applied sciences

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

Jiyou Zhu 1, Qing Xu 1, Jiangming Yao 2, Xinna Zhang 1,* and Chengyang Xu 1,*

1 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, ; [email protected] (J.Z.); [email protected] (Q.X.) 2 College of Forestry, University, Nanning 530005, China; [email protected] * Correspondence: [email protected] (X.Z.); [email protected] (C.X.); Tel.: +86-010-6233-7082 (C.X.)

Abstract: Studies on the influence of parasitism on 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 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, R2 = 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 of Cuscuta japonica. Appl. Sci. 2021, 11, trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, 1937. https://doi.org/10.3390/ we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there app11041937 was a general trend toward the “slow investment-return” type in the global leaf economics spectrum.

Received: 1 February 2021 Keywords: leaf reflectance spectrum; leaf functional traits; leaf economics spectrum; parasitic; 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 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 [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 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 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 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 warning of thenew parasitism experimental of Cuscuta basis japonica for different Choisy measures. At the same to control time, Cuscuta it provides japonica a new Choisy and pro- experimental basisvides fora theoretical different measures basis for toan control in-depthCuscuta understanding japonica Choisy of theand parasitic provides damage mecha- a theoretical basisnism for of anCuscuta in-depth japonica understanding Choisy and its of control the parasitic strategies. damage 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,◦ between0 107°45′– Nanning108°51 city is′ locatedeast longitude in the and southwest 22°13′–23°32 of Guangxi′ north latitude. province, It betweenis a humid 107 subtropical45 – monsoon 108◦510 east longitude and 22◦130–23◦320 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, T1—Initial parasitism:parasitic, less T1—Initial than 50%, parasitism: T2—Parasitic less than metaphase: 50%, T2—Parasitic 50%~80%, T3—Late metaphase:para- 50 %~80%, T3— sitism: more thanLate 80%). parasitism: Healthy more growing than 80%). 30 Osmanthus Healthy gr fragransowing 30 of 15~20Osmanthus years oldfragrans were of 15~20 years selected, and theold plantingwere selected, location and was the away planting from location the influence was away of tall from buildings the influence and tall of tall buildings trees. Leaf samplesand tall were trees. collected Leaf samples from 10: were 00 a.m. collected to 12: 00from a.m. 10: on 00 June a.m. 2019.to 12: Ten00 a.m. mature on June 2019. Ten and healthy leavesmature were and cut healthy from each leaves tree, were placed cut from in an each icebox tree, and placed immediately in an icebox brought and immediately back to the laboratorybrought forback spectral to the determination.laboratory for spectral The time det fromermination. leaf collection The time to spectralfrom leaf collection to measurement wasspectral controlled measurement within 15was min, controlled thus ensuring within the 15 originalmin, thus growth ensuring activity the oforiginal growth leaf samples. Asactivity shown of inleaf Figure samples.1, Figure As shown1a is a plantin Figure that 1, is Figure not parasitic 1a is a andplant Figure that is1b not parasitic and is a plant thatFigure is parasitic 1b is bya plantCuscuta that japonica is parasitic Choisy by. Cuscuta Professor japonica Wei Jiguang Choisy. fromProfessor Agricul- Wei Jiguang from tural College ofAgricultural Guangxi University College of identified Guangxi theUniversity plants and identified plant diseases the plants involved and plant in diseases in- this study. volved in 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 leaves (LFW, g). Leaf thickness (LT, mm) was measured by CD-15AX caliper rule4 of 15(Mi- tutoyo, Shanghai, China). The leaf area (LA, cm2) 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 used to collect spectral data.Specific The spectral leaf area band (SLA, obtained m2/g) by = LA/LDW this instrument ranges from (1) 300 nm to 2500 nm. The reflectivity curve of the final output spectrum is the average Leaf volume (LV, cm3) = LT × LA (2) value of 10 repetitions. The flow chart of spectral measurement is shown in Figure2. The light source is the solarLeaf light tissue source density at 12:00–13:00. (LTD, g/cm Whiteboard3) = LDW/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 at eachAs test shown site, and in Table thirty 1, maturewe selected and 8 healthy typical spectral leaves were characteristic randomly parameters collected of from plants each[37 plant–39], including during 9:00–12:00 the slope inof finered edge weather. (RES), The the relativeposition chlorophyll of red edge content(REP), the index reflec- (CCI)tance was of measured red valley by (RRV), CCM-200 the reflectance plus chlorophyll of green meter peak (OPTI-Science,(RGP), the position Massachusetts, of green peak 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, cm2) 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, m2/g) = LA/LDW (1)   Leaf volume LV, cm3 = LT × LA (2)

