which indicate the water absorption characteristics [53]. Therefore, with the deepening of the invasion degree of Cuscuta japonica Choisy, the cell structure of the leaves suffers cer- the invasion degree of Cuscuta japonica Choisy, the cell structure of the leaves suffers certain tain damage. This is basically consistent with the research results of Xu et al. on pine wood damage. This is basically consistent with the research results of Xu et al. on pine wood nematode infecting Pinus needles [54]. nematode infecting Pinus needles [54]. Figure 5. The first derivative spectral curves of the Osmanthus fragrans leaves. Figure 5. The first derivative spectral curves of the Osmanthus fragrans leaves. Appl. Sci. 2021, 11, 1937 9 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 15 Figure 6. Dynamic trend of spectral parameters in different parasitism period. (a–h) respectively represents the position Figure 6. Dynamic trend of spectral parameters in different parasitism period. (a–h) respectively represents the position of red edge (REP), the slope of red edge (RES), the reflectance of red valley (RRV), the reflectance of green peak (RGP), of red edge (REP), the slope of red edge (RES), the reflectance of red valley (RRV), the reflectance of green peak (RGP), the the position of green peak (GPP), the reflection of water stress band (RWSB), the position of yellow edge (YEP), and the position of green peak (GPP), the reflection of water stress band (RWSB), the position of yellow edge (YEP), and the slope yellow edge slope yellow (Y edge ES) under (YES) under differe dif nt parasitic intensities. ferent parasitic intensities. 3.4. Correlation between Chlorophyll Content and Spectral Characteristic Parameters of Host 3.4. Correlation between Chlorophyll Content and Spectral Characteristic Parameters of Host Plants with Different Parasitic Degree of Cuscuta japonica Choisy Plants with Different Parasitic Degree of Cuscuta japonica Choisy As shown in Figure 3, CCI of the host plant (Osmanthus fragrans) gradually decreased As shown in Figure 3, CCI of the host plant (Osmanthus fragrans) gradually decreased with the deepening of the parasitic intensity of Cuscuta japonica Choisy. Previous studies with the deepening of the parasitic intensity of Cuscuta japonica Choisy. Previous studies generally believed that chlorophyll was an important parameter to determine the char- generally believed that chlorophyll was an important parameter to determine the charac- acteristics of spectral reflectance curve of plant [55]. When the vegetation is in a healthy teristics of spectral reflectance curve of plant [55]. When the vegetation is in a healthy growth state and the chlorophyll content is high, the position of the red edge moves to- growth state and the chlorophyll content is high, the position of the red edge moves to- wards the long wave direction [55,56]. However, when vegetation is stressed by external wards the long wave direction [55,56]. However, when vegetation is stressed by external environmental, such as drought stress, high temperature stress or insert damage, the red environmental, such as drought stress, high temperature stress or insert damage, the red edge position tends to the short-wave direction [57]. Pearson correlation analysis was used edge position tends to the short-wave direction [57]. Pearson correlation analysis was to analyze the correlation between spectral parameters and plant functional traits (Table 2), used to analyze the correlation between spectral parameters and plant functional traits and the correlation analysis in Table 2 was based on all the collected sample data, including (Table 2), and the correlation analysis in Table 2 was based on all the collected sample four parasitic samples. It can be seen that there was an extremely significant correlation data, including four parasitic samples. It can be seen that there was an extremely signifi- between spectral parameters and CCI. There was a significant correlation between RES cant correlation between spectral parameters and CCI. There was a significant correlation and LT. RRV, RGP, RES, RWSB and CCI were have high correlation. In order to further between RES and LT. RRV, RGP, RES, RWSB and CCI were have high correlation. In order explore the correlation between spectral parameters and plant functional traits, according to further explore the correlation between spectral parameters and plant functional traits, to the correlation results in Table 2, the linear correlation analysis was carried out on the according to the correlation results in Table 2, the linear correlation analysis was carried indicators that achieved significant correlation (Figure 7). Figure 7 showed the correlation out on the indicators that achieved significant correlation (Figure 7). Figure 7 showed the between different spectral parameters with CCI and LT. The results of correlation analysis correlation between different spectral parameters with CCI and LT. The results of corre- between plant functional traits and spectral parameters show that they show different lation analysis between plant functional traits and spectral parameters show that they correlations. The reflectance of red valley has the greatest correlation with chlorophyll show different correlations. The reflectance of red valley has the greatest correlation with content (y = 65913.323x + 9.783, R = 0.6888), which indicate that red edge characteristics chlorophyl were very l c sensitive ontent (y to = parasitic −65913.323 infestation x + 9.783and , R = can 0.6888), wh be used to ich characteri indicate th zeat changes red edge in Appl. Appl. Sci. Sci. 2021 2021, , 11 11, x FO , 1937R PEER REVIEW 10 of 10 of 15 15 characteristics were very sensitive to parasitic infestation and can be used to characterize chlorophyll content of Osmanthus fragrans under different parasitic degrees. According to changes in chlorophyll content of Osmanthus fragrans under different parasitic degrees. the results in Figure 7, the spectral parameter model with the highest accuracy was selected. According to the results in Figure 7, the spectral parameter model with the highest accu- Then, a prediction model is established with the most sensitive spectral parameters as inde- racy was selected. Then, a prediction model is established with the most sensitive spectral pendent variables and chlorophyll content as dependent variable. Finally, the accuracy of parameters as independent variables and chlorophyll content as dependent variable. Fi- the model was further verified by analyzing the predicted and measured values calculated nally, the accuracy of the model was further verified by analyzing the predicted and meas- by the linear regression model (Figure 8). As shown in Figure 8, the chlorophyll inversion ured values calculated by the linear regression model (Figure 8). As shown in Figure 8, model of red valley reflectance was tested, and it was found that the prediction accuracy of the chlorophyll inversion model of red valley reflectance was tested, and it was found that this model was high and stable (R = 0.8811, RMSE = 0.0004). the prediction accuracy of this model was high and stable (R = 0.8811, RMSE = 0.0004). Table 2. Pearson correlation analysis between plant traits and spectral parameters. * indicates that the Table 2. Pearson correlation analysis between plant traits and spectral parameters. * indicates that correlation reaches a significant level at the level of p < 0.05. and ** indicates a significant correlation the correlation reaches a significant level at the level of p < 0.05. and ** indicates a significant corre- reaches a significant level at the level of p < 0.01. lation reaches a significant level at the level of p < 0.01. RRV RGP RES RWSB RRV RGP RES RWSB LT 0.25218 0.1787 0.28318 * 0.09577 LT 0.25218 −0.1787 −0.28318 * 0.09577 LA 0.01651 0.18462 0.14292 0.0353 LA −0.01651 0.18462 −0.14292 0.0353 LDMC 0.01136 0.00523 0.03048 0.09512 LDMC 0.01136 −0.00523 0.03048 0.09512 SLA 0.20281 0.24112 0.06407 0.0641 SLA 0.20281 −0.24112 −0.06407 0.0641 LTD 0.19553 0.17124 0.13662 0.01367 LTD −0.19553 0.17124 0.13662 −0.01367 CCI 0.82993 ** 0.72953 ** 0.65295 ** 0.56967 ** CCI −0.82993 ** 0.72953 ** 0.65295 ** −0.56967 ** Figure 7. Linear correlation between functional traits and spectral parameters. (a) the reflection of red valley (RRV) and Figure 7. Linear correlation between functional traits and spectral parameters. (a) the reflection of red valley (RRV) and CCI, (b) the reflectance of green peak (RGP) and CCI, (c) the slope of red edge (RES) and CCI, (d) the reflection of water CCI, (b) the reflectance of green peak (RGP) and CCI, (c) the slope of red edge (RES) and CCI, (d) the reflection of water stress band (RWSB) and CCI, (e) the reflectance of green peak (RGP) and LT. stress band (RWSB) and CCI, (e) the reflectance of green peak (RGP) and LT. Appl. Sci. 2021, 11, 1937 11 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 11 of 15 Figure 8. Test of chlorophyll inversion model based on red valley reflectance. Figure 8. Test of chlorophyll inversion model based on red valley reflectance. 