Evaluation of Photosynthetic Performance and Adaptability of Grape Varieties in Arid Regions

Abstract

Photosynthetic characteristics are critical for grape growth and development. Drought conditions in arid regions significantly affect these characteristics. To identify grape varieties better suited for cultivation in arid environments, this study evaluated the leaf phenotypes and photosynthetic characteristics of 27 table grape varieties in Hotan Prefecture, China. Results revealed significant variations in leaf phenotypes and chlorophyll content (SPAD) among varieties under Hotan’s drought conditions. ‘Kyoho’ exhibited the largest leaf area (254.34 cm²), while ‘Munage’ had the smallest (112.43 cm²), and ‘Manaizi’ showed the highest chlorophyll content (SPAD = 44.21). ‘Munage’ and ‘Flame Seedless’ recorded the highest net photosynthetic rates (P_Nmax = 16.24 and 16.23 μmol·m⁻²·s⁻¹, respectively), while ‘Thompson Seedless’ had the lowest respiratory loss (R_D = 1.15 μmol·m⁻²·s⁻¹) and light compensation point (I_c = 22.41 μmol·m⁻²·s⁻¹), with a highly significant positive correlation between R_D and I_c. ‘Crimson Seedless’ exhibited the highest light saturation point (I_sat = 2745.15 μmol·m⁻²·s⁻¹). Chlorophyll fluorescence analysis indicated that ‘Autumn Black’ had the highest PSII photochemical yield (F_v/F_m = 0.84), while ‘Zicuiwuhe’ showed high energy transfer indices (PI_abs = 1.78, PI_total = 1.66) and electron transfer efficiency (φ_Eo = 0.39). PIabs was significantly correlated with F_v/F_m, F_v/F_o, and energy flux parameters. ‘Molixiang’ demonstrated superior energy utilization, with the highest light absorption (ABS/CSm = 2440.8) and electron transfer flux (ETo/CSm = 874) and the lowest energy dissipation (DIo/CSm = 455.8), supported by a negative correlation between energy dissipation (DIo/CSm) and photochemical efficiency (φ_Eo). Principal component analysis revealed that ‘Molixiang’ had the highest comprehensive photosynthetic adaptability score (0.97), followed by ‘Zicuiwuhe’ (0.79) and ‘Hetianhong’ (0.73), under Hotan’s drought stress conditions. These findings provide valuable insights for selecting and breeding grape varieties adapted to arid environments and climate change.

1. Introduction

Hotan Prefecture in Xinjiang has a long history of grape cultivation and is a significant grape-producing region. The primary grape varieties grown include ‘Hetianhong,’ ‘Thompson Seedless,’ and ‘Manaizi.’ In recent years, new varieties such as ‘Centennial Seedless,’ ‘Kunlunzi,’ and ‘Zitianwuhe’ have been introduced. Hotan Prefecture has an annual total solar radiation ranging from 5800 to 6200 MJ/m² and receives 2500 to 3100 h of sunshine. With a multi-year average temperature of 12.5 °C, average annual precipitation of 36.4 mm, and evaporation reaching 2618 mm, it is characterized as a typical inland temperate desert climate [1]. The climatic condition supports effective grape cultivation. However, climatic factors such as high temperature, low humidity and frequent sandstorms can significantly impact grape growth. Photosuppression and water stress significantly limit photosynthetic capacity, thereby affecting fruit quality and leading to uneven cultivation effects among different varieties.

Photosynthesis is a critical physiological process in plants, forming the foundation for their growth and development. It is closely associated with the plant’s growth environment [2] and serves as a key indicator for assessing the adaptability of introduced plant varieties, alongside yield and quality metrics. He et al. [3] found that photosynthetic parameters vary among grape varieties. The long days, intense light, and high temperatures in the Xinjiang region can induce stomatal closure in grape leaves, reducing the gas exchange rate and thereby inhibiting the photosynthetic rate. Brito et al. [4] comparatively analyzed the photosynthetic characteristics of three red varieties in the Demarcated Douro Region. The findings showed that, in the absence of effective light protection mechanisms, the lower light saturation point of certain grape varieties leads to photoinhibition under high-light conditions. Zsófi et al. [5] compared the growth performance of ‘Kekfrankos’ grapes in two different cultivation environments in the Eger wine region of Hungary and found that there were significant differences in the gas exchange capacity of grapes in the two regions. Severe drought conditions lead to reduced electron transfer, diminished RuBP regeneration capacity, oxidative stress damage, and other non-stomatal limitations. Consequently, grape varieties cultivated under varying environmental conditions exhibit differences in photosynthetic characteristics.

Chlorophyll fluorescence is an intrinsic parameter for examining the relationship between plant photosynthetic efficiency and environmental conditions, reflecting the rate and efficacy of photosynthesis [6]. The maximum photochemical quantum yield (F_v/F_m) of PSII reflects the relative contributions of PSII photochemical capacity and the thermal dissipation process to overall photochemical efficiency [7]. Liu et al. [8] revealed that as light intensity increases, the maximum photochemical quantum yield (F_v/F_m) of PSII steadily decreases. Tanase et al. [9] subjected three grape varieties, including ‘Augusta’, to drought treatment and found that drought stress directly affects the kinetics of chlorophyll fluorescence induction. For instance, temperature can cause changes in F_O and Fm, thereby influencing F_v/F_m. A decrease in the F_v/F_m ratio indicates the presence of stress conditions and fluorescence quenching mechanisms. Therefore, chlorophyll fluorescence parameters can reflect a plant’s tolerance to drought. Studying fluorescence kinetics facilitates real-time assessment of the light-capture ability of photosynthetic pigments and their tolerance to high photon flux density. Measuring the photosynthetic characteristics of leaves serves as an indicator of adaptation to environmental changes and provides a valuable method for predicting the potential for plant domestication [10].

This study evaluates the photosynthetic characteristics of 27 grape varieties cultivated in Hotan, compares their differences, assesses their climate adaptability, and identifies suitable varieties to provide a theoretical basis for grape introduction in the region.

2. Materials and Methods

2.1. Overview of the Experimental Site

The experiment was conducted at the Xinjiang Tianfeng Agriculture & Trade Industrial Co., Ltd. base in Yingbazha Village, Langan Township, Yutian County, Xinjiang (81°50′18″–81°50′36″ E, 36°68′75″–36°69′18″ N). This region is characterized by abundant light and heat resources, with annual sunshine hours ranging from 2500 to 3000 h and total solar radiation of 138.1–151.5 MJ/cm² [11]. The average annual temperature is 11.8 °C, with an effective accumulated temperature above 10 °C ranging from 4200 to 5000 °C [12]. The region experiences a frost-free period of 200 days, significant diurnal temperature variations, a dry climate, annual precipitation of 35.6 mm, and average annual evaporation of 2159–3137 mm [13]. The terrain is flat, and the soil is predominantly gravelly loam. During the growing season, soil and water management practices in the fields align with standard cultivation techniques.

2.2. Plant Materials and Cultivation

The experimental materials consisted of 27 table grape varieties from the Xinjiang Tianfeng Agriculture & Trade Industrial Co., Ltd., Hotan, China (

Table 1. 27 grape varieties in Hotan area.