Leaf tissue density (LTD, g/cm3) = LDW/LV (3) Leaf dry matter content (LDMC, g/g) = LDW/LFW (4) As shown in Table1, 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 Figure3, 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) (Figure3a,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) (Figure3c,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

FigureFigure 3. ChangesChanges in leaf functionalfunctional traitstraits underunder different different parasitic parasitic intensities. intensities Different. Different lowercase lowercase letters letters indicate indicate significant signifi- cantdifferences differences in parameters in parameters at the atp

3.2.3.2. Spectral Spectral Characteristics Characteristics of Osmanthus Fragrans LeavesLeaves underunder thethe DifferentDifferent ParasiticParasitic Intensity Intensityof Cuscuta of japonicaCuscuta Choisyjaponica Choisy UnderUnder different parasitic intensitiesintensities ofofCuscuta Cuscuta japonica japonica Choisy Choisy, the, the leaf leaf surface surface spectral spec- tralreflectance reflectance curves curves of Osmanthus of Osmanthus fragrans fragranswere basicallywere basically the same, the butsame, the but spectral the spectral reflectance re- flectancevalues were values significantly were significantly different (Figuredifferent4). (Figure Spectral 4). reflectance Spectral reflectance values generally values decreas- gener- allying withdecreasing the deepening with the of deepening parasitic intensity, of parasiti andc intensity, the reflectance and the values reflectance were CK values > T1 >were T2 > CKT3. > In T1 the > visible T2 > T3. light In to the near-infrared visible light 350~1800 to near-infrared nm band, 350~1800 the spectral nm reflectance band, the of spectralOsman- reflectancethus fragrans ofleaves Osmanthus under fragrans different leaves parasitic under intensities different wasparasitic the most intensities easily distinguishedwas the most easilyin the distinguished range of 750~1400 in the nm, range which of indicate750~1400 that nm, this which band indicate was the that sensitive this band range was of hostthe sensitiveplants’ spectral range of response host plants’ to parasitic spectral infection. response At to the parasitic same time, infection. this change At the characteristic same time, thiswas change common characteristic under different was parasitic common conditions. under different In addition, parasitic the spectralconditions. reflectance In addition, curve theslope spectral of Osmanthus reflectance fragrans curveleaves slope has of a Osmanthus sharp increasing fragrans trend leaves in the has range a sharp of 700~780 increasing nm. trendIn the in range the ofrange 350~1800 of 700~780 nm, the nm. spectral In the reflection range of curves 350~1800 of Osmanthus nm, the spectral fragrans reflectionleaves for curvesall treatments of Osmanthus have fourfragrans main leaves reflection for all peaks treatments and five have main four absorption main reflection valleys, peaks and and the fivepositions main wereabsorption basically valleys, the same. and the The positi reflectionons were peaks basically were located the same. at 560 The nm, reflection 1150 nm, peaks1300 nm were and located 1650 nm, at 560 and nm, the 1150 absorption nm, 1300 valleys nm and were 1650 located nm, atand 350–560 the absorption nm, 600–700 valleys nm, were950–1050 located nm, at 1150~1250 350–560 nm, nm, 600–700 and 1400~1500 nm, 950–1050 nm, respectively. 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 Appl. Sci. 2021, 11, 1937 of the sample with the highest chlorophyll content (without parasitism) was the highest7 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 manthus fragranswith with different different parasitic parasitic degrees. 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 (Figure3). Previous studies show that chlorophyll content index can Parasitic Stages better characterize the light reflection curve of plant leaves [31,45]. Therefore, the spectral reflectanceAfter first-order curve of the differentiation parasitized Osmanthus of the reflec fragranstance originalleaves wasspectral higher curve, than the that first-or- of the dernon-parasitized differential reflection healthy Osmanthus coefficients fragrans under leaves,different which parasitic may intensities be related towere the obtained decrease (Figureof chlorophyll 5). We calculated content index. eight Withtypical the spectr deepeningal parameters of parasitism, under different the chlorophyll parasitic content inten- sitiesindex (Figure gradually 6), and decreases, the parameter so the absorption description of was sunlight shown decreases in Table and1. After the reflectivityOsmanthus fragransincreases was [46 parasitized]. Studies have by Cuscuta shown japonica that the Choisy phenomenon, there was of plants an obvious increasing “blue suddenly shift” in thein thisred wavebandedge of its belongsleaf surface to the spectral typical curv “rede (Figures edge effect” 5 and characteristic 6a). With the ofdeepening plants [46 of]. parasiticAt the same intensity, time, thethe spectraldegree of reflectance “blue shift” of thealso leaves increased, of the indicating host plant that (Osmanthus with the fra-in- creasegrans) of with parasitic different intensity, relative the chlorophyll influence on contents the red has edge a higher of the reflectionleaf surface platform became inmore the severe.range of In 750~1400 addition, nm,the whichslope of was the wavy red edge and of may the be host affected plant bydecreased the cell structureobviously of after the parasitizationleaves [46,47]. with Among CK (0.01557) them, the > T1 sample (0.01524) with > T2 the (0.01469) lowest reflection > T3 (0.01368) coefficient (Figures was 5 and the 6b).sample Many with studies the lowest show chlorophyllthat the red contentedge slope index has (the a good highest indication parasitic of intensity). chlorophyll The con- re- tentflectance [52]. Combined of the sample with with Figure the highest3, with chlorophyllthe deepening content of parasitic (without intensity, parasitism) chlorophyll was the contenthighest index at 1150 is decreasing. nm, which Therefore, was 0.958. we There suspect was that a significant the cause valleyof this phenomenon at 1350~1800 was nm, relatedwhich mayto the be influence closely related of Cuscuta to light japonica absorption Choisy byon waterthe photosynthesis [48–51]. 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 (Figure5 ). We calculated eight typical spectral parameters under different parasitic inten- sities (Figure6), and the parameter description was shown in Table1. 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 (Figures5 and6a). 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

