Heat Stress in Cotton: A Review on Predicted and Unpredicted Growth-Yield Anomalies and Mitigating Breeding Strategies

✅ 全文

棉花热应激:预测与非预测生长-产量异常及缓解育种策略综述

作者 Sajid Majeed; Iqrar Ahmad Rana; Muhammad Salman Mubarik; Rana Muhammad Atif; Seung Hwan Yang; Gyuhwa Chung; Yinhua Jia; Xiongming Du; Lori L. Hinze; Muhammad Tehseen Azhar 期刊 Agronomy 发表日期 2021 ISSN 2073-4395 DOI 10.3390/agronomy11091825 类型 原创研究 (Original Research)

📄 英文摘要 English Abstract

EN

The demand for cotton fibres is increasing due to growing global population while its production is facing challenges from an unpredictable rise in temperature owing to rapidly changing climatic conditions. High temperature stress is a major stumbling block relative to agricultural production around the world. Therefore, the development of thermo-stable cotton cultivars is gaining popularity. Understanding the effects of heat stress on various stages of plant growth and development and its tolerance mechanism is a prerequisite for initiating cotton breeding programs to sustain lint yield without compromising its quality under high temperature stress conditions. Thus, cotton breeders should consider all possible options, such as developing superior cultivars through traditional breeding, utilizing molecular markers and transgenic technologies, or using genome editing techniques to obtain desired features. Therefore, this review article discusses the likely effects of heat stress on cotton plants, tolerance mechanisms, and possible breeding strategies.

📄 中文摘要 Chinese Abstract

中文
不可预测的气候条件变化,尤其是高温,正持续威胁着棉花的可持续生产。多种环境因素决定了作物生产力,包括热量、干旱、降水、湿度和日照时数。然而,高温或热胁迫是棉花等作物生长发育的主要限制因素之一。Singh等人(2007)报道,即使温度仅比最适生长温度升高1°C,棉花皮棉产量也可能降低高达110 kg ha⁻¹。棉花是最重要的天然纤维和油料工业作物。在巴基斯坦,2021–22年度的种植面积为193.7万公顷,共产皮棉832.9万包,平均单产为731 kg ha⁻¹。巴基斯坦棉花产量较低的主要原因包括投入品价格高昂、投入成本难以获得、病虫害发生率严重、干旱胁迫、热胁迫、机械化收获缺乏以及优质种子供应不足。在棉花中,对热最敏感的阶段是开花期,该阶段会导致严重的花蕾脱落、植株生长受阻、棉铃数量和单铃重减少,从而造成显著的产量损失。因此,植物育种学家在胁迫条件下严格评估棉花基因型以鉴定耐性基因型面临着严峻挑战。本试验研究旨在评估当地棉花基因型的耐热性,并鉴定与棉花耐热性相关的关键性状。

📋 英文结构化总结 English Structured Summary

全文整理

EN

Background:

The unpredictably changing climatic conditions, especially high temperatures, are putting a continuous threat to sustainable cotton production. Several environmental factors determine the productivity of crop plants including heat, drought, precipitation, humidity, and sunshine hours. However, high temperature or heat stress is one of the major constrain in the growth and development of crops including cotton. Singh et al. (2007) reported that with an increase in temperature of even 1 °C over optimal growing temperature, the lint yield of the cotton crop could be reduced up to 110 kg ha⁻¹. Cotton is the most important industrial crop regarding natural fibre and oil. In Pakistan, its cultivated area during 2021–22 was 1.937 million hectares, from which 8.329 million bales were produced, averaging 731 kg ha⁻¹. The major reasons for a lower yield of cotton in Pakistan are high input rates, unavailability of inputs, high diseases and insects-pest infestation rates, drought stress, heat stress, lack of mechanical harvesting, and unavailability of quality seed. In cotton, one of the most heat-sensitive phases is the flowering stage, which leads to severe flower shedding, stunted plant growth, and reduced number of bolls and boll weight, resulting in significant yield losses. Therefore, it is a hard challenge for plant breeders to rigorously evaluate cotton genotypes under stressful conditions to identify tolerant genotypes. The current experimental study was designed to evaluate local cotton genotypes for their heat tolerance along with the identification of key traits that contribute to the heat tolerance in cotton.

Methods:

The current experimental study was conducted at the research area of Cotton Research Station (CRS), Bahawalpur (29° 22' 29.22960" N, 71° 38' 16.11240" E) and at the altitude o...

Results:

The results revealed the presence of significant variations in agro-morphological, physio-chemical and staple length-related parameters for upland cotton genotypes and stress treatments. Further analysis of pooled data unveiled that heat stress had a detrimental impact on all studied plant traits. Severe reduction in plant height, nodes per plant, sympodial branches per plant, number of bolls per plant, ginning out-turn, and staple length were recorded under heat stress. A significant reduction in net photosynthetic rate (Pn) up to 28.6 % was observed in cotton genotype BH-200 (24.7 to 19.2 µmole m⁻² s⁻¹). The accumulation of hydrogen peroxide (H₂O₂) was increased from 7.1 % in BH-306 to 28.7 % in BH-200 under heat stress due to the incidence of oxidative stress. A substantial increase in the accumulation of antioxidants i.e., catalase (65 %–74 %), peroxidase (54 %–169 %), and superoxide dismutase (52 %–98 %) was seen under high-temperature stress conditions.

Data Summary:

Significant reduction in net photosynthetic rate (Pn) up to 28.6 % was observed in cotton genotype BH-200 (24.7 to 19.2 µmole m⁻² s⁻¹). The accumulation of hydrogen peroxide (H₂O₂) was increased from 7.1 % in BH-306 to 28.7 % in BH-200 under heat stress. A substantial increase in the accumulation of antioxidants i.e., catalase (65 %–74 %), peroxidase (54 %–169 %), and superoxide dismutase (52 %–98 %) was seen. The correlation coefficient analysis unveiled a significantly positive correlation of seed cotton yield with nodes per plant (r = 0.432*), net photosynthetic rate (r = 0.829**), peroxidase (r = 0.974**), and superoxide dismutase (r = 0.868**), under heat stress conditions. However, a negative but statistically significant correlation of seed cotton yield with ginning out turn (r = –0.466*), staple length (r = –0.898**), hydrogen peroxide (r = –0.955**) and catalase (r = –0.904**) was also observed.

Conclusions:

The overall results unveiled that cotton genotype BH-232 has a comparatively higher heat tolerance than other contesting genotypes while BH-306 showed the highest susceptibility to heat stress. Hence, BH-232 could be recommended after its approval for general cultivation in heat-prone areas of Pakistan.