Code	Cultivar	Parents	Type
1	Xinhongmeigui	Unknow	Eurasian hybrid
2	Jumeigui	Shenyangmeigui × Kyoho	Euro-American hybrid
3	Ruby Seedless	Emperor × Pirovan075	Eurasian hybrid
4	Xinyu	E42-6 × Rizamat	Eurasian hybrid
5	Heibaladuo	Beni Balad × Yoneyama	Eurasian hybrid
6	Shine Muscat	Akitsu-21 × Hakunan	Euro-American hybrid
7	Flame Seedless	Unknow	Eurasian hybrid
8	B2		Eurasian hybrid
9	Zuijinxiang	7601 × Kyoho	Euro-American hybrid
10	Manicure Finger	Unicorn × Baladi No.2	Eurasian hybrid
11	Summer Black	Kyoho × Thompson Seedless	Euro-American hybrid
12	Bixiangwuhe	1851 × Pearl of Csaba	Eurasian hybrid
13	Heicuiwuhe	Unknow	Eurasian hybrid
14	Zicuiwuhe	Niunai × Autumn Royal	Eurasian hybrid
15	Moldova	Guzali Kala × SV12375	Euro-American hybrid
16	Centennial Seedless	Gold × Q25-6	Eurasian hybrid
17	Kunlunzi		Eurasian hybrid
18	Kyoho	Ishihara Wase × Centennial	Euro-American hybrid
19	Hetianhong		Eurasian hybrid
20	Hongyuwuhe		Eurasian hybrid
21	Thompson Seedless		Eurasian hybrid
22	Zitianwuhe	Niunai × Autumn Royal	Eurasian hybrid
23	Munage		Eurasian hybrid
24	Manaizi		Eurasian hybrid
25	Crimson Seedless	Emperor × C33-199	Eurasian hybrid
26	Autumn Black	Manicure Finger × Black Rose	Eurasian hybrid
27	Molixiang	Delaware × Royal Rose	Euro-American hybrid

), all planted in 2019. The vines were spaced at 0.7 m × 3 m. A “factory-shaped” pruning method and a “V-shaped” leaf canopy were employed. For each variety, three plants with similar and vigorous growth were selected, with three replicates per variety.

2.3. Determination of P_N-PAR Response Curve

During the fruit color change period (July to August), from 9:30 to 12:30, a HANSA CIRAS-3 portable photosynthesis system (Hansha Scientific Instruments Co., Ltd., Taian, China) was used outdoors. For each variety, three disease-free plants with moderate growth vigor were selected. From each plant, three leaves were sampled from new shoots, chosen from the 5th to 7th nodes, facing the sun, of similar size, and free from diseases and pests. These mature, functional leaves were measured using an artificial light source leaf chamber, with the chamber temperature set to match ambient conditions. The photosynthetically active radiation (PAR) was set at 10 gradients: 0, 75, 150, 300, 500, 750, 1000, 1500, 2000, and 2500 µmol·m⁻²·s⁻¹. The light response curve was fitted using the right-angle hyperbola correction model [14], and the following parameters were calculated: dark respiration rate (R_D), maximum net photosynthetic rate (P_Nmax), light saturation point (I_sat), light compensation point (I_C), and apparent quantum yield (AQY).

2.3.1. Chlorophyll Fluorescence Parameters Measurement

Chlorophyll fluorescence parameters were measured using a Handy PEA continuous excitation fluorometer (Hansha Scientific Instruments Co., Ltd., Taian, China). Measurements were conducted from 9:00 to 20:00 in late July. The chlorophyll fluorescence parameters was determined using the same leaves as those determined by the P_N-PAR response curve. Prior to measurement, grape leaves were dark-adapted for 30 min, after which chlorophyll fluorescence parameters were recorded.

2.3.2. Method of SPAD Values and Leaf Phenotypes

During the fruit color transition period (July to August), chlorophyll content was measured using a SPAD-502 chlorophyll meter (Konica Minolta, Tokyo, Japan). For each variety, three disease-free plants with moderate growth vigor were selected. From each plant, five new shoots were randomly sampled, and one leaf from the 5th to 7th internodes was collected, prioritizing sunward-facing leaves of similar size without pest or disease symptoms. The SPAD value was measured at three different positions on each leaf. Additionally, leaf length and width were measured using a vernier caliper. Leaf length is defined as the straight-line distance from the base of the petiole depression to the leaf tip (excluding the petiole), while leaf width is the straight-line distance across the widest part of the leaf, perpendicular to the main vein. Leaf area was calculated using ImageJ software (version 1.53t, developed by Wayne Rasband).

2.4. Data Processing

Data collation and statistical analyses were performed using Microsoft Excel 2019. Duncan’s multiple range test and correlation analyses were conducted using SPSS (version 27.0, IBM Corp., Chicago, IL, USA). Graphs were generated using Origin 2021 software (OriginLab Corp., Northampton, MA, USA). Leaf photographs were processed using Adobe Photoshop 2025 (Adobe Inc., San Jose, CA, USA).

3. Results

3.1. Leaf Phenotypes and SPAD Values

As shown in Figure 1 and

Table 2. Leaf phenotype and SPAD value of 27 grape varieties in Hotan area.

Cultivar	Leaf Length (cm)	Leaf Width (cm)	Leaf Area (cm2)	SPAD
Xinhong meigui	11.76 ± 1.62 cdefgh	15.8 ± 0.79 def	175.19 ± 0.24 cdefghi	35.83 ± 3.3 cdef
Jumeigui	12.14 ± 1.47 cdefgh	15.32 ± 1.58 defg	191.64 ± 13.29 bcdef	41.62 ± 3.08 bcd
Ruby Seedless	13.96 ± 1.79 b	15.72 ± 1.93 def	178.21 ± 9.56 cdefgh	35.41 ± 2.18 ijk
Xinyu	12.46 ± 0.78 bcdefg	16.26 ± 0.96 bcde	149.27 ± 14.44 fghijkl	38.79 ± 1.64 fgh
Heibaladuo	12.76 ± 0.74 bcdef	16.4 ± 1.03 bcde	163.96 ± 10.32 cdefghi	39.09 ± 2.92 efg
Shine Muscat	11 ± 0.31 fghij	14.6 ± 1.75 efgh	138.14 ± 14.2 ghijkl	41.17 ± 2.21 bcde
Flame Seedless	12.2 ± 0.83 bcdefgh	15 ± 1.45 efgh	169.44 ± 14.48 cdefghi	41.96 ± 3.44 bc
B2	11.7 ± 0.7 defghi	15.76 ± 0.91 def	157.79 ± 14.98 efghij	32.05 ± 1.74 l
Zuijinxiang	12.46 ± 0.88 bcdefg	14.02 ± 0.37 fghi	153.79 ± 7.02 fghijkl	33.59 ± 3.07 kl
Manicure Finger	11.68 ± 1.06 defghi	14.7 ± 1.53 efgh	168.65 ± 33.8 cdefghi	28.57 ± 1.35 m
Summer Black	12.62 ± 0.86 bcdef	16.74 ± 0.88 bcde	197.55 ± 12.17 bcde	36.83 ± 4.69 hij
Bixiang wuhe	9.8 ± 0.99 j	15.34 ± 1.65 defg	132.91 ± 31.59 ijkl	34.9 ± 1.85 jk
Heicui wuhe	10.7 ± 1.31 ghij	15.04 ± 1.76 efgh	136.34 ± 1.31 hijkl	32.89 ± 1.01 l
Zicui wuhe	10.58 ± 0.63 hij	15.9 ± 1.87 cdef	164.4 ± 17.57 cdefghi	37.46 ± 5.18 ghi
Moldova	11.02 ± 0.99 fghij	13.52 ± 1.33 ghi	154.33 ± 16.39 fghijk	40.41 ± 2.19 cdef
Centennial Seedless	13.48 ± 1.04 bcd	18.06 ± 1.44 ab	219.42 ± 26.78 ab	41.27 ± 2.36 ij
Kunlunzi	12.9 ± 1.22 bcde	18.08 ± 1.73 ab	202.71 ± 27.01 bcd	37.37 ± 2.36 ghi
Kyoho	15.56 ± 1.6 a	19.44 ± 1.92 a	254.34 ± 49.06 a	43.22 ± 2.35 ab
Hetianhong	9.96 ± 1.14 ij	12.42 ± 1.24 i	113.33 ± 20.21 kl	41.72 ± 2.24 bcd
Hongyu wuhe	11.08 ± 0.87 efghij	13.18 ± 0.54 hi	118.52 ± 5.68 jkl	34.95 ± 2.94 jk
Thompson Seedless	13.54 ± 1.12 bc	15.72 ± 1.8 def	180.75 ± 13.77 bcdefg	35.99 ± 1.68 ij
Zitian wuhe	12.02 ± 2.05 cdefgh	17.9 ± 1.8 abc	205.52 ± 38.24 bc	39.55 ± 2.99 def
Munage	9.38 ± 1.23 j	12.24 ± 1.22 i	112.43 ± 4.67 l	39.93 ± 2.81 bcde
Manaizi	11.98 ± 1.89 cdefgh	15.12 ± 1.79 defgh	161.65 ± 36.38 defghi	44.21 ± 3.04 a
Crimson Seedless	12.42 ± 0.86 bcdefg	17.26 ± 1.04 bcd	180.69 ± 30.58 bcdefg	36.47 ± 2.68 ij
Autumn Black	11.54 ± 0.91 efghi	13.76 ± 0.88 fghi	136.77 ± 11.21 hijkl	39.88 ± 1.67 cdef
Molixiang	12.46 ± 1.39 bcdefg	15.88 ± 1.82 cdef	164.78 ± 12.06 cdefghi	40.86 ± 1.04 cdef