(Figures5 and6b ). Many studies show that the red edge slope has a good indication of Appl. Sci. 2021, 11, x FOR PEER REVIEWchlorophyll content [52]. Combined with Figure3, with the deepening of parasitic intensity,8 of 15

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 redhost valley plants. reflectance As can be of seen host from plants Figures Table5 and 1 shows6c, with a trend the deepening of increasing of parasitic at first intensity,and then decreasingthe spectral (T1 red (0.07912) valley reflectance > T2 (0.07153) of host > plantsCK (0.0672) Table1 > shows T3 (0.0298)). a trend In of the increasing initial stage at first of parasitism,and then decreasing due to the (T1 shielding (0.07912) of >parasitic T2 (0.07153) plants, > CKthe (0.0672)sun burns > T3 the (0.0298)). leaves of In host the plants initial less,stage and of parasitism,the spectraldue reflectance to the shielding tends to increase. of parasitic However, plants, in the the sun middle burns and the late leaves stage of 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 (Figures5 and6g). 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 (Figures5 and6h,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)) (Figures5 and6e ). 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 (Figures4 and6f) 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 nm is is usually usually closely closely related related to to th thee cell structure and water content of plants, which indicate the water absorption characteristics [[53].53]. Therefore, with the deepening of thethe invasion degreedegree ofofCuscuta Cuscuta japonica japonica Choisy Choisy, the, the cell cell structure structure of of the the leaves leaves suffers suffers certain cer- taindamage. damage. This This is basically is basically consistent consistent with with the the research research results results of of Xu Xu et et al. al. onon pinepine wood nematode infecting Pinus needles [54].[54].