Practical Significance:

Hence, BH-232 could be recommended after its approval for general cultivation in heat-prone areas of Pakistan.

📋 中文结构化总结 Chinese Structured Summary

中文

背景:

不可预测的气候条件变化,尤其是高温,正持续威胁着棉花的可持续生产。多种环境因素决定了作物生产力,包括热量、干旱、降水、湿度和日照时数。然而,高温或热胁迫是棉花等作物生长发育的主要限制因素之一。Singh等人(2007)报道,即使温度仅比最适生长温度升高1°C,棉花皮棉产量也可能降低高达110 kg ha⁻¹。棉花是最重要的天然纤维和油料工业作物。在巴基斯坦,2021–22年度的种植面积为193.7万公顷,共产皮棉832.9万包,平均单产为731 kg ha⁻¹。巴基斯坦棉花产量较低的主要原因包括投入品价格高昂、投入成本难以获得、病虫害发生率严重、干旱胁迫、热胁迫、机械化收获缺乏以及优质种子供应不足。在棉花中,对热最敏感的阶段是开花期,该阶段会导致严重的花蕾脱落、植株生长受阻、棉铃数量和单铃重减少,从而造成显著的产量损失。因此,植物育种学家在胁迫条件下严格评估棉花基因型以鉴定耐性基因型面临着严峻挑战。本试验研究旨在评估当地棉花基因型的耐热性,并鉴定与棉花耐热性相关的关键性状。

方法:

本试验研究在巴哈瓦尔布尔棉花研究站(CRS)的研究区域(北纬29°22'29.22960",东经71°38'16.11240")进行,海拔为...

结果:

结果表明,陆地棉基因型在农艺形态、理化及纤维长度相关参数方面以及胁迫处理间存在显著差异。对合并数据的进一步分析揭示,热胁迫对所有研究性状均产生了不利影响。在热胁迫条件下,植株高度、单株节数、单株果枝数、单株铃数、衣分和纤维长度均出现显著降低。棉花基因型BH-200的净光合速率(Pn)显著降低了28.6%(从24.7降至19.2 µmole m⁻² s⁻¹)。由于氧化胁迫的发生,热胁迫下过氧化氢(H₂O₂)的积累从BH-306的7.1%增加到BH-200的28.7%。在高温胁迫条件下,抗氧化酶(即过氧化氢酶65%–74%、过氧化物酶54%–169%和超氧化物歧化酶52%–98%)的积累显著增加。

数据摘要:

棉花基因型BH-200的净光合速率(Pn)显著降低了28.6%(从24.7降至19.2 µmole m⁻² s⁻¹)。热胁迫下过氧化氢(H₂O₂)的积累从BH-306的7.1%增加到BH-200的28.7%。抗氧化酶(即过氧化氢酶65%–74%、过氧化物酶54%–169%和超氧化物歧化酶52%–98%)的积累显著增加。相关系数分析揭示,在热胁迫条件下,籽棉产量与单株节数(r = 0.432*)、净光合速率(r = 0.829**)、过氧化物酶(r = 0.974**)和超氧化物歧化酶(r = 0.868**)呈显著正相关。然而,籽棉产量与衣分(r = –0.466*)、纤维长度(r = –0.898**)、过氧化氢(r = –0.955**)和过氧化氢酶(r = –0.904**)也呈显著负相关。

结论:

总体结果表明,棉花基因型BH-232相较于其他参试基因型具有相对较高的耐热性,而BH-306对热胁迫表现出最高的敏感性。因此,BH-232在通过审定后,可推荐在巴基斯坦热害频发地区进行大面积推广种植。

实践意义:

因此,BH-232在通过审定后,可推荐在巴基斯坦热害频发地区进行大面积推广种植。

📖 英文全文 English Full Text

EN

Journal of King Saud University – Science 35 (2023) 102379 Contents lists available at ScienceDirect Journal of King Saud University – Science journal homepage: www.sciencedirect.com Original article

Impact of heat stress on agro-morphological, physio-chemical and fiber related paramters in upland cotton (Gossypium hirsutum L.) genotypes Muhammad Irfan Yousaf a,b,1, Quaid Hussain c,1, Mona S Alwahibi d, Muhammad Zahid Aslam a, Muhammad Zeeshan Khalid e, Sabir Hussain a, Akash Zafar f, Syed Awais Sajid Shah a, Arshad Mehmood Abbasi g,h, Asrar Mehboob b, Muhammad Waheed Riaz c,i,⇑, Mohamed S. Elshikh d,⇑ a

Cotton Research Station (CRS), Bahawalpur 63100, Pakistan Maize and Millets Research Institute (MMRI), Sahiwal 57000, Pakistan c State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China d Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia e Department of Plant Breeding and Genetics, IUB, Bahawalpur 63100, Pakistan f Regional Agricultural Research Institute, Bahawalpur 63100, Pakistan g Department of Environment Sciences, COMSATS University Islamabad, Abbottabad 22020, Pakistan h University of Gastronomic Sciences, Piazza Vittorio Emanuele II, 9, 12042 Pollenzo, CN, Italy i Zhejiang Provincial Key Laboratory of Resources Protection and Innovation of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou 311300, China b

Article history: Received 22 June 2022 Revised 4 October 2022 Accepted 10 October 2022 Available online 18 October 2022 Keywords: High temperature Antioxidants ROXs Photosynthesis Climate change Staple length

a b s t r a c t The unpredictably changing climatic conditions, especially high temperatures, are putting a continuous threat to sustainable cotton production. The current study was designed to investigate the impact of heat stress on several morpho-physiological, biochemical, and fibre quality-related traits. The results revealed the presence of significant variations in agro-morphological, physio-chemical and staple length-related parameters for upland cotton genotypes and stress treatments. Further analysis of pooled data unveiled that heat stress had a detrimental impact on all studied plant traits. Severe reduction in plant height, nodes per plant, sympodial branches per plant, number of bolls per plant, ginning out-turn, and staple length were recorded under heat stress. A significant reduction in net photosynthetic rate (Pn) up to 28.6 % was observed in cotton genotype BH-200 (24.7 to 19.2 lmole m2 s1). The accumulation of hydrogen peroxide (H2O2) was increased from 7.1 % in BH-306 to 28.7 % in BH-200 under heat stress due to the incidence of oxidative stress. A substantial increase in the accumulation of antioxidants i.e., catalase (65 %–74 %), peroxidase (54 %–169 %), and superoxide dismutase (52 %–98 %) was seen under high-temperature stress conditions. The correlation coefficient analysis unveiled a significantly positive correlation of seed cotton yield with nodes per plant (r = 0.432*), net photosynthetic rate (r = 0.829**), peroxidase (r = 0.974**), and superoxide dismutase (r = 0.868**), under heat stress conditions. However, a negative but statistically significant correlation of seed cotton yield with ginning out turn (r = 0.46 6*), staple length (r = 0.898**), hydrogen peroxide (r = 0.955**) and catalase (r = 0.904**) was also observed. The overall results unveiled that cotton genotype BH-232 has a comparatively higher heat tolerance than other contesting genotypes while BH-306 showed the highest susceptibility to heat stress. Hence, BH-232 could be recommended after its approval for general cultivation in heat-prone areas of Pakistan. Ó 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