After Duncan’s test, different lowercase letters indicated significant differences (p < 0.05), while the same lowercase letters indicated no significant differences.

, the leaf length of 27 grape varieties ranges from 9.38 to 15.56 cm. ‘Kyoho’ has the longest leaves at 15.56 cm, while ‘Munage’ and ‘Bixiangwuhe’ have the shortest at 9.38 cm and 9.80 cm, respectively. Leaf width varies from 12.24 to 19.44 cm, with ‘Kyoho’ having the widest leaves at 19.44 cm and ‘Munage’ the narrowest at 12.24 cm. Leaf area ranges from 112.43 to 254.34 cm², with ‘Kyoho’ exhibiting the largest leaf area at 254.34 cm² and ‘Munage’ the smallest at 112.43 cm². Chlorophyll content, which reflects the plant’s photosynthetic capacity and physiological condition, varies across the varieties. The SPAD values of the leaves range from 27.57 to 44.21, with ‘Manaizi’ having the highest value at 44.21 and ‘Manicure Finger’ the lowest at 28.57.

3.2. Photosynthetic Parameters of Leaves

As shown in Figure 2, the light response curves of 27 grape varieties exhibit a consistent trend. Net photosynthetic rates (PN) increase with rising light intensity and effective radiation, reaching a saturation point beyond which they stabilize. When the photosynthetic photon flux density (PPFD) ranges from 0 to 300 μmol·m⁻²·s⁻¹, PN values show a steady increase. Beyond this range, the rate of increase slows. The PN values of ‘Flame Seedless’ are generally higher than those of other varieties. When PPFD exceeds 1600 μmol·m⁻²·s⁻¹, the PN values of ‘Xinyu’ and ‘Hetianhong’ begin to decline, indicating an earlier turning point compared to other varieties. The intercellular CO₂ concentration (Ci) of leaves decreases as light intensity and effective radiation increase. Among the varieties, ‘Jumeigui’ and ‘Kunlunzi’ exhibit higher Ci values than others. Stomatal conductance (Gs) varies among varieties, with ‘Molixiang’ showing the highest Gs value. Transpiration rate (Tr) curves for the leaves of each variety initially increase and then slightly decrease or stabilize. ‘Moldova’ has the highest Tr value, while ‘Xinyu’ has the lowest. Water use efficiency (WUE) is highest in ‘Thompson Seedless’ and lowest in ‘Kunlunzi.’

As shown in

Table 3. P_N-PAR response curve parameters of 27 grape varieties in Hotan area.

Cultivar	RD (μmol·m−2·s−1)	PNmax (μmol·m−2·s−1)	Isat (μmol·m−2·s−1)	IC (μmol·m−2·s−1)	AQY
Xinhong meigui	1.83 ± 0.13 def	15.45 ± 4 ab	1676.63 ± 189.78 c	45.09 ± 20.95 def	0.029 ± 0.015 abcde
Jumeigui	3.29 ± 1 abc	6.98 ± 2.1 fg	1875.15 ± 375.45 abc	101.46 ± 43.34 ab	0.03 ± 0.003 abcde
Ruby Seedless	2.09 ± 0.32 bcdef	10.64 ± 0.61 bcdefg	2379.14 ± 688.67 abc	55.08 ± 5.39 cdef	0.028 ± 0.003 bcdef
Xinyu	1.49 ± 0.67 ef	8.33 ± 2.03 efg	1575.42 ± 274.7 c	30.51 ± 13.19 ef	0.027 ± 0.002 bcdef
Heibaladuo	1.48 ± 1.18 ef	6.3 ± 0.95 g	1777.02 ± 143.65 bc	46.59 ± 44.62 cdef	0.018 ± 0.002 f
Shine Muscat	2.13 ± 0.29 bcdef	10.56 ± 1.58 bcdefg	1681.86 ± 194.98 c	44.91 ± 9.06 def	0.033 ± 0.003 abcde
Flame Seedless	2.69 ± 0.93 abcde	16.23 ± 5.44 a	2350.07 ± 898.15 abc	58.4 ± 31.97 bcdef	0.034 ± 0.009 abcd
B2	3.38 ± 0.13 ab	8.01 ± 3.16 fg	2317.52 ± 754.79 abc	112.52 ± 8.31 a	0.0267 ± 0.003 cdef
Zuijinxiang	2.05 ± 0.9 bcdef	9.97 ± 1.91 cdefg	2370.9 ± 793.13 abc	53.51 ± 17.6 cdef	0.028 ± 0.003 bcdef
Manicure Finger	1.82 ± 0.76 def	7.86 ± 2.45 fg	1982.48 ± 94.07 abc	44.54 ± 20.59 def	0.027 ± 0.002 bcdef
Summer Black	1.58 ± 0.71 ef	7.21 ± 1.03 fg	1876.66 ± 303.06 abc	42.36 ± 16.33 def	0.022 ± 0.003 ef
Bixiang wuhe	2.53 ± 0.86 abcdef	8.78 ± 1.77 efg	2427.97 ± 117.17 abc	70.78 ± 22.65 abcde	0.027 ± 0.005 cdef
Heicui wuhe	1.56 ± 0.56 ef	9.78 ± 1.96 cdefg	1753.81 ± 589.13 bc	32.85 ± 15.34 ef	0.031 ± 0.011 abcde
Zicui wuhe	3.2 ± 0.73 abcd	11.27 ± 2.02 abcdefg	2063.92 ± 493.08 abc	70.39 ± 18.29 abcde	0.028 ± 0.005 bcdef
Moldova	2.83 ± 0.21 abcde	14.68 ± 3.75 abc	2144.93 ± 323.82 abc	58.68 ± 10.66 bcdef	0.035 ± 0.006 abcd
Centennial Seedless	2.68 ± 0.6 abcde	9.26 ± 1.33 defg	1747.48 ± 219.88 bc	62.54 ± 21.94 bcdef	0.035 ± 0.001 abcd
Kunlunzi	2.72 ± 0.39 abcde	6.95 ± 1.4 fg	1818.08 ± 422.82 abc	82.66 ± 39.06 abcd	0.025 ± 0.004 def
Kyoho	3.66 ± 1.12 a	11.95 ± 4.16 abcdef	1857.32 ± 136.86 abc	92.2 ± 42.97 abc	0.032 ± 0.0093 abcde
Hetianhong	2.51 ± 0.75 abcdef	11.23 ± 1.51 abcdefg	1554.89 ± 98.29 c	48.94 ± 14.21 cdef	0.037 ± 0.0018 abc
Hongyu wuhe	2.54 ± 1.1 abcdef	9.41 ± 2.05 defg	1934.38 ± 561.64 abc	67.21 ± 40.43 bcdef	0.037 ± 0.0046 abc
Thompson Seedless	1.15 ± 0.91 f	11.91 ± 2.05 abcdef	1776.84 ± 97.32 bc	22.41 ± 15.69 f	0.034 ± 0.0074 abcd
Zitian wuhe	1.55 ± 0.58 ef	12.1 ± 1.84 abcdef	2047.34 ± 679.49 abc	33.17 ± 13.57 ef	0.034 ± 0.0022 abcd
Munage	2.16 ± 0.48 bcdef	16.24 ± 5.22 a	2672.87 ± 811.76 ab	49.73 ± 5.36 cdef	0.031 ± 0.008 abcde
Manaizi	1.83 ± 1.11 def	10.39 ± 2.36 bcdefg	1820.84 ± 105.01 abc	34.56 ± 18.31 ef	0.033 ± 0.005 abcde
Crimson Seedless	1.56 ± 0.39 ef	11.44 ± 1.83 abcdefg	2745.15 ± 50.69 a	34.64 ± 4.66 ef	0.031 ± 0.004 abcde
Autumn Black	2.55 ± 0.4 abcdef	14.4 ± 3.47 abcd	1909.5 ± 391.59 abc	48.34 ± 10.31 cdef	0.039 ± 0.007 ab
Molixiang	1.88 ± 0.57 cdef	13.45 ± 0.22 abcde	2237.81 ± 870.03 abc	37.7 ± 11.27 def	0.041 ± 0.004 a