3.5. Effects of Parasitic Plants on the Correlation of Functional Traits of Osmanthus fragrans and 3.5. Effects of Parasitic Plants on the Correlation of Functional Traits of Osmanthus fragrans Analysis of Leaf Economics Spectrum and Analysis of Leaf Economics Spectrum There was an interdependent relationship between the functional traits of the leaves There was an interdependent relationship between the functional traits of the leaves (Table 3). There was a significant positive correlation between LA and SLA. There was a (Table 3). There was a significant positive correlation between LA and SLA. There was a significant negative correlation between SLA and LDMC and LTD. LA was significantly significant negative correlation between SLA and LDMC and LTD. LA was significantly negatively correlated with LDMC and LTD. There was a significant negative correlation negatively correlated with LDMC and LTD. There was a significant negative correlation between LT and LTD. There was a very significant positive correlation between LDMC between LT and LTD. There was a very significant positive correlation between LDMC and LTD. There was a significant positive correlation between CCI and SLA. At the same and LTD. There was a significant positive correlation between CCI and SLA. At the same time, LT has a negative correlation with SLA and LA, but the correlation has not reached a time, LT has a negative correlation with SLA and LA, but the correlation has not reached significant level. a significant level. Table 3. Correlation between plant functional traits indicators. * indicates a significant correlation Table 3. Correlation between plant functional traits indicators. * indicates a significant correlation between functional traits at the level of p < 0.05, and ** indicates a significant correlation between between functional traits at the level of p < 0.05, and ** indicates a significant correlation between functional traits at the level of p < 0.01. functional traits at the level of p < 0.01. LT LA SLA LDMC LTD CCI LT LA SLA LDMC LTD CCI LT 1 LT 1 LA 0.1696 1 LA −0.1696 1 SLA 0.1502 0.3581 * 1 SLA −0.1502 0.3581 * 1 LDMC 0.1293 0.4246 * 0.6991 ** 1 LDMC −0.1293 −0.4246 * −0.6991 ** 1 LTD 0.5436 ** 0.4218 * 0.5950 ** 0.7517 ** 1 LTD −0.5436 ** −0.4218 * −0.5950 ** 0.7517 ** 1 CCI 0.2566 0.2623 0.4993 * 0.2201 0.4456 * 1 CCI 0.2566 0.2623 0.4993 * −0.2201 −0.4456 * 1 Studies have shown that leaf functional traits can reflect the adaptability of plants to Studies have shown that leaf functional traits can reflect the adaptability of plants to the environment, but compared with a single leaf functional trait, continuous leaf economics the environment, but compared with a single leaf functional trait, continuous leaf eco- spectrum can better reflect the growth strategy and adaptation mechanism of plants [54,55]. nomics spectrum can better reflect the growth strategy and adaptation mechanism of In this study, there was an obvious trade-off relationship between the functional traits of plants [54,55]. In this study, there was an obvious trade-off relationship between the func- plant leaves, which indicate that when plants are harmed by parasitic plants, host plants tional traits of plant leaves, which indicate that when plants are harmed by parasitic show certain ecological trade-off strategies in terms of functional traits for survival. SLA is plants, host plants show certain ecological trade-off strategies in terms of functional traits closely related to the growth and survival strategy of plants, which can represent the for survival. SLA is closely related to the growth and survival strategy of plants, which adaptability of plants to the environment and the ability to obtain resources [58]. In this can represent the adaptability of plants to the environment and the ability to obtain re- study, after being invaded by parasitic plants, the reduction of SLA of the host plants makes sources [58]. In this study, after being invaded by parasitic plants, the reduction of SLA of the plants adapt to resource-poor environment. LDMC represents the plants to maintain the host plants makes the plants adapt to resource-poor environment. LDMC represents water and nutrients (cellulose, protein and Nitrogen content, etc), while LTD reflects the plants to maintain water and nutrients (cellulose, protein and Nitrogen content, etc), the bearing capacity and defense ability of plant leaves, which is closely related to the while LTD reflects the bearing capacity and defense ability of plant leaves, which is closely turnover growth rate of leaves [59–61]. In this study, LDMC and LTD gradually increased with the increase of parasitic intensity, and showed a very significant positive correlation. Appl. Sci. 2021, 11, x FOR PEER REVIEW 12 of 15 Appl. Sci. 2021, 11, 1937 12 of 15 related to the turnover growth rate of leaves [59–61]. In this study, LDMC and LTD grad- ually increased with the increase of parasitic intensity, and showed a very significant pos- itive correlation. This indicated that the host plant can improve the nutrient retention abil- This indicated that the host plant can improve the nutrient retention ability of leaves under ity of leaves under the adverse environment of parasitic stress, and thus making more the adverse environment of parasitic stress, and thus making more effective use of limited effective use of limited resources [58,60]. The increase of LTD was beneficial to strengthen resources [58,60]. The increase of LTD was beneficial to strengthen the defense ability of the defense ability of plant against biological factors [61]. To sum up, after being parasi- plant against biological factors [61]. To sum up, after being parasitized, the leaf functional tized, the leaf functional traits of the host plant were generally characterized by large leaf traits of the host plant were generally characterized by large leaf thickness, small leaf area, thickness, small leaf area, small specific leaf area, low chlorophyll content index, high dry small specific leaf area, low chlorophyll content index, high dry matter content and high matter content and high leaf tissue density. Therefore, we suspect that the leaf economics leaf tissue density. Therefore, we suspect that the leaf economics spectrum may also exist in spectrum may also exist in the parasitic environment, and there was a general trend to- the parasitic environment, and there was a general trend toward “slow investment-return” ward “slow investment-return” type in the global leaf economics spectrum (Figure 9). type in the global leaf economics spectrum (Figure 9). Figure 9. Conceptual illustration of leaf economics spectrum [36,62]. Figure 9. Conceptual illustration of leaf economics spectrum [36,62]. 4. Conclusions 4. Conclusions In this paper, we studied the spectral characteristics and leaf functional traits of Osman- In this paper, we studi thus fragrans in ed the spectra different parasitic l charaperiods cteristicafter s and l Cuscuta eaf functiona japonica l tra Choisy its of infection, Os- revealing manthus fragran the s in relatio differe nship nt parasitic between periods after the spectral characteristic Cuscuta japonic changes a Choisyand infec invasive tion, re-processes after vealing the relhost ationshi susceptibility p between the spectra . In addition, by l ch establishing aracteristic ch a corr anelation ges and inv between asivspectral e pro- characteristic parameters and chlorophyll content, the research results can provide theoretical support cesses after host susceptibility. In addition, by establishing a correlation between spectral for the prediction of plant diseases in the early stage. At the same time, it can provide a characteristic parameters and chlorophyll content, the research results can provide theo- reference for monitoring and early warning of infringement, and a new experimental basis retical support for the prediction of plant diseases in the early stage. At the same time, it for different measures to control Cuscuta japonica Choisy. Main conclusions are as follows. can provide a reference for monitoring and early warning of infringement, and a new experimental basis for different measures to control Cuscuta japonica Choisy. Main conclu- (1) The spectral reflectance was generally higher before parasitism than after parasitism. sions are as follows. There were four main reflection peaks and five main absorption valleys in the spectral (1) The spectral reflectance was generally higher before parasitism than after parasit- reflection curve (350~1800 nm). The near-infrared band (750~1400 nm) was the ism. There were four main reflection peaks and five main absorption valleys in the spec- sensitive range of spectral response of host plants to parasitic infection. At the tral reflection curve (350~1800 nm). The near-infrared band (750~1400 nm) was the sensi- same time, such variation characteristics were universal under different parasitic tive range of spectral response of host plants to parasitic infection. At the same time, such degree conditions. variation characteristics were universal under different parasitic degree conditions. (2) The position of red edge, slope of red edge, reflectance of a green peak, and reflectance (2) The position of red edge, slope of red edge, reflectance of a green peak, and re- of water stress band can well reflect the invasion status in different parasitic stages. flectance of water stress band can well reflect the invasion status in different parasitic After parasitism, the red edge position of the host plant spectrum shifted to shortwave stages. After parasitism, the red edge position of the host plant spectrum shifted to direction. With the deepening of parasitic intensity, the moving distance of the red shortwave direction. With the deepening of parasitic intensity, the moving distance of the edge position to the short-wave direction increases. red edge position to the short-wave direction increases. (3) With the increase of parasitic intensity, the relative content of chlorophyll in host plants gradually decreases, and the spectral characteristic parameters were significantly Appl. Sci. 2021, 11, 1937 13 of 15 correlated with them. Chlorophyll inversion model based on red valley reflectance has the highest accuracy (y = 65913.323x + 9.783, R = 0.6888). (4) After parasitism, the leaf functional traits of host plant were characterized by large leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter content, and high leaf tissue density. We suspect that there may be leaf economics spectrum (“slow investment-return”) in the parasitic environment. Author Contributions: J.Z. conceived and designed the study. J.Z. and X.Z. contributed to materials and tools. J.Z., J.Y. and Q.X. performed the experiments. Q.X., J.Y., X.Z. and C.X. contributed to literature collection. J.Z. contributed to data analysis. J.Z. contributed to paper preparation, writing and revision. All the authors read and approved it for publication. All authors have read and agreed to the published version of the manuscript. Funding: This study was funded by “the Fundamental Research Funds for the Central Universities (NO. BLX201704)”, “National Natural Science Foundation of China (NSFC project NO. 31901277)” and “Integration and Demonstration of Key Technologies for Oriented Tending of Plain Ecological Forest in Chaoyang District (CYSF-1904)”. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data involved in the article were all shown in the figures and tables. However, there are still available from the first author on reasonable request. Acknowledgments: Research was conducted in Guangxi University. We thank the Forestry College of Guangxi University and the Agricultural College of Guangxi University for providing us with necessary experimental platforms and instruments. The English in this document has been checked by at least two professional editors; both were native speakers of English. We thank Jiguang Wei from the College of Agriculture of Guangxi University for identifying the plant species used in this study (Identification information refers to Flora of China). Conflicts of Interest: The authors declare that they have no competing interest. Ethics Approval and Consent to Participate: This experiment does not involve human experiments and animal experiments. The field trial experiments in the current study were permitted by the local government in China (Guangxi University and Guangxi Finance and Economics University), including the collection of leaf samples. 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The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica

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applied sciences Article The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica 1 1 2 1 , 1 , Jiyou Zhu , Qing Xu , Jiangming Yao , Xinna Zhang * and Chengyang Xu * Research Center for Urban Forestry, Key Laboratory for Forest Silviculture and Conservation of Ministry of Education, Key Laboratory for Silviculture and Forest Ecosystem Research in Arid- and Semi-arid Region of State Forestry Administration, Beijing Forestry University, Beijing 100083, China; joezhu1205@gmail.com (J.Z.); qingzi050656@163.com (Q.X.) College of Forestry, Guangxi University, Nanning 530005, China; jiangming618@gmail.com * Correspondence: zhangxinna0513@163.com (X.Z.); cyxu@bjfu.edu.cn (C.X.); Tel.: +86-010-6233-7082 (C.X.) Abstract: Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results showed that the spectral reflectance was higher than those being parasitized in the visible and near-infrared range. The spectral reflectance in 750~1400 nm was the sensitive range of spectral response of host plant to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y = 65913.323x + 9.783, R = 0.6888) based on the reflectance of red valley, which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral parameters and chlorophyll content index. Through the change of spectral parameters, Citation: Zhu, J.; Xu, Q.; Yao, J.; we can predict the chlorophyll content of Osmanthus fragrans under different parasitic degrees. After Zhang, X.; Xu, C. The Changes of Leaf being parasitized, the leaf functional traits of host plant were generally characterized by large leaf Reflectance Spectrum and Leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter Functional Traits of Osmanthus content and high leaf tissue density. These findings indicate that the host plant have adopted a certain fragrans Are Related to the Parasitism trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, of Cuscuta japonica. Appl. Sci. 2021, 11, we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there 1937. https://doi.org/10.3390/ was a general trend toward the “slow investment-return” type in the global leaf economics spectrum. app11041937 Keywords: leaf reflectance spectrum; leaf functional traits; leaf economics spectrum; parasitic; Received: 1 February 2021 Accepted: 15 February 2021 Cuscuta japonica Choisy; Osmanthus fragrans Published: 23 February 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in 1. Introduction published maps and institutional affil- Parasitic plants are one of the special groups commonly existing in the global ecosys- iations. tems [1–3]. The common parasitic plants include Taxillidae, Mistletoe and Cuscutaceae [4,5]. Among them, Cuscutaceae is one of the most common parasitic plant species in China, and Cuscuta japonica Choisy is widely distributed [6]. Cuscuta japonica Choisy is seriously short of chlorophyll and other important substances to maintain its photosynthesis due to Copyright: © 2021 by the authors. the degradation of its roots and leaves [6,7]. It usually parasitizes the root and stem of the Licensee MDPI, Basel, Switzerland. host plant through its special root absorption, and relies on absorbing carbohydrates, inor- This article is an open access article ganic salts and water from the host to maintain its survival, growth and reproduction [8]. distributed under the terms and Studies have shown that the host range of Cuscuta Japonica Choisy is quite wide, and the vast conditions of the Creative Commons majority of herbaceous dicotyledonous and monotyledonous plants may become parasitic Attribution (CC BY) license (https:// objects of Cuscuta japonica Choisy. Cuscuta japonica Choisy usually grows in a winding way creativecommons.org/licenses/by/ and spreads rapidly [9–11]. Moreover, when the damage is aggravated, the whole host 4.0/). Appl. Sci. 2021, 11, 1937. https://doi.org/10.3390/app11041937 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, 1937 2 of 15 plant is often covered with the stem strips of Cuscuta japonica Choisy, causing the host plant to grow poorly and even causing the whole host plant to die [11]. Therefore, parasitic plants are one of the important factors that harm urban greening plants and threaten the urban environment seriously. Research on Cuscuta japonica Choisy parasitism mainly focuses on its own biological and ecological characteristics and its effects on photosynthetic physiology and ecosystem of parasitic objects [11–13]. For example, Beifen Yang et al. study the effects of Cuscuta japonica Choisy parasitism on the growth and reproduction of Solidago canadensis L. Sumin Guo et al. study the growth trade-off mechanism of Alternanthera philoxeroides (Mart.) Griseb. on Cuscuta japonica Choisy parasitism [14,15]. All of these indicate that the host plants often change their growth defense strategies to maintain their own survival and reproduction after being subjected to Cuscuta japonica Choisy parasitism stress. Also, many studies have shown that there are many uncertainties in the impact of parasitic plants on the biomass of the community in which they live, which are often affected by the characteristics of the communities themselves, external environment and other fac- tors [16–18]. Osmanthus fragrans Lour., one of the most common tree species in China, plays an important role in the city’s main ecological, cultural and landscape functions. However, the parasitism of Cuscuta japonica Choisy seriously hinders the normal growth of Osmanthus fragrans. Health diagnosis, monitoring and early warning of urban trees have always been a hot spot in international urban forestry research. Therefore, how to monitor and obtain the growth status and the infringed status of the damaged vegetation is the key to effectively prevent and control the infringement. In recent years, with the rapid development of hyperspectral technology, it has been widely used in forestry monitoring. Hyperspectral data has the advantages of high reso- lution, abundant information and simple data acquisition [19,20]. Different plants have different reflection spectral characteristics, and the same plant has different reflection spectral characteristics under different growth stages conditions [21,22]. Such spectral characteristics vary depending on the type of plant, the growth stage, the chlorophyll content, and the health status (whether or not it is affected by diseases, insect pests or parasitic plants) [21–24]. Plant functional traits refer to a series of internal physiological functions and external morphological characteristics gradually formed during the long- term interaction between plants and environmental factors, thus avoiding and reducing the adverse effects of the environment on them to the greatest extent [25]. In 2004, Wright et al. put forward the concept of leaf economics spectrum (LES) for the first time by analyz- ing the correlation between leaf functional traits. LES is the general internal relationship among functional traits of leaves [26,27]. Leaf functional traits can objectively reflect the influence of environmental changes on plants and the adaptability of plants to the environment [27–29]. Therefore, we speculate that leaf functional traits can also be used to diagnose the relationship between biological interactions. At the same time, spectral remote sensing technology and the change information of plant spectral characteristics can provide a reliable basis for large-scale monitoring of pests and diseases. Related researches based on forestry hyperspectral mainly focuses on plant yield, crop