⇑ Corresponding authors. E-mail addresses: waheed_riaz2007@yahoo.com (M.W. Riaz), melshikh@ksu. edu.sa (M.S. Elshikh). 1 These authors have contributed equally to this work and share the first authorship. Peer review under responsibility of King Saud University.

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1. Introduction The transitional environmental conditions are posing a continuous menace to the productivity and sustainability of major field crops by altering their development behaviour and capacity to endure severe environmental conditions. The constant deterioration in croping areas due to urbanization, desertification, salinization, and uncontrolled increase in the human population

https://doi.org/10.1016/j.jksus.2022.102379 1018-3647/Ó 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

M.I. Yousaf, Q. Hussain, Mona S Alwahibi et al. Journal of King Saud University – Science 35 (2023) 102379

of April (Late sowing). In the late sown crop, the flowering and bud formation stage is expected to experience a high temperature (above 40 °C) as revealed by previous years’ metrological data. The research was carried out in an RCBD pattern in triplicates and treatments were laid out using split-plot arrangement.

exacerbated the effects of climate change. Several environmental factors determine the productivity of crop plants including heat, drought, precipitation, humidity, and sunshine hours. However, high temperature or heat stress is one of the major constrain in the growth and development of crops including cotton. Singh et al. (2007) reported that with an increase in temperature of even 1 °C over optimal growing temperature, the lint yield of the cotton crop could be reduced up to 110 kg ha1. Cotton is the most important industrial crop regarding natural fibre and oil (Salimath et al., 2021). During 2020–21, it was cultivated on 31.42 million hectares from which 111.48 million 480 lb bales were obtained, averaging 773 kg ha1 in the World (USDA, 2022). In Pakistan, its cultivated area during 2021–22 was 1.937 million hectares, from which 8.329 million bales were produced, averaging 731 kg ha1 (ESP, 2021-22). Although Pakistan’s per hectare cotton production is very near to the world’s per hectare production, it is far behind the major cottonproducing countries i.e., Australia (2217 kg ha1), China (1976 kg ha1), Turkey (1804 kg ha1), Brazil (1720 kg ha1) and United States (957 kg ha1) (USDA, 2022). The major reasons for a lower yield of cotton in Pakistan are high input rates, unavailability of inputs, high diseases and insects-pest infestation rates, drought stress, heat stress, lack of mechanical harvesting, and unavailability of quality seed. In cotton, one of the most heat-sensitive phases is the flowering stage, which leads to severe flower shedding, stunted plant growth, and reduced number of bolls and boll weight, resulting in significant yield losses (Xu et al., 2020). Higher temperatures (32– 40 °C) negatively influence root development and stomatal conductance. Moreover, temperatures higher than 29 °C also reduce the boll weight (Lokhande and Reddy, 2014). The seed germination rate is highly affected by the higher temperatures (˃37 °C) along with the reduction in pollen tube germination and elongation (Burke et al., 2004). Salman et al. (2019) showed that the reduction in cotton yield under heat stress is resulted by the decrease in germination rate, net photosynthetic rate, relative cell injuries, sympodial branches, boll weight, and increase in flower, square, and boll abscission. Along with the cotton yield, lint quality is also degraded under heat stress due to the increase in short fibres, decrease in fibre fineness and fibre uniformity (Zafar et al., 2021). Therefore, it is a hard challenge for plant breeders to rigorously evaluate cotton genotypes under stressful conditions to identify tolerant genotypes. The current experimental study was designed to evaluate local cotton genotypes for their heat tolerance along with the identification of key traits that contribute to the heat tolerance in cotton.

2.3. Measurement/Recording of plant parameters 2.3.1. Morpho-Physiological and fibre-related parameters Several plant morphological traits i.e., plant height (PH), nodes per plant (N/P), number of sympodial branches per plant (SB/P) and number of bolls per plant (NB/P) were recorded at the time of second picking while ginning out-turn (GOT) and seed cotton yield (SCY) were measured after crop harvest. Net photosynthetic rate (Pn; lmolem-2s1) was recorded through CI-320, a handheld Near-Infrared Gas Analyzer as recommended and used by Yousaf et al. (2022). The staple or fibre length of cotton was measured through a high-volume instrument (HVI) and measured in millimetres.

2.3.2. Methodology for the measurement of hydrogen peroxide (H2O2) accumulation The activity of H2O2 was measured through the protocol developed and used by Velikova et al. (2000).

3. Enzymatic antioxidant determination 3.1. Preparation of enzyme extract Collected Fully extended and healthy leaves were thoroughly washed with distilled water and frozen under liquid nitrogen (N2) and stored at 80◦C for the assessment of the antioxidant activity of different enzymes. Leaf samples of 5 g from the stored samples were ground meticulously in chilled 10 ml potassium phosphate buffer (pH 7.8). The reaction mixture was then centrifuged at 14000 rpm for 10 min at 4 °C. The supernatant was used for the determination of antioxidant activities through their absorbance at different wavelengths in a UV–vis spectrophotometer (Sarwar et al., 2019).

3.2. Estimation of Catalase, Peroxidase and Super-oxidase dismutase activities (U mg1 Protein) The activity of these enzymes was measured through a UV–vis spectrophotometer at different wavelengths. The Catalase activity was measured at the wavelength of 240 nm as given by Liu et al., 2009. The Peroxidase activity was recorded according to Liu et al. (2009) at 470 nm wavelength. Similarly, superoxidase dismutase (SOD) activity was measured spectrophotometrically through the absorbance capacity of SOD at 560 nm wavelength by following the protocol given by Beauchamp and Fridovich (1971).