Figure 5. TheThe first first derivative sp spectralectral 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 of red edge edge (REP), (REP), the the slope slope of of red red edge edge (RES), (RES), the the reflectanc reflectancee of ofred red valley valley (RRV), (RRV), thethe reflectance reflectance of green of green peak peak (RGP), (RGP), the positionthe position of green of green peak peak (GPP), (GPP), the reflecti the reflectionon of water of water stress stress band band (RWSB), (RWSB), the posi thetion position of yellow of yellow edge (YEP), edge (YEP), and the and slope the yellowslope yellow edge (YES) edge (YES)under under differe differentnt parasitic parasitic intensities. intensities.

3.4. Correlation Correlation between 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 Figure3, 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- generallyacteristics believed of spectral that reflectance chlorophyll curve was ofan plant important [55]. Whenparameter the vegetation to determine is in the a healthycharac- teristicsgrowth stateof spectral and the reflectance chlorophyll curve content of plant is high, [55]. the When position the vegetation of the red edgeis in movesa healthy to- growthwards the state long and wave the directionchlorophyll [55 content,56]. However, is high, whenthe position vegetation of the is stressedred edge by moves external to- wardsenvironmental, the long wave such asdirection drought [55 stress,,56]. However, high temperature when vegetation stress or insertis stressed damage, by external the red environmental,edge position tends such to as the drought short-wave stress, direction high temperature [57]. Pearson stress correlation or insert analysis damage, was the used red edgeto analyze position the correlationtends to the between short-wave spectral direct parametersion [57]. and Pearson plant functionalcorrelation traits analysis (Table was2), usedand the to correlationanalyze the analysis correlation in Table between2 was basedspectr onal parameters all the collected and sampleplant functional data, including traits (Tablefour parasitic 2), and samples.the correlation It can beanalysis seen that in Ta thereble 2 was was an based extremely on all significant the collected correlation sample data,between including spectral four parameters parasitic samples. and CCI. It There can be was seen a significantthat there was correlation an extremely between signifi- RES cantand correlation LT. RRV, RGP, between RES, RWSBspectral and parameters CCI were and have CCI. high There correlation. was a significant In order correlation to further betweenexplore the RES correlation and LT. RRV, between RGP, spectral RES, RWSB parameters and CCI and were plant have functional high correlation. traits, according In order toto further the correlation explore resultsthe correlation in Table 2between, the linear spec correlationtral parameters analysis and was plant carried functional out on traits, the accordingindicators to that the achieved correlation significant results correlationin Table 2, (Figurethe linear7). Figurecorrelation7 showed analysis the correlationwas carried outbetween on the different indicators spectral that achieved parameters significa with CCInt correlation and LT. The (Figure results 7). of Figure correlation 7 showed analysis the correlationbetween plant between functional different traits spectral and spectral parameters parameters with CCI show and thatLT. The they results show differentof corre- lationcorrelations. analysis The between reflectance plantof functional red valley trai hasts theand greatest spectral correlation parameters with show chlorophyll that they showcontent different (y = −65913.323x correlations. + 9.783,The reflectanceR2 = 0.6888), of red which valley indicate has the that greatest red edge correlation characteristics with chlorophyllwere very sensitive content (y to = parasitic −65913.323x infestation + 9.783, and R2 can= 0.6888), be used which to characterize indicate that changes red edge in Appl. Sci. 20212021,, 1111,, x 1937 FOR PEER REVIEW 1010 of of 15 15