seed vigor, plant diseases, plant feature extraction and so on [29–34]. However, there are few studies on the response of plant leaf functional traits and leaf spectral characteristics to parasitic plant invasion. As plants are harmed by parasitic plants, they will grow badly or even die within a certain period time [31,35,36]. Therefore, how to monitor and acquire the growth status and the invasion of the damaged vegetation is the key to effectively control parasitic diseases. To fully understand the changing characteristics and laws of leaf reflectance and leaf functional traits of host plants after being parasitized, and further explore the response mechanism of leaf reflectance spectrum and plant traits to plant-parasitic stress. In this study, Osmanthus fragrans Lour., a typical greening tree species in China, was taken as the research object. Spectral reflectance characteristics and leaf functional traits of Osmanthus fragrans leaves before and after being parasitized by Cuscuta japonica Choisy and different parasitic areas were analyzed, and sensitive bands of Osmanthus fragrans response to parasitic stress were obtained. The results provide a reference for the monitoring and early Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 of 15 the research object. Spectral reflectance characteristics and leaf functional traits of Osman- thus fragrans leaves before and after being parasitized by Cuscuta japonica Choisy and dif- Appl. Sci. 2021, 11, 1937 3 of 15 ferent parasitic areas were analyzed, and sensitive bands of Osmanthus fragrans response to parasitic stress were obtained. The results provide a reference for the monitoring and early warning of the parasitism of Cuscuta japonica Choisy. At the same time, it provides a new experimental basis for different measures to control Cuscuta japonica Choisy and pro- warning of the parasitism of Cuscuta japonica Choisy. At the same time, it provides a new vides a theoretical basis for an in-depth understanding of the parasitic damage mecha- experimental basis for different measures to control Cuscuta japonica Choisy and provides a theoretical basis nism o for f an Cuscuta jap in-depth onica Choisy understanding and it of s co the ntparasitic rol stratedamage gies. mechanism of Cuscuta japonica Choisy and its control strategies. 2. Material and Methods 2. Material and Methods 2.1. Research Area and Sample Collection 2.1. Research Area and Sample Collection Nanning city is located in the southwest of Guangxi province, between 107°45′– Nanning city is located in the southwest of Guangxi province, between 107 45 – 108°51′ east longitude and 22°13′–23°32′ north latitude. It is a humid subtropical monsoon 0  0  0 108 51 east longitude and 22 13 –23 32 north latitude. It is a humid subtropical monsoon climate with abundant sunshine and rainfall all year round. The annual average temper- climate with abundant sunshine and rainfall all year round. The annual average tempera- ature is about 21.6 °C, the annual average rainfall is 1304.2 mm, and the average relative ture is about 21.6 C, the annual average rainfall is 1304.2 mm, and the average relative humidity is 79% (Quoted from https://baike.baidu.com (accessed on 15 April 2020)). The humidity is 79% (Quoted from https://baike.baidu.com (accessed on 15 April 2020)). sampling area are located on the campuses of Guangxi University, Guangxi Finance and The sampling area are located on the campuses of Guangxi University, Guangxi Finance Economics University, and Guangxi Nationalities University. The straight-line distance of and Economics University, and Guangxi Nationalities University. The straight-line distance the three sites are about 8 km, which belongs to community-based environment, ensuring of the three sites are about 8 km, which belongs to community-based environment, ensuring the relative consistency of atmosphere, planting, maintenance and management condi- the relative consistency of atmosphere, planting, maintenance and management conditions. tions. According to the proportion of the parasitic area of Cuscuta japonica Choisy to the According to the proportion of the parasitic area of Cuscuta japonica Choisy to the crown crown area of the host plant, it was divided into four parasitic degrees (CK—Without area of the host plant, it was divided into four parasitic degrees (CK—Without parasitic, parasitic, T1—Initial parasitism: less than 50%, T2—Parasitic metaphase: 50 %~80%, T3— T1—Initial parasitism: less than 50%, T2—Parasitic metaphase: 50%~80%, T3—Late para- Late parasitism: more than 80%). Healthy growing 30 Osmanthus fragrans of 15~20 years sitism: more than 80%). Healthy growing 30 Osmanthus fragrans of 15~20 years old were old were selected, and the planting location was away from the influence of tall buildings selected, and the planting location was away from the influence of tall buildings and tall and tall trees. Leaf samples were collected from 10: 00 a.m. to 12: 00 a.m. on June 2019. Ten trees. Leaf samples were collected from 10: 00 a.m. to 12: 00 a.m. on June 2019. Ten mature mature and healthy leaves were cut from each tree, placed in an icebox and immediately and healthy leaves were cut from each tree, placed in an icebox and immediately brought brought back to the laboratory for spectral determination. The time from leaf collection to back to the laboratory for spectral determination. The time from leaf collection to spectral spectral measurement was controlled within 15 min, thus ensuring the original growth measurement was controlled within 15 min, thus ensuring the original growth activity of activity of leaf samples. As shown in Figure 1, Figure 1a is a plant that is not parasitic and leaf samples. As shown in Figure 1, Figure 1a is a plant that is not parasitic and Figure 1b Figure 1b is a plant that is parasitic by Cuscuta japonica Choisy. Professor Wei Jiguang from is a plant that is parasitic by Cuscuta japonica Choisy. Professor Wei Jiguang from Agricul- Agricultural College of Guangxi University identified the plants and plant diseases in- tural College of Guangxi University identified the plants and plant diseases involved in volved in this study. this study. Figure 1. (a) Osmanthus fragrans without parasitism of Cuscuta japonica Choisy (healthy plant). (b) Osman- thus fragrans with parasitism of Cuscuta japonica Choisy. Appl. Sci. 2021, 11, x FOR PEER REVIEW 4 of 15 Figure 1. (a) Osmanthus fragrans without parasitism of Cuscuta japonica Choisy (healthy plant). (b) Osmanthus fragrans with parasitism of Cuscuta japonica Choisy. 2.2. Leaf Reflectance Spectrum Collection and Calculation Method of Leaf Functional Traits The FieldSpec3 near-infrared spectrometer (ASD, Almero, Netherlands, USA) was used to collect spectral data. The spectral band obtained by this instrument ranges from 300 nm to 2500 nm. The reflectivity curve of the final output spectrum is the average value of 10 repetitions. The flow chart of spectral measurement is shown in Figure 2. The light source is the solar light source at 12: 00–13: 00. Whiteboard is made of sintered polytetra- fluoroethylene-based material. In order to reduce human interference, instrument opera- tors wear cotton overalls. In July, 2019, 30 Osmanthus fragrans with different degrees of damage were selected at each test site, and thirty mature and healthy leaves were randomly collected from each plant during 9:00–12:00 in fine weather. The relative chlorophyll content index (CCI) was measured by CCM-200 plus chlorophyll meter (OPTI-Science, Massachusetts, USA). The instrument is recalibrated once every 15 min. Use FA/JA electronic balance (Changzhou Xingyun Electronic Equipment Co., Ltd., Changzhou, China) to weigh the fresh weight of Appl. Sci. 2021, 11, 1937 4 of 15 leaves (LFW, g). Leaf thickness (LT, mm) was measured by CD-15AX caliper rule (Mi- tutoyo, Shanghai, China). The leaf area (LA, cm ) was measured by a DS-310/360W scan- ner (Epson (China) co., ltd, Beijing, China), and then put into 9030A electric constant tem- perature air-blowing drying oven (Yiheng, Shanghai, China), the temperature was 60 °C, 2.2. Leaf Reflectance Spectrum Collection and Calculation Method of Leaf Functional Traits and the leaf dry weight (LDW, g) was weighed by FA/JA electronic balance. The FieldSpec3 near-infrared spectrometer (ASD, Almero, Netherlands, USA) was Specific leaf area (SLA, m /g) = LA/LDW (1) used to collect spectral data. The spectral band obtained by this instrument ranges from 300 nm to 2500 nm. The reflectivity curve of the final output spectrum is the average Leaf volume (LV, cm ) = LT × LA (2) value of 10 repetitions. The flow chart of spectral measurement is shown in Figure 2. The light source is the solarLeaf tissue light sour de ce at nsity 12:00–13:00. (LTD, g/cm Whiteboar ) = LDW/ d LV is made of sintered (3) polytetrafluoroethylene-based material. In order to reduce human interference, instrument Leaf dry matter content (LDMC, g/g) = LDW/LFW (4) operators wear cotton overalls. Figure 2. The operation flow of ASD spectrometer for measuring leaf surface spectrum. (a) is the operation flow of ASD Figure 2. The operation flow of ASD spectrometer for measuring leaf surface spectrum. (a) is the operation flow of ASD spectrometer. (b) is a schematic diagram of the operation of the spectrometry of the blade. spectrometer. (b) is a schematic diagram of the operation of the spectrometry of the blade. In July, 2019, 30 Osmanthus fragrans with different degrees of damage were selected As shown in Table 1, we selected 8 typical spectral characteristic parameters of plants at each test site, and thirty mature and healthy leaves were randomly collected from [37–39], including the slope of red edge (RES), the position of red edge (REP), the reflec- each plant during 