2. Materials and methods 2.1. Experimental materials and location The current experimental study was conducted at the research area of Cotton Research Station (CRS), Bahawalpur (29° 220 29.22960 ’ N, 71° 380 16.11240 ’ E) and at the altitude of 115 m during two consecutive cotton growing seasons (2020-21, 2021–22). The experimental material was comprised of five upland cotton genotypes viz., BH-254, BH-234, CIM-600, BH-200, and BH-306.

3.3. Statistical analysis The obtained data of seed cotton yield and its associated morpho-physiological and biochemical traits were investigated for analysis of variance (ANOVA) and correlation coefficient analysis (Steel et al., 1997). To execute the above mention analysis, three statistical packages i.e., Statistix 8.1, XLSTAT 21.0, and Origin 21.0 were used. Furthermore, Microsoft Excel 2021 and Adobe Illustrator 22.0 were used for the illustration of the results.

2.2. Experimental layout The experiment was carried out in the field under two treatments 1) control and 2) heat stress for two consecutive cottongrowing seasons 2020-21 and 2021-22. In the control treatment, the cotton crop was sown during the 2nd week of March while under stress treatment, the sowing was done during the 3rd week 2

Journal of King Saud University – Science 35 (2023) 102379 M.I. Yousaf, Q. Hussain, Mona S Alwahibi et al.

Climatic data for key factors, temperature (°C) and precipitation (mm) were recorded on daily basis from the date of sowing to square and boll development (60 days after sowing). The data was recorded for both treatments and two consecutive years (2020–21 and 2021–22). The data showed that the maximum temperature for the control treatment during the month of sowing was less, 34 °C (2020–21) and 36 °C (2021–22) than the maximum temperature for the heat stress treatment, 36 °C (2020–21) and 40 °C (2021–22) (Fig. 1a). Moreover, the mean daily maximum temperature under high-temperature treatment was meaningfully higher than maximum temperature in control (Fig. 1b).

diversity for net photosynthetic rate (Pn) in cotton genotypes under normal and stress conditions (Table 1). The results further showed a significant decline in net photosynthetic activity (Pn) under heat stress compared to control in all-cotton genotypes (Fig. 2b). The highest reduction in Pn under heat stress was observed in BH-200 (28.6 %) from 24.7 lmolem-2s1 in control to 19.2 lmolem-2s1 in stress conditions (Fig. 2b). However, the minimum reduction in Pn (7.0 %) was reported in BH-306 under heat stress, even though the overall net photosynthetic rate of BH-306 under control and heat stress treatment was the lowest among the cotton genotypes under study (Fig. 2b). The correlation coefficient analysis unveiled a strong positive correlation of net photosynthetic rate (Pn) with seed cotton yield (SCY) under control (r = 0.838**) as well as heat stress treatment (r = 0.829**), respectively (Table 2).

4.6. Accumulation of reactive oxygen species (ROX)

The combined analysis of variance revealed the presence of highly significant variations among cotton genotypes for morpho-physiological, biochemical, and fibre related parameters under control and high temperature conditions (Table 1). However, the variation for the year’s source of variance was non-significant for all studied traits except the number of bolls per plant. Due to this fact, the two-year data were pooled, and their average was taken for further analysis.

4.6.1. Hydrogen peroxide (H2O2) Results from combined ANOVA revealed a high degree of variation in cotton genotypes for the accumulation of hydrogen peroxide (H2O2) under heat stress conditions (Table 1). The further results revealed that the accumulation of hydrogen peroxide (H2O2) was quite significant under heat stress conditions compared to control in all-cotton genotypes, indicating the higher oxidative stress experienced by the plants under stress. Under heat stress, the maximum accumulation of H2O2 was recorded in BH-306 (13.1 lmoleg1) in comparison to control (9.6 lmoleg1) while the lowest H2O2 accumulation was observed in BH-232 under heat stress (7.2 lmoleg1) in contrast to the control treatment (4.8 lmoleg1) (Fig. 2c). Moreover, the hydrogen peroxide (H2O2) was found to have a very strong negative correlation with seed cotton yield under control (r = 0.972**) as well as heat stress conditions (r = 0.955**) (Table 2).

4.3. Seed cotton yield-associated morpho-agronomical traits The correlation analysis unveiled a significant positive association between nodes per plant (N/P) and seed cotton yield (SCY) under normal (r = 0.465*) as well as heat stress conditions (r = 0.432*) (Table 2). However, seed cotton yield depicts a significantly negative correlation with GOT under normal (r = 0.548*) and heat stress conditions (r = 0.466**). The correlation of SCY with PH and NB/P was positive but non-significant under both normal (r = 0.96, r = 0.179) and heat stress (r = 0.235, r = 0.236) conditions, respectively. On the other hand, the correlation between SB/P and SCY was negative but non-significant under both stress conditions (r = 0.317, r = 0.270), respectively (Table 2). A significant decrease in seed cotton yield (SCY) and its associated morpho-agronomical traits i.e., PH, N/P, SB/P, NB/P and GOT was observed in heat stress treatment compared to control (Table 3).

4.6.2. Accumulation of enzymatic antioxidants The combined analysis of variance unveiled the existence of significant diversity for CAT, POXs and SOD under stress treatments (Table 1). However, the variations for these antioxidants across years were found non-significant and their interactions too. Further results revealed that heat stress triggered the accumulation of several antioxidants including CAT, POXs and SOD in cotton genotypes (Fig. 2d, Fig. 3a & b). The maximum increase in CAT accumulation was observed in BH-254, where CAT accumulated 189 % more under heat stress (238.0 U mg1 protein) than control (82.6 U mg1 protein). However, the highest CAT accumulation under heat stress was recorded in BH-306 (248.9 U mg1 protein). A strong, negative but highly significant correlation was observed between CAT accumulation and seed cotton yield under both conditions (rn = 0.937**, rh = 0.904**) in studied cotton genotypes (Table 2). The highest accumulation of POXs was recorded in BH232 (115.9 U mg1 protein) while the lowest POXs accumulation was observed in BH-306 (83.6 U mg1 protein), respectively. However, the percentage increase in POXs accumulation was found highest in BH-306, where POXs accumulated 168 % higher under heat stress conditions compared to control (Fig. 3a). The correlation coefficient analysis disclosed a strong positive and highly significant correlation between POXs accumulation and seed cotton yield under control (r = 0.920**) heat stress conditions (r = 0.974**), respectively (Table 2). Similarly, the highest SOD activity was observed in cotton genotype BH-232 (109.8 U mg1 protein) while the lowest activity was recorded in BH-306 (84.8 U mg1 protein) under heat stress conditions. The maximum percentage increase in T-SOD activity was recorded in BH-306 (97.8 %) from 42.9 U mg1 protein in control to 84.8 U mg1 protein in heat stress conditions, respectively.