characteristicschlorophyll content were very of Osmanthus sensitive fragransto parasiticunder infestation different and parasitic can be degrees. used to Accordingcharacterize to changesthe results in inchlorophyll Figure7, the content spectral of parameter Osmanthus model fragrans with under the highest different accuracy parasitic was degrees. selected. AccordingThen, a prediction to the results model in is Figure established 7, the with spectral the most parameter sensitive model spectral with parameters the highest as accu- inde- racypendent was variablesselected. Then, and chlorophyll a prediction content modelas is dependentestablished variable.with the Finally,most sensitive the accuracy spectral of parametersthe model was as independent further verified variables by analyzing and chlo therophyll predicted content and measuredas dependent values variable. calculated Fi- nally,by the the linear accuracy regression of the model model (Figure was furthe8). Asr verified shown inby Figureanalyzing8, the the chlorophyll predicted inversionand meas- uredmodel values of red calculated valley reflectance by the linear was tested, regressi andon it model was found (Figure that 8). the As prediction shown in accuracy Figure of8, thethis chlorophyll model was inversion high and stablemodel (ofR2 red= 0.8811, valley RMSEreflectance = 0.0004). was tested, and it was found that the prediction accuracy of this model was high and stable (R2 = 0.8811, RMSE = 0.0004). Table 2. Pearson correlation analysis between plant traits and spectral parameters. * indicates that the Tablecorrelation 2. Pearson reaches correlation a significant analysis level atbetween the level plant of p trai< 0.05.ts and and spectral ** indicates parameters. a significant * indicates correlation that thereaches correlation a significant reaches level a significant at the level level of p at< the 0.01. level of p < 0.05. and ** indicates a significant corre- lation reaches a significant level at the level of p < 0.01. RRV RGP RES RWSB RRV RGP RES RWSB LTLT 0.25218 0.25218 −0.1787−0.1787 −0.28318−0.28318 * * 0.09577 0.09577 − − LALA −0.016510.01651 0.18462 0.18462 −0.142920.14292 0.0353 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 LTDCCI −0.19553−0.82993 **0.17124 0.72953 ** 0.13662 0.65295 ** −−0.569670.01367 ** CCI −0.82993 ** 0.72953 ** 0.65295 ** −0.56967 **

Figure 7. Linear correlation between functional traits traits and and spectral spectral parameters. parameters. ( (aa)) the the reflection reflection of of red red valley valley (RRV) (RRV) and CCI, ( b)) the the reflectance reflectance of of green green peak peak (RGP) (RGP) and and CCI, CCI, ( (cc)) the the slope slope of of red red edge (RES) and and CCI, CCI, ( (d)) the the reflection reflection of of water stressstress band (RWSB) and CCI, (e) the reflectancereflectance ofof greengreen peakpeak (RGP)(RGP) andand LT.LT. Appl. Sci. 2021, 11, x 1937 FOR PEER REVIEW 11 of 15

FigureFigure 8. 8. TestTest of chlorophyll inversion model based on red valley reflectance.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 (Table3). There was a significant positive correlation between LA and SLA. There was a (Tablesignificant 3). There negative was correlationa significant between positive SLA correlation and LDMC between and LTD.LA and LA SLA. was significantlyThere was a significantnegatively negative correlated correlation with LDMC between and LTD. SLA There and LDMC was a significantand LTD. LA negative was significantly correlation negativelybetween LT correlated and LTD. with There LDMC was aand very LTD. significant There was positive a significant correlation negative between correlation LDMC betweenand LTD. LT There and wasLTD. a significantThere was positivea very sign correlationificant positive between correlation CCI and SLA. between At the LDMC same andtime, LTD. LT has There a negative was a significant correlation positive with SLA correlation and LA, butbetween the correlation CCI and SLA. has not At reachedthe same a time,significant LT has level. a negative correlation with SLA and LA, but the correlation has not reached a significant level. Table 3. Correlation between plant functional traits indicators. * indicates a significant correlation Tablebetween 3. Correlation functional traitsbetween at the plant level functional of p < 0.05, traits and in **dicators. indicates * indicates a significant a significant correlation 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.

LTLT LA SLASLA LDMCLDMC LTDLTD CCICCI LTLT 1 1 LALA −−0.16960.1696 1 SLASLA −−0.15020.1502 0.3581 * 1 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