After Duncan’s test, different lowercase letters indicated significant differences (p < 0.05), while the same lowercase letters indicated no significant differences.

, significant differences (p < 0.05) exist among the 27 grape varieties in photosynthetic parameters, including dark respiration rate (R_D), maximum net photosynthetic rate (P_Nmax), light saturation point (I_sat), light compensation point (I_C), and apparent quantum yield (AQY). ‘Thompson Seedless’ has a lower dark respiration rate and light compensation point than other varieties, at 1.15 μmol·m⁻²·s⁻¹ and 22.41 μmol·m⁻²·s⁻¹, respectively. ‘Munage’ and ‘Flame Seedless’ exhibit the highest P_Nmax values, at 16.24 μmol·m⁻²·s⁻¹ and 16.23 μmol·m⁻²·s⁻¹, respectively, while ‘Heibaladuo’ has the lowest, at 6.3 μmol·m⁻²·s⁻¹. ‘Crimson Seedless’ has a higher light saturation point than other varieties, reaching 2745.15 μmol·m⁻²·s⁻¹, whereas ‘Shine Muscat’, ‘Xinhongmeigui’, ‘Hetianhong’, and ‘Xinyu’ have the lowest, at 1681.86 μmol·m⁻²·s⁻¹, 1676.63 μmol·m⁻²·s⁻¹, 1554.89 μmol·m⁻²·s⁻¹, and 1575.42 μmol·m⁻²·s⁻¹, respectively. ‘Molixiang’ demonstrates a higher apparent quantum yield than other varieties, exceeding that of ‘Heibaladuo’ by 23%.

3.3. Chlorophyll Fluorescence Parameters and Performance Index of Leaves

As shown in

Table 4. Leaf chlorophyll parameters and performance indices of 27 grape varieties in Hotan area.

Cultivar	Fv/Fm	Fv/FO	PIabs	PItotal
Xinhong meigui	0.76 ± 0.02 ghi	3.22 ± 0.38 ghi	0.66 ± 0.23 gh	0.43 ± 0.16 g
Jumeigui	0.8 ± 0.05 abcdefg	4.31 ± 1.08 abcde	1.36 ± 0.59 abcdef	0.97 ± 0.55 bcdefg
Ruby Seedless	0.79 ± 0.04 bcdefgh	3.89 ± 0.81 cdefgh	1.05 ± 0.64 bcdefgh	1.12 ± 0.65 abcdef
Xinyu	0.81 ± 0.03 abcde	4.31 ± 0.88 abcde	1.45 ± 0.71 abc	1.5 ± 0.46 abcd
Heibaladuo	0.78 ± 0.02 cdefgh	3.66 ± 0.54 cdefghi	0.78 ± 0.38 efgh	0.75 ± 0.39 efg
Shine Muscat	0.77 ± 0.01 efgh	3.33 ± 0.18 fghi	0.67 ± 0.08 gh	0.91 ± 0.17 cdefg
Flame Seedless	0.81 ± 0.02 abcd	4.46 ± 0.67 abcd	1.11 ± 0.37 bcdefgh	0.83 ± 0.11 efg
B2	0.83 ± 0.02 ab	4.9 ± 0.62 ab	1.65 ± 0.65 ab	1.22 ± 0.3 abcde
Zuijinxiang	0.77 ± 0.03 efgh	3.41 ± 0.6 fghi	0.78 ± 0.42 efgh	0.85 ± 0.34 efg
Manicure Finger	0.8 ± 0.01 abcdefg	4.08 ± 0.22 bcdefg	1.04 ± 0.12 bcdefgh	0.9 ± 0.13 defg
Summer Black	0.72 ± 0.08 i	2.82 ± 1 i	0.58 ± 0.53 h	1.1 ± 0.49 abcdef
Bixiang wuhe	0.76 ± 0.02 hi	3.15 ± 0.37 hi	0.81 ± 0.23 defgh	1.06 ± 0.32 abcdefg
Heicui wuhe	0.76 ± 0.05 hi	3.23 ± 0.74 ghi	1.01 ± 0.56 cdefgh	0.97 ± 0.4 bcdefg
Zicui wuhe	0.82 ± 0.02 abcd	4.46 ± 0.49 abcd	1.78 ± 0.31 a	1.66 ± 0.25 a
Moldova	0.79 ± 0.03 bcdefgh	3.83 ± 0.58 cdefgh	0.74 ± 0.26 fgh	1.37 ± 0.51 abcde
Centennial Seedless	0.81 ± 0.03 abcd	4.48 ± 0.79 abcd	1.3 ± 0.63 abcdefg	1.1 ± 0.54 abcdef
Kunlunzi	0.77 ± 0.03 defgh	3.46 ± 0.52 efghi	0.69 ± 0.26 gh	1.16 ± 0.3 abcdef
Kyoho	0.76 ± 0.05 fgh	3.38 ± 0.91 fghi	1.04 ± 0.62 bcdefgh	1.59 ± 1.05 ab
Hetianhong	0.83 ± 0.01 ab	5.02 ± 0.3 a	1.43 ± 0.24 abcd	1.55 ± 0.16 abc
Hongyu wuhe	0.79 ± 0.01 cdefgh	3.67 ± 0.15 cdefghi	0.84 ± 0.17 cdefgh	1.03 ± 0.36 abcdefg
Thompson Seedless	0.78 ± 0.02 cdefgh	3.63 ± 0.31 defghi	0.95 ± 0.27 cdefgh	1.51 ± 0.32 abcd
Zitian wuhe	0.81 ± 0.01 abcdef	4.15 ± 0.31 bcdef	1.12 ± 0.22 bcdefgh	1.35 ± 0.25 abcde
Munage	0.8 ± 0.01 abcdefg	4.14 ± 0.29 bcdef	1.13 ± 0.24 bcdefgh	1.05 ± 0.26 abcdefg
Manaizi	0.77 ± 0.01 efgh	3.31 ± 0.17 fghi	0.86 ± 0.24 cdefgh	0.55 ± 0.48 fg
Crimson Seedless	0.82 ± 0.02 abc	4.52 ± 0.55 abc	1.41 ± 0.44 abcde	1.04 ± 0.58 abcdefg
Autumn Black	0.84 ± 0.01 a	5.12 ± 0.23 a	1.42 ± 0.41 abcd	0.8 ± 0.33 efg
Molixiang	0.81 ± 0.01 abcd	4.36 ± 0.17 abcd	1.4 ± 0.15 abcde	1.39 ± 0.21 abcde

F_v/F_m: Maximum photoelectrochemical quantum yield of PSII; F_v/F_O: photochemical efficiency; PI_abs: Performance index based on absorption of light energy; PI_total: The performance index of the transfer of light energy absorbed from PSII to the reduction of PSI end electron acceptors. After Duncan’s test, different lowercase letters indicated significant differences (p < 0.05), while the same lowercase letters indicated no significant differences.