4.4. Staple length Staple length (SL), which is one of the most important fibre traits from the textile industrial point of view, showed significant variance among cotton genotypes under normal and heat stress conditions (Table 1). The results revealed that the highest staple length was exhibited by cotton genotype BH-254 (29.2 mm) followed by BH-306 (29.1 mm) and CIM-600 (29.0 mm) (Fig. 2a). On the other hand, BH-232 showed minimum staple length under normal (28.2 mm) and heat stress treatment (27.9 mm) followed by BH-200 (28.5 mm, 28.2 mm), respectively. The correlation coefficient analysis indicated a strong negative and highly significant correlation between staple length (S.L) and seed cotton yield (SCY) under normal (r = 0.921**) and heat stress treatment (r = 0.898**) (Table 2). 4.5. Net photosynthetic rate (Pn) Photosynthesis is the key physiological process in cotton which is responsible for optimum growth and development for higher productivity. The ANOVA revealed the presence of significant 3

Journal of King Saud University – Science 35 (2023) 102379

Fig. 1. (a) Metrological data for the first four months of crop growth, (b) Variation in temperature under control and heat stress conditions.

Table 1 Mean Squares (MS) of plant traits in five cotton genotypes under drought stress conditions. Source of Variation df P.H N/P SB/P NB/P GOT SL Pn H2O2 CAT POXs T-SOD SCY REP (A) Year (B) Error A*B Treatment (C) B*C Error A*B*C Genotypes (D) C*D Error A*B*C*D Total

2 1 2 1 1 4 4 4 32 59 197.36 0.07NS 0.68 1870.4** 0.02NS 1.65 1430** 324.6** 98.65 197.36 5.12 0.60NS 0.35 98.8** 0.82NS 0.67 13.90** 10.77** 4.39 5.12 24.08 0.02NS 2.13 112.07** 0.07NS 0.20 42.4** 0.83NS 10.77 24.08

20.70 1.30* 0.55 148.8** 0.94NS 0.66 87.43** 41.57* 19.10 20.70 0.20 0.32NS 0.22 15.2** 0.42NS 0.29 14.54** 5.50** 1.99 0.20 0.88 0.50NS 0.38 0.46** 0.10NS 0.12 4.38** 0.008NS 0.12 0.88 3.15 0.14NS 0.22 182.6** 1.49** 0.36 49.18** 9.03** 0.92 3.15

0.10 1.33NS 1.42 194.8** 1.64NS 1.32 63.02** 0.80** 0.07 0.10 75.51 0.48NS 0.54 324283** 0.68NS 78.95 6518.9** 640.4** 47.17 75.51 58.42 0.51NS 0.38 33443** 0.71NS 0.81 2861.9** 122.65** 8.47 58.42 23.51 0.14NS 0.32 22136** 0.26NS 23.00 930** 125** 10 23.51

35,900 1.67NS 2.92 2054980** 201.67NS 6379.27 377000** 165008** 24,562 35,900 *P  0.05, **P  0.01; ns: non-significant. P.H = Plant height (cm), N/P: Number of nodes per plant, SB/P: Number of sympodial branches per plant, NB/P: Number of bolls per plant, G.O.T: Ginning out turn (%), SL: Staple length (mm), Pn: Net photosynthetic rate (lmolem-2s1), H2O2: Hydrogen peroxide (lmoleg1), CAT: Catalase (U mg1 protein), POXs: Peroxidase (U mg1 protein), TSOD: Total superoxide dismutase (U mg1 protein), SCY: Seed cotton yield (Kg per ha1).

Table 2 Correlation between different agronomic, physio-chemical, and fibre-related traits in upland cotton genotypes under heat stress conditions. Traits P.H N/P SB/P NB/P GOT SL Pn H2O2 CAT POXs T-SOD SCY

P.H N/P 0.418 0.771 0.186 0.411 0.772 0.183 0.235 0.174 0.330 0.470 0.193 0.096 0.423 0.040 0.295 0.104 0.631 0.582 0.517 0.709 0.599 0.465 SB/P 0.025 0.656 0.516 0.255 0.609 0.216 0.246 0.470 0.239 0.243 0.317

NB/P 0.471 0.285 0.809 0.210 0.357 0.024 0.185 0.495 0.426 0.160 0.335 GOT 0.767 0.185 0.229 0.292 0.700 0.347 0.478 0.289 0.185 0.454 0.548 SL Pn H2O2 CAT POXs T-SOD SCY 0.220 0.177 0.418 0.212 0.732

0.578 0.226 0.466 0.555 0.058 0.590 0.160 0.576 0.153 0.217 0.399 0.884 0.700 0.490 0.515 0.300 0.506 0.090 0.732 0.868 0.920 0.215 0.473 0.293 0.344 0.379 0.895 0.792 0.986 0.953 0.327 0.158 0.631 0.684 0.237 0.804 0.881 0.831 0.926 0.908

0.179 0.432 0.270 0.236 0.466 0.898 0.829 0.955 0.904 0.974 0.868 0.722 0.859 0.865 0.752 0.842 0.921 0.940 0.851 0.866 0.956 0.838 0.932 0.939 0.999 0.972 0.967 0.929 0.937 0.938 0.920

0.959

Note: Values in the upper diagonal are the correlation (rh) between different traits under heat stress while the values in the lower diagonal are the correlation (rn) between different plant traits under control/normal conditions. P.H = Plant height (cm), N/P: Number of nodes per plant, SB/P: Number of sympodial branches per plant, NB/P: Number of bolls per plant, G.O.T: Ginning out turn (%), SL: Staple length (mm), Pn: Net photosynthetic rate (lmolem-2 s-1), H2O2: Hydrogen peroxide (lmoleg1), CAT: Catalase (U mg1 protein), POXs: Peroxidase (U mg1 protein), T-SOD: Total superoxide dismutase (U mg1 protein), SCY: Seed cotton yield (Kg per ha1). 4