StudiesStudies have have shown shown that leaf functional traits can reflect reflect the adaptability of plants to thethe environment,environment, butbut compared compared with with a single a single leaf leaf functional functional trait, trait, continuous continuous leaf economics leaf eco- nomicsspectrum spectrum can better can reflect better the reflect growth the strategy growth and strategy adaptation and mechanism adaptation of mechanism plants [54,55 of]. plantsIn this [54 study,,55]. thereIn this was study, an obviousthere was trade-off an obviou relationships trade-off between relationship the functional between the traits func- of tionalplant leaves,traits of which plant indicate leaves, thatwhich when indicate plants that are harmedwhen plants by parasitic are harmed plants, by host parasitic plants plants,show certain host plants ecological show trade-off certain ecological strategies trad in termse-off ofstrategies functional in traitsterms forof functional survival. SLA traits is forclosely survival. related SLA to is the closely growth related and survivalto the growth strategy and of survival plants, strategy which can of plants, represent which the canadaptability represent of the plants adaptability to the environment of plants to andthe theenvironment ability to obtainand the resources ability to [58 obtain]. In this re- sourcesstudy, after [58]. being In this invaded study, byafter parasitic being invade plants,d the by reduction parasitic ofplants, SLA ofthe the reduction host plants of SLA makes of thethe host plants plants adapt makes to resource-poor the plants adapt environment. to resource-poor LDMC represents environment. the plantsLDMC to represents maintain 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, smallsmall leaf area, specific small leaf specific area, low leaf chlorophyll area, low chlorophyll content index, content high index, dry matter high dry content and high matter contentleaf and tissue high leaf density. tissue Therefore, density. weTherefore, suspect we that suspect the leaf that economics the leaf spectrum economics may also exist in spectrum may thealso parasitic exist in environment,the parasitic en andvironment, there was and a general there trendwas a toward general “slow trend investment-return” to- ward “slow investment-return”type in the global type leaf economicsin the global spectrum leaf economics (Figure9 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,thus we fragrans studiedin different the spectral parasitic characteristics periods after andCuscuta leaf functional japonica traits Choisy ofinfection, Os- revealing manthus fragransthe in relationship different parasitic between periods the spectral after characteristicCuscuta japonica changes Choisy and infection, invasive re- processes after vealing the relationshiphost susceptibility. between In the addition, spectral by characteristic establishinga changes correlation and between invasive spectral pro- characteristic cesses after hostparameters susceptibility. and chlorophyllIn addition, content,by establishing the research a correlation results canbetween provide spectral theoretical support characteristic parametersfor the prediction and chlorophyll of plant diseases content, inthe the research early stage. results At can the provide same time, theo- it can provide a retical supportreference for the prediction for monitoring of plant and diseas earlyes warning in the early of infringement, stage. At the and same a new time, experimental it basis can provide a forreference different for measures monitoring to control and earlyCuscuta warning japonica of Choisyinfringement,. Main conclusions and a new are as follows. experimental basis(1) forThe different spectral measures reflectance to was control generally Cuscuta higher japonica before Choisy parasitism. Main conclu- than after parasitism. sions are as follows.There were four main reflection peaks and five main absorption valleys in the spectral (1) The spectralreflection reflectance curve was generally (350~1800 higher nm). before The near-infrared parasitism than band after (750~1400 parasit- nm) was the ism. There were foursensitive main reflection range of peaks spectral and responsefive main ofabsorption host plants valleys to parasitic in the spec- infection. At the tral reflection curve same(350~1800 time, nm). such The variation near-infrared characteristics band (750~1400 were universal nm) was under the sensi- different parasitic tive range of spectraldegree response conditions. of host plants to parasitic infection. At the same time, such variation characteristics(2) The positionwere universal of red edge, under slope different of red parasitic edge, reflectance degree conditions. of a green peak, and reflectance (2) The positionof of water red edge, stress slope band of can red well edge, reflect reflectance the invasion of a green status peak, in different and re- parasitic stages. flectance of water stressAfter parasitism,band can well the redreflec edget the position invasion of the status host in plant different spectrum parasitic shifted to shortwave stages. After parasitism,direction. the Withred edge the deepeningposition of of the parasitic host plant intensity, spectrum the moving shifted distance to of the red shortwave direction.edge With position the deepening to the short-wave of parasitic direction intensity, increases. the moving distance of the red edge position(3) toWith the shor the increaset-wave direction of parasitic increases. 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, R2 = 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 ). 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.

Abbreviations SLA-Specific leaf area, LDMC-Leaf dry matter content, CCI-Chlorophyll content index, LTD-Leaf tissue density, LT-Leaf thickness, LSFW-Leaf saturated fresh weight, LV-Leaf volume, LDW- Leaf dry weight, REP-Position of red edge, RES-Slope of red edge, RRV- Reflectance of red valley, RGP-Reflectance of green peak, GPP-Position of green peak, RWSB- Reflectance of water stress band, YES-Slope of yellow edge, YEP-Position of yellow edge.

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