, significant differences (p < 0.05) exist among the 27 grape varieties in the chlorophyll fluorescence parameters F_v/F_m, F_v/F_o, PI_abs, and PI_total. ‘Autumn Black’ exhibits the highest F_v/F_m and F_v/F_o values, at 0.84 and 5.12, respectively, followed by ‘Hetianhong’ with 0.83 and 5.02. ‘Summer Black’ has the lowest F_v/F_m and F_v/F_o values, at 0.72 and 2.82, respectively. ‘Zicuiwuhe’ shows the highest PI_abs and PI_total values, at 1.78 and 1.66, respectively. ‘Xinhongmeigui’ has the lowest PI_total value, at 0.43.

3.4. Blade JIP-Test Parameters

As shown in

Table 5. Parameters of JIP-test for 27 grape varieties in Hotan area.

Cultivar	VJ	VI	φEo	dV/dto
Xinhong meigui	0.62 ± 0.07 abcde	0.86 ± 0.03 a	0.29 ± 0.06 bcdefg	1.44 ± 0.13 ab
Jumeigui	0.57 ± 0.04 cdef	0.83 ± 0.05 abcde	0.35 ± 0.05 abcd	1.16 ± 0.12 cde
Ruby Seedless	0.62 ± 0.1 abcde	0.8 ± 0.05 cdefgh	0.3 ± 0.09 abcdefg	1.29 ± 0.23 abcd
Xinyu	0.56 ± 0.06 def	0.78 ± 0.03 efgh	0.35 ± 0.06 abc	1.13 ± 0.14 cde
Heibaladuo	0.66 ± 0.08 abc	0.84 ± 0.05 abcd	0.27 ± 0.07 defg	1.36 ± 0.19 abcd
Shine Muscat	0.66 ± 0.01 abc	0.81 ± 0.02 abcdefg	0.26 ± 0.01 efg	1.31 ± 0.08 abcd
Flame Seedless	0.63 ± 0.04 abcde	0.84 ± 0.01 abcd	0.31 ± 0.04 abcdefg	1.27 ± 0.09 abcd
B2	0.55 ± 0.04 ef	0.81 ± 0.01 abcdefg	0.37 ± 0.04 a	1.17 ± 0.16 cde
Zuijinxiang	0.65 ± 0.08 abcd	0.82 ± 0.03 abcdef	0.27 ± 0.07 cdefg	1.31 ± 0.2 abcd
Manicure Finger	0.58 ± 0.01 cdef	0.81 ± 0.02 bcdefg	0.34 ± 0.01 abcde	1.34 ± 0.06 abcd
Summer Black	0.69 ± 0.12 a	0.8 ± 0.04 cdefg	0.23 ± 0.11 g	1.47 ± 0.29 a
Bixiang wuhe	0.6 ± 0.02 bcdef	0.77 ± 0.01 fgh	0.31 ± 0.02 abcdefg	1.22 ± 0.09 bcd
Heicui wuhe	0.59 ± 0.12 bcdef	0.8 ± 0.04 defgh	0.31 ± 0.1 abcdefg	1.18 ± 0.25 cde
Zicui wuhe	0.53 ± 0.01 f	0.77 ± 0.03 fgh	0.39 ± 0.01 a	0.98 ± 0.05 e
Moldova	0.68 ± 0.04 ab	0.79 ± 0.03 defgh	0.25 ± 0.04 fg	1.37 ± 0.13 abc
Centennial Seedless	0.6 ± 0.08 bcdef	0.82 ± 0.03 abcdef	0.33 ± 0.07 abcdef	1.25 ± 0.22 abcd
Kunlunzi	0.64 ± 0.04 abcde	0.78 ± 0.02 efgh	0.27 ± 0.04 bcdefg	1.46 ± 0.14 a
Kyoho	0.6 ± 0.08 bcdef	0.76 ± 0.06 gh	0.31 ± 0.08 abcdefg	1.18 ± 0.24 cde
Hetianhong	0.6 ± 0.03 bcdef	0.79 ± 0.01 defgh	0.34 ± 0.03 abcdef	1.2 ± 0.05 cde
Hongyu wuhe	0.64 ± 0.04 abcde	0.81 ± 0.04 abcdefg	0.27 ± 0.03 bcdefg	1.24 ± 0.09 abcd
Thompson Seedless	0.59 ± 0.04 bcdef	0.75 ± 0.02 h	0.32 ± 0.04 abcdef	1.26 ± 0.13 abcd
Zitian wuhe	0.61 ± 0.03 abcdef	0.79 ± 0.02 defgh	0.31 ± 0.03 abcdefg	1.18 ± 0.08 cde
Munage	0.61 ± 0.03 abcdef	0.81 ± 0.02 abcdefg	0.31 ± 0.03 abcdefg	1.16 ± 0.1 cde
Manaizi	0.56 ± 0.07 def	0.86 ± 0.08 ab	0.34 ± 0.05 abcdef	1.32 ± 0.13 abcd
Crimson Seedless	0.57 ± 0.05 cdef	0.82 ± 0.05 abcdef	0.35 ± 0.05 abcd	1.18 ± 0.15 cde
Autumn Black	0.59 ± 0.04 bcdef	0.85 ± 0.02 abc	0.34 ± 0.04 abcde	1.29 ± 0.19 abcd
Molixiang	0.56 ± 0.01 def	0.78 ± 0.01 efgh	0.36 ± 0.01 ab	1.12 ± 0.07 de

V_J: relative variable fluorescence at point j; V_I: i point relative variable fluorescence; φ_Eo: The quantum yield of energy absorption used for electron transfer at t = 0; dV/dt_o: The rate of QA reduction. After Duncan’s test, different lowercase letters indicated significant differences (p < 0.05), while the same lowercase letters indicated no significant differences.

, significant differences (p < 0.05) exist among 27 grape varieties in the chlorophyll fluorescence parameters V_J, V_I, φ_Eo, and dV/dt_o. ‘Summer Black’ exhibits the highest V_J value, which is 30.19% higher than the lowest, observed in ‘Zicuiwuhe.’ ‘Xinhongmeigui’ has the highest V_I value, which is 14.67% higher than the lowest, recorded for ‘Thompson Seedless.’ ‘Zicuiwuhe’ shows the highest φ_Eo value, which is 41.03% higher than the lowest, found in ‘Summer Black.’ Conversely, ‘Zicuiwuhe’ has the lowest dV/dt_o value, which is 33.33% lower than the highest, observed in ‘Summer Black.’

3.5. Energy Flux Parameter per Unit Area of Leaf Photosynthetic Object

As shown in

Table 6. Energy flux parameters of photosynthetic objects per unit area of 27 grape varieties in Hotan area.