Journal of King Saud University – Science 35 (2023) 102379

M.I. Yousaf, Q. Hussain, Mona S Alwahibi et al. Table 3 Effects of heat stress on upland cotton genotypes. Variety Treatment P.H N/P SB/P NB/P GOT BH-254 Control Heat Stress Control Heat Stress Control Heat Stress Control Heat Stress Control Heat Stress

115.7 ± 3.22abc 103.0 ± 3.45bcd 120.0 ± 3.23ab 110.0 ± 3.47abcd 125.0 ± 3.26a 120.0 ± 3.45ab 99.7 ± 3.24cde 80.0 ± 3.47e 108.7 ± 3.26bcd 90.0 ± 3.45de

24.0 ± 0.47abc 21.0 ± 0.53 cd 25.0 ± 0.49ab 21.7 ± 0.52 cd 26.3 ± 0.47a 23.3 ± 0.52abcd 24.0 ± 0.48abc 22.0 ± 0.54bcd 23.3 ± 0.45abcd 20.7 ± 0.53d

18.7 ± 0.75ab 16.3 ± 0.73ab 17.7 ± 0.73ab 15.0 ± 0.72b 20.7 ± 0.73a 17.7 ± 0.72ab 19.0 ± 0.74ab 17.0 ± 0.75ab 19.3 ± 0.75ab 16.0 ± 0.74ab

20.3 ± 1.09abc 18.0 ± 1.08bc 26.0 ± 1.1a 22.0 ± 1.09abc 20.7 ± 1.12abc 17.7 ± 1.09bc 18.7 ± 1.09abc 15.0 ± 1.10c 23.3 ± 1.11ab 19.3 ± 1.08abc

41.3 ± 0.41a 39.9 ± 0.38abcd 40.0 ± 0.39abc 39.0 ± 0.39bcd 41.0 ± 0.41ab 40.7 ± 0.37ab 38.4 ± 0.40 cd 37.8 ± 0.37d 40.4 ± 0.39abc 39.8 ± 0.38abcd BH-232 CIM-600 BH-200 BH-306

P.H = Plant height (cm), N/P: Number of nodes per plant, SB/P: Number of sympodial branches per plant, NB/P: Number of bolls per plant, G.O.T: Ginning out turn (%).

Fig. 2. Impact of Heat stress on (a) Staple length and (b) Net Photosynthetic rate (Pn) (c) Hydrogen peroxide (H2O2) and (d) Catalase (CAT) activity in cotton genotype.

of seed cotton yield with N/P (r = 0.432*), Pn (r = 0.829**), POXs (r = 0.974**) and T-SOD (r = 0.868**) under heat stress conditions. However, under heat stress conditions, SCY had a strong negative correlation with GOT (r = 0.466**), SL (r = 0.898**), H2O2 (r = 0.955**) and CAT (r = 0.904**) (Table 2).

4.6.3. Seed cotton yield (SCY) Seed cotton yield is the most important trait and the final product ready for usage in different industries. In the current study, significant differences were observed among cotton genotypes, stress treatments, and their interactions with seed cotton yield (Table 1). The mean data of five cotton genotypes revealed the drastic impact of heat stress on seed cotton yield (Fig. 3c). Results revealed that heat stress reduced SCY from 15.1 % in BH-254 to 27.0 % in BH-232. Maximum SCY under heat stress was recorded in BH-232 (1646.7 kg ha1) followed by BH-200 (1492.7 kg ha1) while the lowest seed cotton yield was recorded in BH-306 (1202 kg ha1) (Fig. 3c). The correlation coefficient analysis unveiled the presence of highly significant and positive correlation

5. Discussion Heat stress is one of the major constrain in improving cotton yield and fibre quality as it affects several yields and qualityassociated physio-chemical and metabolic processes (Xu et al., 2020). The development of new cotton genotypes and improving 5

M.I. Yousaf, Q. Hussain, Mona S Alwahibi et al. Journal of King Saud University – Science 35 (2023) 102379

Fig. 3. Impact of Heat stress on (a) Peroxidases (POXs) and (b) Total superoxide dismutase (T-SOD) activity (c) seed cotton yield in cotton genotypes.

Fibre quantity and quality are also greatly affected by the increase in temperature. In the current study, ginning out turn (GOT) and staple length were significantly reduced under stress conditions. The reduction in GOT and staple length is associated with a decrease in cell division and photosynthetic ability (Abro et al., 2021). Correlation analysis also showed a negative but strong correlation of seed cotton yield with GOT and staple length under control as well as heat stress conditions as shown by Bhatti et al. (2020), Abro et al. (2021), Aslam et al. (2022). Photosynthesis is one of the key physiological processes which is responsible for yield potential and sustainability. However, heat stress adversely affects plant growth and development by halting and ceasing plant photosynthesis (Hassanuzzaman et al., 2013). Results revealed a differential response of net photosynthesis under heat stress conditions (Fig. 3). It was observed that heat stress significantly reduced the net photosynthetic rate in cotton genotypes. The reduction or sometimes inhibition of net photosynthetic rate under stress conditions might be attributed to the reduction in chlorophyll contents, increase in ionic conductance of thylakoid membranes, and disruption in RuBisCo activity (Crafts-Brandner and Law, 2000; Karademir et al., 2018). Heat stress in cotton is accompanied by oxidative stress, which disrupts the composition and concentration of biochemical and metabolic compounds. One of the major impacts of oxidative stress in cotton is the increased accumulation of reactive oxygen species (ROXs), especially hydrogen peroxide, which increases the peroxi-

the existing ones with high-temperature tolerance along with higher cotton yield is the primary focus of plant breeders to combat climate change. To achieve this target, screening and evaluation of existing germplasm for seed cotton yield and its associated physio-chemical, agronomical and fibre-related traits under stress conditions is pivotal to assess the magnitude of genetic diversity for these traits (Yousaf et al., 2022). The results obtained through combined ANOVA showed the existence of sufficient genotypic variations among cotton genotypes for studied traits, which indicates the extent of genetic variability present in the studied genotypes and could be used to develop heat stresstolerant cotton genotypes as suggested by Riaz et al., 2021. However, the variations in the studied traits were non-significant for years as a source of variation, indicating the minute impact of different growing seasons, suggesting the pooling of data as recommended and used by Saroj et al., (2021). Results revealed that the performance of seed cotton yieldassociated traits was greatly reduced under heat stress (Fig. 4). Plant height, nodes per plant and sympodial branches per plant were significantly reduced under stress. This might be due to a decrease in the internodal distance, and photosynthate availability because of the reduction in chlorophyll contents and net photosynthesis (Abro et al., 2021). Cotton genotype CIM-600 was the best performer due to higher plant height, nodes per plant, and sympodial branches per plant. Several other studies also categorize CIM-600 as a heat-tolerant cotton variety (Majeed et al., 2021). 6