9:00–12:00 in fine weather. The relative chlorophyll content index tance of red valley (RRV), the reflectance of green peak (RGP), the position of green peak (CCI) was measured by CCM-200 plus chlorophyll meter (OPTI-Science, Massachusetts, USA). The instrument is recalibrated once every 15 min. Use FA/JA electronic balance (Changzhou Xingyun Electronic Equipment Co., Ltd., Changzhou, China) to weigh the fresh weight of leaves (LFW, g). Leaf thickness (LT, mm) was measured by CD-15AX caliper rule (Mitutoyo, Shanghai, China). The leaf area (LA, cm ) was measured by a DS-310/360W scanner (Epson (China) Co., ltd, Beijing, China), and then put into 9030A electric constant temperature air-blowing drying oven (Yiheng, Shanghai, China), the temperature was 60 C, and the leaf dry weight (LDW, g) was weighed by FA/JA electronic balance. Specific leaf area (SLA, m /g) = LA/LDW (1) Leaf volume LV, cm = LT  LA (2) Leaf tissue density (LTD, g/cm ) = LDW/LV (3) Leaf dry matter content (LDMC, g/g) = LDW/LFW (4) As shown in Table 1, we selected 8 typical spectral characteristic parameters of plants [37–39], including the slope of red edge (RES), the position of red edge (REP), the reflectance of red valley (RRV), the reflectance of green peak (RGP), the position of green peak (GPP), the reflectance of water stress band (RWSB), the slope of yellow edge (YES), the position of yellow edge (YEP). Appl. Sci. 2021, 11, 1937 5 of 15 Table 1. Spectral parameters and their description. Spectral Parameter Description The maximum 1st derivative of reflectance in the red band RES (680~750 nm). The wavelength position corresponding to the maximum REP reflectance in the wavelength band 680~750 nm. RRV The minimum band reflectance in the range of 640~700 nm. RGP The maximum band reflectance in the range of 510~580 nm. The wavelength position corresponding to the green peak GPP reflectance in the wavelength band 510~580 nm. The maximum band reflectance in the range of wavelengths from RWSB 1550~1750 nm. The maximum 1st derivative of reflectance in the yellow band YES (550–582 nm). The wavelength position corresponding to the maximum YEP reflectance in the wavelength band 550~582 nm. 2.3. Data Analysis Analysis and processing of spectral data were based on ViewSpecPro 6.0 software. We use ViewSpecPro software to analyze the original spectral data and the first-order differential spectral data. Leaf functional traits data processing was based on origin2019b software and Excel 2020 software. 3. Results and Discussion 3.1. Changes in Leaf Functional Traits of Osmanthus Fragrans Leaves Parasitized by Cuscuta japonica Choisy In this study, six plant functional traits that are sensitive to environmental changes and external stress were selected, including chlorophyll content, leaf area, leaf thickness, specific leaf area, leaf dry matter content and leaf tissue density. As shown in Figure 3, there were significant differences in leaf functional traits of Osmanthus fragrans between healthy leaves and the leaves being parasitic by Cuscuta japonica Choisy. The chlorophyll content index, leaf area and specific leaf area of Osmanthus fragrans were significantly lower than those after parasitism, and these indexes gradually decreased (CK > T1 > T2 > T3) with the increase of parasitism intensity. There were significant differences between healthy leaves and parasitic leaves (chlorophyll content index, leaf area and specific leaf area) (Figure 3a,b,e). The reason for the poor growth of Osmanthus fragrans was that Cuscuta japonica plundered water and nutrients of Osmanthus fragrans [40–44]. In addition, due to the overgrowth of the parasitic plant Cuscuta japonica, the host plant lacks sufficient light. It is also an important reason for the decrease of chlorophyll content index, leaf area and specific leaf area in plants. Leaf thickness, dry matter content and leaf tissue density of Osmanthus fragrans were significantly higher than those after parasitism, and these indexes gradually increased with the increase of parasitism intensity (CK < T1 < T2 < T3) (Figure 3c,d,f). In this study, the increase of leaf dry matter content and leaf tissue density was the adjustment of Osmanthus fragrans resources after being parasitized by Cuscuta japonica. This was an ecological strategy for plants to cope with external disturbances, which aims to improve the nutrient preservation and defense ability of leaves by increasing the leaf dry matter content and leaf tissue density. Appl. Sci. 2021, 11, 1937 6 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 6 of 15 Figure 3. Changes in leaf functional traits under different parasitic intensities. Different lowercase letters indicate signifi- Figure 3. Changes in leaf functional traits under different parasitic intensities. Different lowercase letters indicate significant cant differences in parameters at the p < 0.05 level. (a) Chlorophyll content index, (b) leaf area, (c) leaf dry matter content, differences in parameters at the p < 0.05 level. (a) Chlorophyll content index, (b) leaf area, (c) leaf dry matter content, (d) leaf (d) leaf tissue density, (e) specific leaf area, (f) leaf thickness. tissue density, (e) specific leaf area, (f) leaf thickness. 3.2. Spectral Characteristics of Osmanthus Fragrans Leaves under the Different Parasitic 3.2. Spectral Characteristics of Osmanthus Fragrans Leaves under the Different Parasitic Intensity Intensity of Cuscuta japonica Choisy of Cuscuta japonica Choisy Under different parasitic intensities of Cuscuta japonica Choisy, the leaf surface spec- Under different parasitic intensities of Cuscuta japonica Choisy, the leaf surface spectral tral reflectance curves of Osmanthus fragrans were basically the same, but the spectral re- reflectance curves of Osmanthus fragrans were basically the same, but the spectral reflectance flectance values were significantly different (Figure 4). Spectral reflectance values gener- values were significantly different (Figure 4). Spectral reflectance values generally decreas- ally decreasing with the deepening of parasitic intensity, and the reflectance values were ing with the deepening of parasitic intensity, and the reflectance values were CK > T1 > T2 > CK > T1 > T2 > T3. In the visible light to near-infrared 350~1800 nm band, the spectral T3. In the visible light to near-infrared 350~1800 nm band, the spectral reflectance of Osman- reflectance of Osmanthus fragrans leaves under different parasitic intensities was the most thus fragrans leaves under different parasitic intensities was the most easily distinguished easily distinguished in the range of 750~1400 nm, which indicate that this band was the in the range of 750~1400 nm, which indicate that this band was the sensitive range of host sensit plants’ ive spectral range o response f host plto ants’ spectral r parasitic infection. esponse to p At the a same rasititime, c infethis ction. change At the same ti characterime, stic twas his ch common ange ch under aractedif rist fer ic en was t parasitic commoconditions. n under differ In addition, ent parasitic the spectral conditions. In reflectance addit curve ion, slope of Osmanthus fragrans leaves has a sharp increasing trend in the range of 700~780 nm. the spectral reflectance curve slope of Osmanthus fragrans leaves has a sharp increasing trend i In the range n the of range of 350~1800 700~7 nm,80 nm. In t the spectral he ra reflection nge of curves 350~1800 of Osmanthus nm, the spectral ref fragrans leaves lection for curves of all treatments Osmanthus fra have four grmain ans leaves fo reflection r all treatments have peaks and five main fouabsorption r main reflect valleys, ion peak and s and the positions were basically the same. The reflection peaks were located at 560 nm, 1150 nm, five main absorption valleys, and the positions were basically the same. The reflection 1300 nm and 1650 nm, and the absorption valleys were located at 350–560 nm, 600–700 nm, peaks were located at 560 nm, 1150 nm, 1300 nm and 1650 nm, and the absorption valleys 950–1050 nm, 1150~1250 nm, and 1400~1500 nm, respectively. were located at 350–560 nm, 600–700 nm, 950–1050 nm, 1150~1250 nm, and 1400~1500 nm, respectively. Chlorophyll content index of Osmanthus fragrans gradually decreased with the deep- ening of parasitism (Figure 3). Previous studies show that chlorophyll content index can better characterize the light reflection curve of plant leaves [31,45]. Therefore, the spectral reflectance curve of the parasitized Osmanthus fragrans leaves was higher than that of the non-parasitized healthy Osmanthus fragrans leaves, which may be related to the decrease of chlorophyll content index. With the deepening of parasitism, the chlorophyll content Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 of 15 index gradually decreases, so the absorption of sunlight decreases and the reflectivity in- creases [46]. Studies have shown that the phenomenon of plants increasing suddenly in this waveband belongs to the typical “red edge effect” characteristic of plants [46]. At the same time, the spectral reflectance of the leaves of the host plant (Osmanthus fragrans) with different relative chlorophyll contents has a higher reflection platform in the range of 750~1400 nm, which was wavy and may be affected by the cell structure of the leaves [46,47]. Among them, the sample with the lowest reflection coefficient was the sample with the lowest chlorophyll content index (the highest parasitic intensity). The reflectance of the sample with the highest chlorophyll content (without parasitism) was the highest Appl. Sci. 2021, 11, 1937 7 of 15 at 1150 nm, which was 0.958. There was a significant valley at 1350~1800 nm, which may be closely related to light absorption by water [48–51]. Figure 4. Spectral