Cultivar	ABS/CSm	DIo/CSm	TRo/CSm	ETo/CSm	REo/CSm
Xinhong meigui	1810.6 ± 103.09 e	430 ± 23.49 bcd	1380.6 ± 114.25 f	523 ± 121.7 fg	194 ± 40.4 f
Jumeigui	2422.6 ± 350.18 a	463.2 ± 51.66 bcd	1959.4 ± 378.27 a	852.2 ± 236.02 ab	344 ± 146.2 abcd
Ruby Seedless	2357.8 ± 171.1 ab	491 ± 69.84 b	1866.8 ± 205.02 ab	722.4 ± 256.95 abcdefg	375 ± 123.65 abcd
Xinyu	2313.8 ± 272.56 ab	438.8 ± 30.01 bcd	1875 ± 297.45 ab	830 ± 238.97 abc	418.8 ± 80.28 ab
Heibaladuo	2241.4 ± 173.81 abc	483.8 ± 47.71 b	1757.6 ± 171.69 abcde	601.4 ± 168.84 cdefg	284.8 ± 88.02 def
Shine Muscat	2019.4 ± 106.3 cde	466.2 ± 18.78 bcd	1553.2 ± 95.42 def	524.6 ± 39.51 efg	301.2 ± 30.41 cdef
Flame Seedless	2449.2 ± 310.09 a	448.2 ± 19.27 bcd	2001 ± 304.56 a	757 ± 183.16 abcde	324.8 ± 48.11 abcd
B2	2314.6 ± 164.12 ab	393.8 ± 27.62 d	1920.8 ± 166.75 a	864.6 ± 136.94 a	371.4 ± 40.96 abcd
Zuijinxiang	2003.8 ± 139.94 cde	460.6 ± 62.52 bcd	1543.2 ± 142.54 def	543.8 ± 156.18 efg	284.8 ± 66.15 def
Manicure Finger	2236.2 ± 155.94 abc	440 ± 24.77 bcd	1796.2 ± 137.81 abcde	755.6 ± 68.42 abcdef	348.6 ± 21.05 abcd
Summer Black	2091.5 ± 231.49 bcd	565.5 ± 94.7 a	1526 ± 316.89 ef	504 ± 277.48 g	308.5 ± 125.73 bcde
Bixiang wuhe	1929.8 ± 145.69 de	466.2 ± 22.4 bcd	1463.6 ± 145.86 f	591.6 ± 81.14 defg	334.8 ± 44.3 abcd
Heicui wuhe	2020.33 ± 239.49 cde	482.67 ± 37.43 b	1537.67 ± 270.1 def	654.83 ± 261.96 abcdefg	320.33 ± 97.27 abcde
Zicui wuhe	2218.2 ± 219.76 abc	406.4 ± 10.85 cd	1811.8 ± 215.4 abcd	858.8 ± 115.92 a	411.6 ± 27.77 abc
Moldova	2272.6 ± 130.57 abc	476.2 ± 66.04 bc	1796.4 ± 126.79 abcde	574.8 ± 88.13 efg	371 ± 67.19 abcd
Centennial Seedless	2268.2 ± 158.97 abc	419.4 ± 52.19 bcd	1848.8 ± 173.55 abc	750.6 ± 187.76 abcdef	343 ± 75.61 abcd
Kunlunzi	2021.4 ± 124.44 cde	455.4 ± 27.99 bcd	1566 ± 147.3 def	569 ± 114.99 efg	349.6 ± 43.18 abcd
Kyoho	2323.4 ± 162.36 ab	553.8 ± 144.63 a	1769.6 ± 112.33 abcde	716.4 ± 166.41 abcdefg	425.4 ± 118.85 ab
Hetianhong	2404.8 ± 38.17 a	400.2 ± 15.39 d	2004.6 ± 50.61 a	811.6 ± 72.54 abcd	420.6 ± 21.3 ab
Hongyu wuhe	2046 ± 110.83 cde	438.6 ± 37.35 bcd	1607.4 ± 74.05 bcdef	571.2 ± 31.99 efg	308.8 ± 50.02 bcde
Thompson Seedless	2029 ± 109.57 cde	439 ± 17.07 bcd	1590 ± 111.31 cdef	650 ± 99.68 abcdefg	396.6 ± 38.2 abcd
Zitian wuhe	2372.4 ± 179.23 a	460.6 ± 17.99 bcd	1911.8 ± 168.49 a	748 ± 107.23 abcdef	404.2 ± 32.21 abc
Munage	2215.2 ± 143.99 abc	431.6 ± 22.76 bcd	1783.6 ± 133.4 abcde	692 ± 82.91 abcdefg	330 ± 41.59 abcd
Manaizi	1861.6 ± 171.22 de	432.6 ± 43.26 bcd	1429 ± 131.94 f	622.2 ± 65.5 bcdefg	210.8 ± 142.57 ef
Crimson Seedless	2389.4 ± 160.49 a	436.4 ± 50.01 bcd	1953 ± 151.48 a	840.6 ± 125.56 ab	342.6 ± 82.52 abcd
Autumn Black	2434.4 ± 104.65 a	397.6 ± 7.06 d	2036.8 ± 101.69 a	837.6 ± 103.7 ab	298.8 ± 52.25 cdef
Molixiang	2440.8 ± 98.85 a	455.8 ± 19.56 bcd	1985 ± 86.09 a	874 ± 40 a	435.2 ± 39.95 a

ABS/CSm: Light energy absorbed per unit area (t = tF_m); DIo/CSm: energy dissipation per unit area (t = tF_m); TRo/CSm: Light energy captured per unit area (t = tF_m); ETo/CSm: energy captured per unit area for electron transport (t = tF_m); REo/CSm: Energy transferred per unit area to the end of the electron chain (t = tF_m). After Duncan’s test, different lowercase letters indicated significant differences (p < 0.05), while the same lowercase letters indicated no significant differences.

, significant differences (p < 0.05) exist among 27 grape varieties in the chlorophyll fluorescence parameters ABS/CSm, DIo/CSm, TRo/CSm, ETo/CSm, and REo/CSm. ‘Jumeigui’, ‘Flame Seedless’, ‘Hetianhong’, ‘Zitianwuhe’, ‘Crimson Seedless’, ‘Autumn Black’, and ‘Molixiang’ exhibit higher ABS/CSm ratios than other varieties, while ‘Xinhongmeigui’ has the lowest ratio at 1810.6. The DIo/CSm ratios of ‘Hetianhong’, ‘Autumn Black’, and ‘B2’ are lower than those of other varieties, at 400.2, 397.6, and 393.8, respectively. The TRo/CSm ratios of ‘Jumeigui’, ‘Flame Seedless’, ‘B2’, ‘Hetianhong’, ‘Zitianwuhe’, ‘Crimson Seedless’, ‘Autumn Black’, and ‘Molixiang’ are higher than those of other varieties, whereas ‘Bixiangwuhe’, ‘Manaizi’, and ‘Xinhongmeigui’ have lower TRo/CSm ratios, at 1463.6, 1429, and 1380.6, respectively. The ETo/CSm ratios of ‘B2’, ‘Zicuiwuhe’, and ‘Molixiang’ are higher than those of other varieties, while ‘Summer Black’ has the lowest at 504. The REo/CSm ratio of ‘Molixiang’ is the highest, at 435.2, while ‘Xinhongmeigui’ has the lowest, at 194.

3.6. Correlation Analysis of Photosynthetic Fluorescence Parameters

Chlorophyll content, photosynthetic parameters, and fluorescence parameters all influence the photosynthetic capacity of leaves. As shown in Figure 3, the R_D and I_C of different grape varieties are significantly positively correlated, as are P_Nmax and AQY. F_v/F_m, F_v/F_O, PI_abs, ABS/CSm, TRo/CSm, and ETo/CSm are also significantly positively correlated with each other. REo/CSm is significantly positively correlated with PI_abs, PI_total, ABS/CSm, TRo/CSm, and ETo/CSm. φ_Eo is significantly positively correlated with F_v/F_m, F_v/F_O, PI_abs, TRo/CSm, and ETo/CSm. dV/dt_o is significantly positively correlated with V_J, but it is significantly negatively correlated with F_v/F_m, F_v/F_O, PI_abs, PI_total, TRo/CSm, ETo/CSm, and REo/CSm. DIo/CSm is significantly positive with V_J, but it is significantly negative with F_v/F_m, F_v/F_O, PI_abs, φ_Eo. V_J is significantly negative with F_v/F_m, F_v/F_O, PI_abs, ETo/CSm, and φ_Eo. V_I is significantly negative with REo/CSm and PI_total.

3.7. Comprehensive Evaluation of Photosynthetic Capacity

Following standardization of 20 photosynthetic fluorescence characteristic indicators, principal component analysis (PCA) was conducted, extracting five principal components (PC1, PC2, PC3, PC4, and PC5) with eigenvalues greater than 1. As shown in

Table 7. Eigenvalues, contribution rates, cumulative contribution rates, and factor loading coefficients of the 5 principal components.