Journal of King Saud University – Science 35 (2023) 102379 M.I. Yousaf, Q. Hussain, Mona S Alwahibi et al. Fig. 4. Impact of Heat Stress on Cotton Genotypes under Current study.

dation of lipid bilayers and the degradation of cellular membranes. Therefore, a lower concentration of H2O2 in the cotton plants could serve as an indicator of heat stress tolerance (Majeed et al., 2019). In the current study, the concentration of H2O2 was increased in all-cotton genotypes under heat stress conditions. However, the highest accumulation of H2O2 was observed in BH-306, which appeared to be the least productive and heat susceptible cotton genotype. This was evident that a higher concentration of ROS species like H2O2 had a strong negative correlation with seed cotton yield under heat stress as shown by correlation analysis. Similar findings were reported by Zhang et al. (2014), Majeed et al. (2019), who reported a highly negative correlation between seed cotton yield and hydrogen peroxide concentration under stress conditions. To check, minimize or detoxify the adverse effects of reactive oxygen species, several enzymatic and non-enzymatic antioxidants are produced in cotton plants under heat stress, which act as detoxifying or scavenging agents (Gür et al., 2010; Sekmen et al., 2014). The highest accumulation of CAT was observed in BH-306 while the lowest CAT activity was recorded in BH-232. However, the accumulation of POXs and T-SOD was found maximum in BH-232, respectively under heat stress conditions, and these were the main reasons for the lowest accumulation of H2O2 and highest seed cotton yield in BH-232 under stress conditions. The same results were also shown by many other researchers who revealed that an increase in antioxidant activity decreases the accumulation of ROXs in stress-tolerant genotypes, which has a very significant and positive impact on economical yield (Gür et al., 2010; Sekmen et al., 2014). However, the accumulation of SOD decreases at the temperature of 45 °C while the concentration of CAT, POXs, and APX kept on increasing with the increase in temperature (Sarwar et al., 2018).

6. Conclusion In this study, heat stress was found to have a very negative impact on plant growth and development by significantly reducing plant height (PH), nodes per plant (N/P), sympodial branches per plant (SB/P), number of bolls per plant (NB/P), ginning out-turn (GOT), net photosynthetic rate (Pn), staple length (S.L) and seed cotton yield (SCY). However, the concentration of hydrogen peroxide (H2O2) was increased under heat stress as an indication of oxidative stress. To combat the negative impact of heat stress and higher concentration of H2O2, cotton genotypes increased the accumulation of certain enzymatic antioxidants i.e., CAT, POXs, and T-SOD. Based on the results, it is therefore recommended to cultivate the heat-tolerant cotton genotype BH-232 in heat-prone areas of the country.

📖 中文全文 Chinese Full Text

中文

# 翻译

## 标题:热胁迫对陆地棉(Gossypium hirsutum L.)基因型农艺形态、理化及纤维相关参数的影响

**作者:** Muhammad Irfan Yousaf a,b,1, Quaid Hussain c,1, Mona S Alwahibi d, Muhammad Zahid Aslam a, Muhammad Zeeshan Khalid e, Sabir Hussain a, Akash Zafar f, Syed Awais Sajid Shah a, Arshad Mehmood Abbasi g,h, Asrar Mehboob b, Muhammad Waheed Riaz c,i,⇑, Mohamed S. Elshikh d,⇑

**作者单位:** a 巴基斯坦巴哈瓦尔普尔棉花研究中心(CRS),63100 b 巴基斯坦萨希瓦尔玉米和谷子研究所(MMRI),57000 c 中国浙江农林大学亚热带林业国家重点实验室,杭州,311300 d 沙特阿拉伯利雅得国王沙特大学理学院植物学与微生物学系,11451 e 巴基斯坦巴哈瓦尔普尔伊本·白图泰大学植物育种与遗传学系,63100 f 巴基斯坦巴哈瓦尔普尔区域农业研究所,63100 g 巴基斯坦阿伯塔巴德COMSATS大学环境科学系,22020 h 意大利库内奥省波伦佐美食科学大学,12042 i 中国浙江农林大学浙江省中药资源保护与创新重点实验室,杭州,311300

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## 摘要

不可预测的气候条件变化,尤其是高温,正在对棉花可持续生产构成持续威胁。本研究旨在探究热胁迫对若干形态生理、生化及纤维品质相关性状的影响。结果表明,陆地棉基因型及胁迫处理在农艺形态、理化及纤维长度相关参数方面存在显著变异。合并数据的进一步分析揭示,热胁迫对所有研究性状均产生了不利影响。在热胁迫条件下,植株高度、单株节数、单株果枝数、单株铃数、衣分和纤维长度均显著降低。在棉花基因型BH-200中观察到净光合速率(Pn)显著降低达28.6%(从24.7降至19.2 μmol m⁻² s⁻¹)。由于氧化胁迫的发生,热胁迫下过氧化氢(H₂O₂)的积累从BH-306的7.1%增加至BH-200的28.7%。在高温胁迫条件下,抗氧化酶即过氧化氢酶(65%–74%)、过氧化物酶(54%–169%)和超氧化物歧化酶(52%–98%)的积累均显著增加。相关系数分析揭示,在热胁迫条件下,籽棉产量与单株节数(r = 0.432*)、净光合速率(r = 0.829**)、过氧化物酶(r = 0.974**)和超氧化物歧化酶(r = 0.868**)呈显著正相关。然而,籽棉产量与衣分(r = -0.466*)、纤维长度(r = -0.898**)、过氧化氢(r = -0.955**)和过氧化氢酶(r = -0.904**)也呈负相关且具有统计学意义。总体结果表明,棉花基因型BH-232相较于其他参试基因型具有相对较高的耐热性,而BH-306对热胁迫表现出最高的敏感性。因此,BH-232在通过审定后可推荐在巴基斯坦高温易发地区进行大面积种植。

**关键词:** 高温;抗氧化酶;活性氧;光合作用;气候变化;纤维长度

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## 1. 引言

不断变化的环境条件正在通过改变主要大田作物的发育行为和抵御恶劣环境条件的能力,对其生产力和可持续性构成持续威胁。由于城市化、荒漠化、盐渍化和人类人口不受控制的增长,耕地不断退化,加剧了气候变化的影响。若干环境因素决定了作物植株的生产力,包括热量、干旱、降水、湿度和日照时数。然而,高温或热胁迫是包括棉花在内的作物生长和发育的主要限制因素之一。Singh等(2007)报道,即使温度比最适生长温度升高1°C,棉花皮棉产量也可能减少达110 kg ha⁻¹。