reflectance of healthy Osmanthus fragrans leaves and spectral reflectance of Osman- Figure 4. Spectral reflectance of healthy Osmanthus fragrans leaves and spectral reflectance of Os- thus fragrans with different parasitic degrees. manthus fragrans with different parasitic degrees. Chlorophyll content index of Osmanthus fragrans gradually decreased with the deep- 3.3. Dynamic Changes of Spectral Characteristic Parameters of Osmanthus fragrans in Different ening of parasitism (Figure 3). Previous studies show that chlorophyll content index can Parasitic Stages better characterize the light reflection curve of plant leaves [31,45]. Therefore, the spectral After first-order differentiation of the reflectance original spectral curve, the first-or- reflectance curve of the parasitized Osmanthus fragrans leaves was higher than that of the der differential reflection coefficients under different parasitic intensities were obtained non-parasitized healthy Osmanthus fragrans leaves, which may be related to the decrease (Figure 5). We calculated eight typical spectral parameters under different parasitic inten- of chlorophyll content index. With the deepening of parasitism, the chlorophyll content sities (Figure 6), and the parameter description was shown in Table 1. After Osmanthus index gradually decreases, so the absorption of sunlight decreases and the reflectivity fragrans was parasitized by Cuscuta japonica Choisy, there was an obvious “blue shift” in increases [46]. Studies have shown that the phenomenon of plants increasing suddenly the red edge of its leaf surface spectral curve (Figures 5 and 6a). With the deepening of in this waveband belongs to the typical “red edge effect” characteristic of plants [46]. parasitic intensity, the degree of “blue shift” also increased, indicating that with the in- At the same time, the spectral reflectance of the leaves of the host plant (Osmanthus fra- crea grans se of pa ) with rasi differ tic i ent ntensi relative ty, the chlor inflophyll uence on contents the red has edge o a higher f the r le eflection af surface platform became more in the severe. In addition, the slope of the red edge of the host plant decreased obviously after range of 750~1400 nm, which was wavy and may be affected by the cell structure of the pa leaves rasitiza [46 ti ,47 on wi ]. Among th CK (0 them, .01557the ) > T1 (0 sample .0152 with 4) > T2 the (0 lowest .01469)r eflection > T3 (0.0136 coef 8)ficient (Figures was 5 athe nd 6b). sample Many with stu the dies lowest show that the red chlorophyll edg content e slope h indexa(the s a good in highest dic parasitic ation of chloroph intensity).yll con- The re- flectance of the sample with the highest chlorophyll content (without parasitism) was the tent [52]. Combined with Figure 3, with the deepening of parasitic intensity, chlorophyll highest at 1150 nm, which was 0.958. There was a significant valley at 1350~1800 nm, content index is decreasing. Therefore, we suspect that the cause of this phenomenon was which may be closely related to light absorption by water [48–51]. related to the influence of Cuscuta japonica Choisy on the photosynthesis of host plants. As can be seen from Figures 5 and 6c, with the deepening of parasitic intensity, the spectral 3.3. Dynamic Changes of Spectral Characteristic Parameters of Osmanthus fragrans in Different Parasitic Stages After first-order differentiation of the reflectance original spectral curve, the first- order differential reflection coefficients under different parasitic intensities were obtained (Figure 5). We calculated eight typical spectral parameters under different parasitic inten- sities (Figure 6), and the parameter description was shown in Table 1. After Osmanthus fragrans was parasitized by Cuscuta japonica Choisy, there was an obvious “blue shift” in the red edge of its leaf surface spectral curve (Figures 5 and 6a). With the deepening of parasitic intensity, the degree of “blue shift” also increased, indicating that with the increase of parasitic intensity, the influence on the red edge of the leaf surface became more severe. In addition, the slope of the red edge of the host plant decreased obvi- ously after parasitization with CK (0.01557) > T1 (0.01524) > T2 (0.01469) > T3 (0.01368) Appl. Sci. 2021, 11, 1937 8 of 15 (Figures 5 and 6b). Many studies show that the red edge slope has a good indication of Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 of 15 chlorophyll content [52]. Combined with Figure 3, with the deepening of parasitic intensity, chlorophyll content index is decreasing. Therefore, we suspect that the cause of this phe- nomenon was related to the influence of Cuscuta japonica Choisy on the photosynthesis of host plants. As can be seen from Figures 5 and 6c, with the deepening of parasitic intensity, red valley reflectance of host plants Table 1 shows a trend of increasing at first and then the spectral red valley reflectance of host plants Table 1 shows a trend of increasing at first decreasing (T1 (0.07912) > T2 (0.07153) > CK (0.0672) > T3 (0.0298)). In the initial stage of and then decreasing (T1 (0.07912) > T2 (0.07153) > CK (0.0672) > T3 (0.0298)). In the initial parasitism, due to the shielding of parasitic plants, the sun burns the leaves of host plants stage of parasitism, due to the shielding of parasitic plants, the sun burns the leaves of less, and the spectral reflectance tends to increase. However, in the middle and late stage host plants less, and the spectral reflectance tends to increase. However, in the middle of parasitism, the nutrient deficiency of the host plant leaves led to the weakening of sun- and late stage of parasitism, the nutrient deficiency of the host plant leaves led to the light reflection in this band [51,52]. Under different parasitic conditions, the position of weakening of sunlight reflection in this band [51,52]. Under different parasitic conditions, the yellow edge is not affected, and it is all at 570 nm (Figures 5 and 6g). With the deep- the position of the yellow edge is not affected, and it is all at 570 nm (Figures 5 and 6g). ening of parasitic intensity, the slope of the yellow edge (CK (−0.00143) > T1 (−0.00213) > With the deepening of parasitic intensity, the slope of the yellow edge (CK (0.00143) > T2 (−0.00249) >T3 (−0.00264)) and the reflectivity of the green peak (CK (0.0017), T1 T1 (0.00213) > T2 (0.00249) >T3 (0.00264)) and the reflectivity of the green peak (CK (0.0028), T2 (0.0039) and T3 (0.0043)) gradually decreases (Figures 5 and 6h,d). The posi- (0.0017), T1 (0.0028), T2 (0.0039) and T3 (0.0043)) gradually decreases (Figures 5 and 6h,d). tion of the green peak presents shifts to long wave direction (CK (519), T1(519), T2(520), The position of the green peak presents shifts to long wave direction (CK (519), T1(519), T3(522)) (Figures 5 and 6e). At this time, the reflectivity of the water stress wave band T2(520), T3(522)) (Figures 5 and 6e). At this time, the reflectivity of the water stress wave (Figures 4 and 6f) decreases gradually with CK (0.5425) > T1 (0.5182) > T2 (0.4938) > T3 band (Figures 4 and 6f) decreases gradually with CK (0.5425) > T1 (0.5182) > T2 (0.4938) > (0.3483). Studies have shown that the spectral reflectance of vegetation in the range of T3 (0.3483). Studies have shown that the spectral reflectance of vegetation in the range of 1550~1750 nm is usually closely related to the cell structure and water content of plants, 1550~1750 nm is usually closely related to the cell structure and water content of plants, which indicate the water absorption characteristics [53]. Therefore, with the deepening of which indicate the water absorption characteristics [53]. Therefore, with the deepening of the invasion degree of Cuscuta japonica Choisy, the cell structure of the leaves suffers cer- the invasion degree of Cuscuta japonica Choisy, the cell structure of the leaves suffers certain tain damage. This is basically consistent with the research results of Xu et al. on pine wood damage. This is basically consistent with the research results of Xu et al. on pine wood nematode infecting Pinus needles [54]. nematode infecting Pinus needles [54]. Figure 5. The first derivative spectral curves of the Osmanthus fragrans leaves. Figure 5. The first derivative spectral curves of the Osmanthus fragrans leaves. Appl. Sci. 2021, 11, 1937 9 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 15 Figure 6. Dynamic trend of spectral parameters in different parasitism period. (a–h) respectively represents the position Figure 6. Dynamic trend of spectral parameters in different parasitism period. (a–h) respectively represents the position of red edge (REP), the slope of red edge (RES), the reflectance of red valley (RRV), the reflectance of green peak (RGP), of red edge (REP), the slope of red edge (RES), the reflectance of red valley (RRV), the reflectance of green peak (RGP), the the position of green peak (GPP), the reflection of water stress band (RWSB), the position of yellow edge (YEP), and the position of green peak (GPP), the reflection of water stress band (RWSB), the position of yellow edge (YEP), and the slope yellow edge slope yellow (Y edge ES) under (YES) under differe dif nt parasitic intensities. ferent parasitic intensities. 