Indicator	Factor Loading Coefficient
	PC1	PC2	PC3	PC4	PC5
RD	−0.368	−0.274	0.208	0.683	0.38
PNmax	0.2	−0.378	0.659	−0.041	−0.157
Isat	0.208	−0.096	−0.014	−0.088	0.477
IC	−0.212	−0.343	0.481	0.678	0.191
AQY	0.455	−0.265	0.568	0.06	−0.413
SPAD	0.177	0.008	0.571	−0.389	−0.409
Fv/Fm	0.894	−0.322	0.031	−0.059	0.116
Fv/FO	0.902	−0.263	0.039	−0.149	0.155
PIabs	0.956	−0.043	−0.185	0.052	0
PItotal	0.532	0.718	0.201	0.277	−0.097
dV/dto	0.79	0.138	−0.089	0.268	−0.177
ABS/CSm	0.774	0.137	0.284	−0.298	0.412
DIo/CSm	0.544	−0.63	−0.225	0.147	−0.204
TRo/CSm	0.852	0.004	0.227	−0.257	0.354
ETo/CSm	0.958	−0.022	−0.098	−0.005	0.111
REo/CSm	0.663	0.659	0.196	0.216	0.088
Leaf area	−0.047	0.535	0.004	−0.342	0.015
VJ	0.725	−0.112	−0.405	0.292	−0.253
VI	0.2	0.806	0.107	0.444	−0.102
φEo	0.843	−0.146	−0.34	0.186	−0.179
Eigenvalue	8.194	2.945	1.965	1.925	1.313
Variance contribution rate (%)	40.972	14.726	9.823	9.627	6.563
Cumulative contribution rate (%)	40.972	55.698	65.521	75.148	81.71

, the cumulative contribution rate of these components reached 81.71%, indicating that they capture most of the variability in the photosynthetic fluorescence indicators.

The factor loading of each indicator is proportional to its contribution to the principal component. According to the factor loading coefficients (Table 7), the highest loading factors are ETo/CSm for PC1, V_I for PC2, P_Nmax for PC3, R_D for PC4, and I_sat for PC5.

Based on the variance contribution rates and cumulative variance contribution rate, a comprehensive evaluation function model was established:

F = (0.41/0.817) F1 + (0.147/0.817) F2 + (0.098/0.817) F3 + (0.096/0.817) F4 + (0.066/0.817) F5

As shown in

Table 8. Comprehensive evaluation scores of 27 grape varieties in Hotan area.

Rank	Cultivar	Comprehensive Score	PC1	PC2	PC3	PC4	PC5
1	Molixiang	0.97	1.33	0.21	1.33	0.89	−0.04
2	Zicuiwuhe	0.79	1.63	0.71	−1.22	0.73	−1.18
3	Hetianhong	0.73	1.31	−0.16	0.91	0.38	−0.68
4	Xinyu	0.72	0.89	0.47	−0.16	1.66	0.16
5	Zitianwuhe	0.6	0.5	0.47	1.25	0.54	0.7
6	Crimson Seedless	0.51	0.89	−0.72	−0.05	0.42	1.84
7	Kyoho	0.38	0.16	2.74	0.66	−1.44	−1.38
8	B2	0.33	1.4	0.03	−2.49	−0.89	0.39
9	Thompson Seedless	0.33	−0.19	0.67	0.68	2.29	−0.6
10	Ruby Seedless	0.21	0	0.52	0.13	−0.2	1.63
11	Autumn Black	0.16	1.07	−1.95	0.71	−0.91	0.02
12	Munage	0.12	0.28	−0.91	0.76	0.17	0.38
13	Jumeigui	0.09	0.84	0.36	−1.17	−1.87	−0.41
14	Centennial Seedless	0.09	0.54	−0.07	−0.01	−0.92	−0.72
15	Flame Seedless	0.09	0.47	−0.93	1.27	−1.59	0.63
16	Moldova	0.01	−0.42	0.52	1.89	−0.88	0.05
17	Manicure Finger	0	0.02	−0.31	−1.33	0.77	1.43
18	Heicuiwuhe	−0.23	−0.65	−0.08	−0.5	1.63	−0.29
19	Bixiangwuhe	−0.35	−0.73	0.59	−1.18	0.68	−0.44
20	Hongyuwuhe	−0.41	−0.53	−0.4	−0.14	0.07	−0.77
21	Kunlunzi	−0.5	−0.98	1.15	−0.83	−0.74	−0.35
22	Heibaladuo	−0.56	−1.08	−0.18	−0.5	−0.57	1.71
23	Shine Muscat	−0.59	−1.13	−0.24	0.8	−0.02	−0.94
24	Zuijinxiang	−0.61	−1.09	−0.38	−0.41	0.05	0.63
25	Summer Black	−0.65	−2.04	1.41	0.32	−0.16	1.3
26	Manaizi	−0.95	−0.88	−1.72	−0.43	0.12	−1.94

, the comprehensive scores of the 27 grape varieties range from 0.97 to −1.28, with ‘Molixiang’ achieving the highest score of 0.97. Seventeen varieties have scores of 0 or higher, indicating strong performance in leaf photosynthetic potential, light energy utilization, and stress resistance. The varieties are ranked by their overall photosynthetic performance from highest to lowest: ‘Molixiang’ > ‘Zicuiwuhe’ > ‘Hetianhong’ > ‘Xinyu’ > ‘Zitianwuhe’ > ‘Crimson Seedless’ > ‘Kyoho’ > ‘B2’ > ‘Thompson Seedless’ > ‘Ruby Seedless’ > ‘Autumn Black’ > ‘Munage’ > ‘Jumeigui’ > ‘Centennial Seedless’ > ‘Flame Seedless’ > ‘Moldova’ > ‘Manicure Finger’ > ‘Heicuiwuhe’ > ‘Bixiangwuhe’ > ‘Hongyuwuhe’ > ‘Kunlunzi’ > ‘Heibaladuo’ > ‘Shine Muscat’ > ‘Zuijinxiang’ > ‘Summer Black’ > ‘Manaizi’ > ‘Xinhongmeigui’.

4. Discussion

The P_N-PAR response curve and its associated photosynthetic parameters reflect photosynthetic potential, efficiency, and light inhibition levels of plants [15,16]. Light intensity can generate free radicals and interfere with the light capture complex (LHC) [17]. This leads to photo-suppression, while this study found that the net photosynthetic rate (PN) of each grape variety exhibited a single-peak curve with increasing PAR, with no significant light inhibition seen in any variety. This suggests that all 27 grape varieties show tolerance to strong light in the warm conditions of the Hotan region. The intercellular CO₂ concentration (Ci) of each variety decreased rapidly within the PAR range of 0 to 500 µmol·m⁻²·s⁻¹. This rapid decline resulted from high CO₂ consumption as a substrate for photosynthetic reactions under low light conditions [18]. Concurrently, stomatal conductance (Gs) increased with rising PAR, leading to a decrease in Ci and an increase in transpiration rate (Tr), thereby enhancing water use efficiency (WUE). The varieties ‘Molixiang,’ ‘Kunlunzi,’ and ‘Zicuiwuhe’ exhibited higher Gs, showing high growth potential in arid environments. In contrast, ‘Xinyu,’ ‘Heibaladuo,’ and ‘Summer Black’ exhibited lower transpiration rates (Tr) compared to other varieties, indicating that photosynthetic efficiency in their leaves decreases due to reduced photorespiration in high-temperature and high-light environments [19]. The Gs and Tr curves of the 27 grape varieties varied significantly, possibly due to the climatic conditions, including prolonged exposure to high temperatures and low humidity [20]. Research indicates that under harsh environmental conditions, different grape varieties adapt their photosynthetic processes through mechanisms such as stomatal closure, osmotic regulation, and enhanced stress tolerance [21].

It is also revealed that P_N-PAR response curve parameter is one of the important methods in studying the photosynthetic physiological ecology of plants [22]. Our findings revealed that ‘Flame Seedless’ and ‘Munage’ exhibit higher P_Nmax values compared to other varieties. This is due to their higher AQY and φ_Eo [23]. The high efficiency in light energy conversion enhances their photosynthetic potential under strong light conditions. The light compensation point and I_sat define the range of light conditions that plants can utilize, reflecting their adaptability to varying light intensities [24]. The light flux of I_C and I_sat varies with environmental and developmental conditions [16]. ‘Crimson Seedless’ has the highest I_sat, indicating strong light adaptation, possibly due to its higher F_v/F_m and φ_Eo. This enables it to maintain a balance between photochemical reactions and carbon assimilation by enhancing the electron transport efficiency of PSII. I_C, AQY, and R_D reflect the shade tolerance in plants [25]. ‘Thompson Seedless’ exhibits lower I_C and R_D than other varieties, suggesting it can reduce respiration rate and energy consumption based on the light conditions in the Hotan region. ‘Molixiang’ has higher AQY than other varieties, showing better utilization of low light intensity. Both varieties have the potential to increase organic matter accumulation and adapt to a certain degree of weak light environment. Correlation analysis shows that I_C and R_D are highly positively correlated, while AQY is negatively correlated, consistent with previous research results [26].

Chlorophyll is a green pigment found in plants that is essential for photosynthesis. Research findings show that it is an important parameter to judge the photosynthetic capacity and health status of plants [27]. In the present study it was found that ‘Manaizi’ exhibited the highest SPAD value. Under the environmental conditions of the Hotan region, improving light energy capture efficiency and the stability of the photosynthetic reaction center can enhance the SPAD value. However, the moderate P_Nmax suggests a possible decoupling between chlorophyll content and photosynthetic capacity, while this decoupling could be influenced by leaf position as discussed above, it may also stem from underlying biochemical limitations, such as variations in thylakoid membrane integrity, Rubisco activity, or the efficiency of electron transport chains [28]. Correlation analysis indicates a positive but non-significant correlation between SPAD value and P_Nmax, suggesting that high chlorophyll content does not necessarily translate directly into a photosynthetic advantage. It reveals that the function of the thylakoid membrane protein complex has a greater impact on light energy conversion than pigment concentration. In addition, the changes in photosynthetic rate under temperature and pressure are affected by the thermal instability of the enzymes involved in photosynthesis. Therefore, combining biochemical parameters will be extremely valuable for clarifying the specific mechanisms responsible for this observed change.

Chlorophyll fluorescence is an effective tool for studying plant processes and status at the cell, leaf, individual, and regional scales [29,30]. The maximum photochemical quantum yield (F_v/F_m) indicates the maximum photochemical efficiency of leaves, a key measure of light energy utilization efficiency [31]. Under conditions of high temperature and strong light, electron transfer, photochemical efficiency and photo-oxidation will hinder the quantum efficiency of PSII and cause it to decline [32]. Research findings show that ‘Autumn Black’ and ‘Hetianhong’ have higher F_v/F_m and F_v/F_O values compared to other varieties, indicating their high light energy conversion efficiency and the LHCII pigment–protein arrangement is more conducive to the transfer of energy to the reaction center. In contrast, ‘Summer Black’ has lower F_v/F_m and F_v/F_O values compared to other varieties, It is due to the destruction of oxygen-evolving complexes, light-harvesting pigments, and thylakoid membrane proteins in grape leaves under temperature and light stress, leading to chlorophyll degradation [33] and a decrease in the maximum photochemical quantum yield of PSII. The PI_abs and PI_total indices reflect the performance of the leaf’s photosystems, with PI_abs primarily indicating light energy absorption capacity and PI_total reflecting the overall performance of the leaf. ‘Zicuiwuhe’ has higher PI_abs and PI_total values compared to other varieties, and its high φ_Eo and low V_J indicate efficient electron transport chain performance, which may help mitigate strong light damage [34,35]. The highly significant negative correlation between V_J and φ_Eo suggests that increased closure of the PSII reaction center reduces electron transport efficiency, leading to photoinhibition or photodamage.

Energy allocation is well known phenomenon used by plants to adopt the environmental condition during adverse conditions [36]. In the current research it was observed that ‘Molixiang’ and ‘B2’ exhibit higher levels of ABS/CSm, TRo/CSm, ETo/CSm, and REo/CSm, while DIo/CSm is relatively low. This indicates that ‘Molixiang’ and ‘B2’ have a stronger ability to absorb, capture, and transfer light energy, resulting in lower leaf energy dissipation and higher light energy utilization. ‘Kyoho’ shows higher levels of ABS/CSm, DIo/CSm, TRo/CSm, ETo/CSm, and REo/CSm, suggesting that it has a strong capacity for light energy absorption and conversion but also experiences significant energy dissipation. This is due to the input of light energy not matching the output of electron transfer, the excess energy is dissipated in the form of heat through non-photochemical quenching, which is a key mechanism for the self-protection of plants [37]. Correlation analysis reveals that F_v/F_m, F_v/F_O, PI_abs, ABS/CSm, TRo/CSm, ETo/CSm, REo/CSm, and φ_Eo are all significantly or highly positively correlated, while dV/dt_o is significantly or highly negatively correlated. This suggests that stronger light energy absorption, capture, and transfer capabilities per unit leaf area enhance photochemical potential, while a higher QA reduction rate reduces photochemical potential. These different energy distribution strategies highlight the variety differences in how grape leaves manage light energy under adverse conditions. Varieties like ‘Molixiang’ have demonstrated outstanding efficiency in photochemical utilization of absorbed light rather than dissipation, which is a key feature of superior productivity in a strong and arid environment like Hotan.

Photosynthesis in grapevines varies significantly across stem positions and leaf characteristics [38]. Leaves at different positions (basal, median, apical) and developmental stages (primary swelling, maturity, senescence) exhibit distinct photosynthetic capacities, chlorophyll contents, and responses to environmental stress [39,40]. Leaves on lateral branches also display different photosynthetic characteristics compared to those on primary branches. Bertamini et al. [41] found that under high-light conditions, mature leaves showed less reduction in photosynthetic chain activity and PSII function compared to young leaves, which experienced significant declines. Hirano et al. [42] reported that during fruit ripening, lateral branch leaves exhibited higher photosynthetic rates than primary branch leaves. Furthermore, increased leaf area on lateral branches accelerated berry ripening, enhanced soluble solid accumulation, reduced titratable acidity, and improved fruit color. These differences are primarily attributed to leaf morphology (e.g., area and stomatal density), biochemical components (e.g., Rubisco content), source–sink relationships, and microclimate [38]. In this study, mature, sun-facing functional leaves from the 5th to 7th nodes of new shoots were sampled to minimize variations due to extreme developmental stages (very young or senescent leaves) or heavily shaded positions. However, even within this selected range, inherent physiological gradients and varietal differences in canopy structure or stem-leaf growth patterns may influence the microenvironment, affecting photosynthetic parameters measured at these nodes. These factors require further investigation in future studies.

5. Conclusions

Hotan Prefecture in Xinjiang is one of the important grape-growing areas. This study investigated the photosynthetic fluorescence characteristics of mature leaves of 27 grape varieties. It was found that there were significant physiological differences among these varieties, reflecting different degrees of adaptation to the local drought and strong light environment. ‘Molixiang’ is the variety with the best comprehensive photosynthetic performance. Its light energy absorption and electron transfer efficiency are both superior to other varieties, and it has high potential for suitable cultivation in Hotan Prefecture. This variety has demonstrated strong parental potential in the breeding program aimed at enhancing drought resistance. This study provided a powerful physiological assessment and identified promising varieties. The established photosynthetic physiological evaluation system offers a valuable theoretical framework for selecting and promoting grape varieties in arid areas. Future research that combines biochemical and molecular analysis will be crucial for fully elucidating the mechanisms underlying superior photosynthetic adaptability.