3.4. Correlation between Chlorophyll Content and Spectral Characteristic Parameters of Host 3.4. Correlation between Chlorophyll Content and Spectral Characteristic Parameters of Host Plants with Different Parasitic Degree of Cuscuta japonica Choisy Plants with Different Parasitic Degree of Cuscuta japonica Choisy As shown in Figure 3, CCI of the host plant (Osmanthus fragrans) gradually decreased As shown in Figure 3, CCI of the host plant (Osmanthus fragrans) gradually decreased with the deepening of the parasitic intensity of Cuscuta japonica Choisy. Previous studies with the deepening of the parasitic intensity of Cuscuta japonica Choisy. Previous studies generally believed that chlorophyll was an important parameter to determine the char- generally believed that chlorophyll was an important parameter to determine the charac- acteristics of spectral reflectance curve of plant [55]. When the vegetation is in a healthy teristics of spectral reflectance curve of plant [55]. When the vegetation is in a healthy growth state and the chlorophyll content is high, the position of the red edge moves to- growth state and the chlorophyll content is high, the position of the red edge moves to- wards the long wave direction [55,56]. However, when vegetation is stressed by external wards the long wave direction [55,56]. However, when vegetation is stressed by external environmental, such as drought stress, high temperature stress or insert damage, the red environmental, such as drought stress, high temperature stress or insert damage, the red edge position tends to the short-wave direction [57]. Pearson correlation analysis was used edge position tends to the short-wave direction [57]. Pearson correlation analysis was to analyze the correlation between spectral parameters and plant functional traits (Table 2), used to analyze the correlation between spectral parameters and plant functional traits and the correlation analysis in Table 2 was based on all the collected sample data, including (Table 2), and the correlation analysis in Table 2 was based on all the collected sample four parasitic samples. It can be seen that there was an extremely significant correlation data, including four parasitic samples. It can be seen that there was an extremely signifi- between spectral parameters and CCI. There was a significant correlation between RES cant correlation between spectral parameters and CCI. There was a significant correlation and LT. RRV, RGP, RES, RWSB and CCI were have high correlation. In order to further between RES and LT. RRV, RGP, RES, RWSB and CCI were have high correlation. In order explore the correlation between spectral parameters and plant functional traits, according to further explore the correlation between spectral parameters and plant functional traits, to the correlation results in Table 2, the linear correlation analysis was carried out on the according to the correlation results in Table 2, the linear correlation analysis was carried indicators that achieved significant correlation (Figure 7). Figure 7 showed the correlation out on the indicators that achieved significant correlation (Figure 7). Figure 7 showed the between different spectral parameters with CCI and LT. The results of correlation analysis correlation between different spectral parameters with CCI and LT. The results of corre- between plant functional traits and spectral parameters show that they show different lation analysis between plant functional traits and spectral parameters show that they correlations. The reflectance of red valley has the greatest correlation with chlorophyll show different correlations. The reflectance of red valley has the greatest correlation with content (y = 65913.323x + 9.783, R = 0.6888), which indicate that red edge characteristics chlorophyl were very l c sensitive ontent (y to = parasitic −65913.323 infestation x + 9.783and , R = can 0.6888), wh be used to ich characteri indicate th zeat changes red edge in Appl. Appl. Sci. Sci. 2021 2021, , 11 11, x FO , 1937R PEER REVIEW 10 of 10 of 15 15 characteristics were very sensitive to parasitic infestation and can be used to characterize chlorophyll content of Osmanthus fragrans under different parasitic degrees. According to changes in chlorophyll content of Osmanthus fragrans under different parasitic degrees. the results in Figure 7, the spectral parameter model with the highest accuracy was selected. According to the results in Figure 7, the spectral parameter model with the highest accu- Then, a prediction model is established with the most sensitive spectral parameters as inde- racy was selected. Then, a prediction model is established with the most sensitive spectral pendent variables and chlorophyll content as dependent variable. Finally, the accuracy of parameters as independent variables and chlorophyll content as dependent variable. Fi- the model was further verified by analyzing the predicted and measured values calculated nally, the accuracy of the model was further verified by analyzing the predicted and meas- by the linear regression model (Figure 8). As shown in Figure 8, the chlorophyll inversion ured values calculated by the linear regression model (Figure 8). As shown in Figure 8, model of red valley reflectance was tested, and it was found that the prediction accuracy of the chlorophyll inversion model of red valley reflectance was tested, and it was found that this model was high and stable (R = 0.8811, RMSE = 0.0004). the prediction accuracy of this model was high and stable (R = 0.8811, RMSE = 0.0004). Table 2. Pearson correlation analysis between plant traits and spectral parameters. * indicates that the Table 2. Pearson correlation analysis between plant traits and spectral parameters. * indicates that correlation reaches a significant level at the level of p < 0.05. and ** indicates a significant correlation the correlation reaches a significant level at the level of p < 0.05. and ** indicates a significant corre- reaches a significant level at the level of p < 0.01. lation reaches a significant level at the level of p < 0.01. RRV RGP RES RWSB RRV RGP RES RWSB LT 0.25218 0.1787 0.28318 * 0.09577 LT 0.25218 −0.1787 −0.28318 * 0.09577 LA 0.01651 0.18462 0.14292 0.0353 LA −0.01651 0.18462 −0.14292 0.0353 LDMC 0.01136 0.00523 0.03048 0.09512 LDMC 0.01136 −0.00523 0.03048 0.09512 SLA 0.20281 0.24112 0.06407 0.0641 SLA 0.20281 −0.24112 −0.06407 0.0641 LTD 0.19553 0.17124 0.13662 0.01367 LTD −0.19553 0.17124 0.13662 −0.01367 CCI 0.82993 ** 0.72953 ** 0.65295 ** 0.56967 ** CCI −0.82993 ** 0.72953 ** 0.65295 ** −0.56967 ** Figure 7. Linear correlation between functional traits and spectral parameters. (a) the reflection of red valley (RRV) and Figure 7. Linear correlation between functional traits and spectral parameters. (a) the reflection of red valley (RRV) and CCI, (b) the reflectance of green peak (RGP) and CCI, (c) the slope of red edge (RES) and CCI, (d) the reflection of water CCI, (b) the reflectance of green peak (RGP) and CCI, (c) the slope of red edge (RES) and CCI, (d) the reflection of water stress band (RWSB) and CCI, (e) the reflectance of green peak (RGP) and LT. stress band (RWSB) and CCI, (e) the reflectance of green peak (RGP) and LT. Appl. Sci. 2021, 11, 1937 11 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 11 of 15 Figure 8. Test of chlorophyll inversion model based on red valley reflectance. Figure 8. Test of chlorophyll inversion model based on red valley reflectance. 3.5. Effects of Parasitic Plants on the Correlation of Functional Traits of Osmanthus fragrans and 3.5. Effects of Parasitic Plants on the Correlation of Functional Traits of Osmanthus fragrans Analysis of Leaf Economics Spectrum and Analysis of Leaf Economics Spectrum There was an interdependent relationship between the functional traits of the leaves There was an interdependent relationship between the functional traits of the leaves (Table 3). There was a significant positive correlation between LA and SLA. There was a (Table 3). There was a significant positive correlation between LA and SLA. There was a significant negative correlation between SLA and LDMC and LTD. LA was significantly significant negative correlation between SLA and LDMC and LTD. LA was significantly negatively correlated with LDMC and LTD. There was a significant negative correlation negatively correlated with LDMC and LTD. There was a significant negative correlation between LT and LTD. There was a very significant positive correlation between LDMC between LT and LTD. There was a very significant positive correlation between LDMC and LTD. There was a significant positive correlation between CCI and SLA. At the same and LTD. There was a significant positive correlation between CCI and SLA. At the same time, LT has a negative correlation with SLA and LA, but the correlation has not reached a time, LT has a negative correlation with SLA and LA, but the correlation has not reached significant level. a significant level. Table 3. Correlation between plant functional traits indicators. * indicates a significant correlation Table 3. Correlation between plant functional traits indicators. * indicates a significant correlation between functional traits at the level of p < 0.05, and ** indicates a significant correlation between between functional traits at the level of p < 0.05, and ** indicates a significant correlation between functional traits at the level of p < 0.01. functional traits at the level of p < 0.01. LT LA SLA LDMC LTD CCI LT LA SLA LDMC LTD CCI LT 1 LT 1 LA 0.1696 1 LA −0.1696 1 SLA 0.1502 0.3581 * 1 SLA −0.1502 0.3581 * 1 LDMC 0.1293 0.4246 * 0.6991 ** 1 LDMC −0.1293 −0.4246 * −0.6991 ** 1 LTD 0.5436 ** 0.4218 * 0.5950 ** 0.7517 ** 1 LTD −0.5436 ** −0.4218 * −0.5950 ** 0.7517 ** 1 CCI 0.2566 0.2623 0.4993 * 0.2201 0.4456 * 1 CCI 0.2566 0.2623 0.4993 * −0.2201 −0.4456 * 1 Studies have shown that leaf functional traits can reflect the adaptability of plants to Studies have shown that leaf functional traits can reflect the adaptability of plants to the environment, but compared with a single leaf functional trait, continuous leaf economics the environment, but compared with a single leaf functional trait, continuous leaf eco- spectrum can better reflect the growth strategy and adaptation mechanism of plants [54,55]. nomics spectrum can better reflect the growth strategy and adaptation mechanism of In this study, there was an obvious trade-off relationship between the functional traits of plants [54,55]. In this study, there was an obvious trade-off relationship between the func- plant leaves, which indicate that when plants are harmed by parasitic plants, host plants tional traits of plant leaves, which indicate that when plants are harmed by parasitic show certain ecological trade-off strategies in terms of functional traits for survival. SLA is plants, host plants show certain ecological trade-off strategies in terms of functional traits closely related to the growth and survival strategy of plants, which can represent the for survival. SLA is closely related to the growth and survival strategy of plants, which adaptability of plants to the environment and the ability to obtain resources [58]. In this can represent the adaptability of plants to the environment and the ability to obtain re- study, after being invaded by parasitic plants, the reduction of SLA of the host plants makes sources [58]. In this study, after being invaded by parasitic plants, the reduction of SLA of the plants adapt to resource-poor environment. LDMC represents the plants to maintain the host plants makes the plants adapt to resource-poor environment. LDMC represents water and nutrients (cellulose, protein and Nitrogen content, etc), while LTD reflects the plants to maintain water and nutrients (cellulose, protein and Nitrogen content, etc), the bearing capacity and defense ability of plant leaves, which is closely related to the while LTD reflects the bearing capacity and defense ability of plant leaves, which is closely turnover growth rate of leaves [59–61]. In this study, LDMC and LTD gradually increased with the increase of parasitic intensity, and showed a very significant positive correlation. Appl. Sci. 2021, 11, x FOR PEER REVIEW 12 of 15 Appl. Sci. 2021, 11, 1937 12 of 15 related to the turnover growth rate of leaves [59–61]. In this study, LDMC and LTD grad- ually increased with the increase of parasitic intensity, and showed a very significant pos- itive correlation. This indicated that the host plant can improve the nutrient retention abil- This indicated that the host plant can improve the nutrient retention ability of leaves under ity of leaves under the adverse environment of parasitic stress, and thus making more the adverse environment of parasitic stress, and thus making more effective use of limited effective use of limited resources [58,60]. The increase of LTD was beneficial to strengthen resources [58,60]. The increase of LTD was beneficial to strengthen the defense ability of the defense ability of plant against biological factors [61]. To sum up, after being parasi- plant against biological factors [61]. To sum up, after being parasitized, the leaf functional tized, the leaf functional traits of the host plant were generally characterized by large leaf traits of the host plant were generally characterized by large leaf thickness, small leaf area, thickness, small leaf area, small specific leaf area, low chlorophyll content index, high dry small specific leaf area, low chlorophyll content index, high dry matter content and high matter content and high leaf tissue density. Therefore, we suspect that the leaf economics leaf tissue density. Therefore, we suspect that the leaf economics spectrum may also exist in spectrum may also exist in the parasitic environment, and there was a general trend to- the parasitic environment, and there was a general trend toward “slow investment-return” ward “slow investment-return” type in the global leaf economics spectrum (Figure 9). type in the global leaf economics spectrum (Figure 9). Figure 9. Conceptual illustration of leaf economics spectrum [36,62]. Figure 9. Conceptual illustration of leaf economics spectrum [36,62]. 4. Conclusions 4. Conclusions In this paper, we studied the spectral characteristics and leaf functional traits of Osman- In this paper, we studi thus fragrans in ed the spectra different parasitic l charaperiods cteristicafter s and l Cuscuta eaf functiona japonica l tra Choisy its of infection, Os- revealing manthus fragran the s in relatio differe nship nt parasitic between periods after the spectral characteristic Cuscuta japonic changes a Choisyand infec invasive tion, re-processes after vealing the relhost ationshi susceptibility p between the spectra . In addition, by l ch establishing aracteristic ch a corr anelation ges and inv between asivspectral e pro- characteristic parameters and chlorophyll content, the research results can provide theoretical support cesses after host susceptibility. In addition, by establishing a correlation between spectral for the prediction of plant diseases in the early stage. At the same time, it can provide a characteristic parameters and chlorophyll content, the research results can provide theo- reference for monitoring and early warning of infringement, and a new experimental basis retical support for the prediction of plant diseases in the early stage. At the same time, it for different measures to control Cuscuta japonica Choisy. Main conclusions are as follows. can provide a reference for monitoring and early warning of infringement, and a new experimental basis for different measures to control Cuscuta japonica Choisy. Main conclu- (1) The spectral reflectance was generally higher before parasitism than after parasitism. sions are as follows. There were four main reflection peaks and five main absorption valleys in the spectral (1) The spectral reflectance was generally higher before parasitism than after parasit- reflection curve (350~1800 nm). The near-infrared band (750~1400 nm) was the ism. There were four main reflection peaks and five main absorption valleys in the spec- sensitive range of spectral response of host plants to parasitic infection. At the tral reflection curve (350~1800 nm). The near-infrared band (750~1400 nm) was the sensi- same time, such variation characteristics were universal under different parasitic tive range of spectral response of host plants to parasitic infection. At the same time, such degree conditions. variation characteristics were universal under different parasitic degree conditions. (2) The position of red edge, slope of red edge, reflectance of a green peak, and reflectance (2) The position of red edge, slope of red edge, reflectance of a green peak, and re- of water stress band can well reflect the invasion status in different parasitic stages. flectance of water stress band can well reflect the invasion status in different parasitic After parasitism, the red edge position of the host plant spectrum shifted to shortwave stages. After parasitism, the red edge position of the host plant spectrum shifted to direction. With the deepening of parasitic intensity, the moving distance of the red shortwave direction. With the deepening of parasitic intensity, the moving distance of the edge position to the short-wave direction increases. red edge position to the short-wave direction increases. (3) With the increase of parasitic intensity, the relative content of chlorophyll in host plants gradually decreases, and the spectral characteristic parameters were significantly Appl. Sci. 2021, 11, 1937 13 of 15 correlated with them. Chlorophyll inversion model based on red valley reflectance has the highest accuracy (y = 65913.323x + 9.783, R = 0.6888). (4) After parasitism, the leaf functional traits of host plant were characterized by large leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter content, and high leaf tissue density. We suspect that there may be leaf economics spectrum (“slow investment-return”) in the parasitic environment. Author Contributions: J.Z. conceived and designed the study. J.Z. and X.Z. contributed to materials and tools. J.Z., J.Y. and Q.X. performed the experiments. Q.X., J.Y., X.Z. and C.X. contributed to literature collection. J.Z. contributed to data analysis. J.Z. contributed to paper preparation, writing and revision. All the authors read and approved it for publication. All authors have read and agreed to the published version of the manuscript. Funding: This study was funded by “the Fundamental Research Funds for the Central Universities (NO. BLX201704)”, “National Natural Science Foundation of China (NSFC project NO. 31901277)” and “Integration and Demonstration of Key Technologies for Oriented Tending of Plain Ecological Forest in Chaoyang District (CYSF-1904)”. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data involved in the article were all shown in the figures and tables. However, there are still available from the first author on reasonable request. Acknowledgments: Research was conducted in Guangxi University. We thank the Forestry College of Guangxi University and the Agricultural College of Guangxi University for providing us with necessary experimental platforms and instruments. The English in this document has been checked by at least two professional editors; both were native speakers of English. We thank Jiguang Wei from the College of Agriculture of Guangxi University for identifying the plant species used in this study (Identification information refers to Flora of China). Conflicts of Interest: The authors declare that they have no competing interest. Ethics Approval and Consent to Participate: This experiment does not involve human experiments and animal experiments. The field trial experiments in the current study were permitted by the local government in China (Guangxi University and Guangxi Finance and Economics University), including the collection of leaf samples. 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