棉花是最重要的天然纤维和油料工业作物(Salimath等,2021)。2020–21年度,全球棉花种植面积达3142万公顷,产量为1.1148亿包(每包480磅),平均单产为773 kg ha⁻¹(USDA,2022)。在巴基斯坦,2021–22年度棉花种植面积为193.7万公顷,产量为832.9万包,平均单产为731 kg ha⁻¹(ESP,2021-22)。尽管巴基斯坦的每公顷棉花产量非常接近世界平均水平,但仍远低于主要产棉国,即澳大利亚(2217 kg ha⁻¹)、中国(1976 kg ha⁻¹)、土耳其(1804 kg ha⁻¹)、巴西(1720 kg ha⁻¹)和美国(957 kg ha⁻¹)(USDA,2022)。巴基斯坦棉花产量较低的主要原因是投入品价格高、投入品供应不足、病虫害发生率高、干旱胁迫、热胁迫、缺乏机械化采收以及优质种子供应不足。

在棉花中,对热最敏感的阶段之一是开花期,这导致严重的花器脱落、植株生长受阻、铃数和铃重减少,最终造成显著减产(Xu等,2020)。较高温度(32–40°C)对根系发育和气孔导度产生负面影响。此外,高于29°C的温度也会降低铃重(Lokhande和Reddy,2014)。种子萌发率受高温(>37°C)的显著影响,同时花粉管的萌发和伸长也会降低(Burke等,2004)。Salman等(2019)研究表明,热胁迫下棉花产量的降低是由于萌发率、净光合速率、相对细胞损伤、果枝数、铃重的降低以及花、蕾和铃脱落增加所致。除棉花产量外,热胁迫下纤维品质也会因短纤维增加、纤维细度和纤维均匀性降低而下降(Zafar等,2021)。因此,在胁迫条件下严格评估棉花基因型以鉴定耐性基因型对植物育种家而言是一项严峻挑战。本试验研究旨在评估当地棉花基因型的耐热性,并鉴定有助于棉花耐热性的关键性状。

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## 2. 材料与方法

### 2.1 试验材料与地点

本试验研究在巴哈瓦尔普尔棉花研究中心(CRS)的研究区域进行(北纬29°22′29.22960″,东经71°38′16.11240″,海拔115 m),连续两个棉花生长季(2020–21、2021–22年度)。试验材料由五个陆地棉基因型组成,即BH-254、BH-234、CIM-600、BH-200和BH-306。

### 2.2 试验设计

试验在田间进行,设两个处理:1)对照;2)热胁迫,连续两个棉花生长季(2020–21和2021–22年度)。对照处理中,棉花于3月第二周播种;胁迫处理中,播种于4月第三周进行(晚播)。根据往年气象数据,晚播作物的开花和蕾期预计会经历高温(40°C以上)。

试验采用随机完全区组设计(RCBD),三次重复,处理按裂区排列。

关键气候因子——温度(°C)和降水量(mm)的数据从播种至蕾铃发育期(播种后60天)逐日记录。记录两个处理和连续两个年度(2020–21和2021–22年度)的数据。数据显示,对照处理播种当月最高温度较低,2020–21年度为34°C,2021–22年度为36°C,而热胁迫处理的最高温度分别为36°C(2020–21)和40°C(2021–22)(图1a)。此外,高温处理下的日均最高温度显著高于对照(图1b)。

### 2.3 植株参数的测量/记录

#### 2.3.1 形态生理及纤维相关参数

在第二次收花时记录若干植株形态性状,即株高(PH)、单株节数(N/P)、单株果枝数(SB/P)和单株铃数(NB/P);收获后测定衣分(GOT)和籽棉产量(SCY)。净光合速率(Pn;μmol m⁻² s⁻¹)通过CI-320手持式近红外气体分析仪进行测定,该仪器的使用参考了Yousaf等(2022)的推荐方法。棉花的纤维长度通过大容量测试仪(HVI)测量,单位为毫米。

#### 2.3.2 过氧化氢(H₂O₂)积累的测量方法

H₂O₂活性的测定参照Velikova等(2000)开发并使用的方法进行。

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## 3. 酶促抗氧化酶活性测定

### 3.1 酶提取液的制备

采集充分展开的健康叶片,用蒸馏水彻底清洗后在液氮(N₂)中冷冻,并于-80°C保存,用于评估不同酶的抗氧化活性。从保存的样品中取5 g叶片样品,在预冷的10 ml磷酸钾缓冲液(pH 7.8)中仔细研磨。然后将反应混合物在4°C下以14000 rpm离心10 min。上清液用于通过紫外-可见分光光度计在不同波长下的吸光度测定抗氧化活性(Sarwar等,2019)。

### 3.2 过氧化氢酶、过氧化物酶和超氧化物歧化酶活性的测定(U mg⁻¹ 蛋白)

这些酶的活性通过紫外-可见分光光度计在不同波长下进行测量。过氧化氢酶活性按照Liu等(2009)的方法在240 nm波长下测定。过氧化物酶活性按照Liu等(2009)的方法在470 nm波长下记录。同样,超氧化物歧化酶(SOD)活性通过SOD在560 nm波长下的吸光能力进行分光光度测定,参照Beauchamp和Fridovich(1971)的方案进行。

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## 3.3 统计分析

对籽棉产量及其相关的形态生理和生化性状数据进行方差分析(ANOVA)和相关系数分析(Steel等,1997)。为进行上述分析,使用了三个统计软件包,即Statistix 8.1、XLSTAT 21.0和Origin 21.0。此外,使用Microsoft Excel 2021和Adobe Illustrator 22.0进行结果图示。

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## 4. 结果

合并方差分析揭示,在对照和高温条件下,棉花基因型在形态生理、生化和纤维相关参数方面存在高度显著变异(表1)。然而,除单株铃数外,所有研究性状的年度变异源均不显著。基于这一事实,将两年数据合并并取平均值进行进一步分析。

### 4.3 籽棉产量相关农艺性状

相关分析揭示,在正常(r = 0.465*)和热胁迫条件(r = 0.432*)下,单株节数(N/P)与籽棉产量(SCY)之间存在显著正相关(表2)。然而,籽棉产量与GOT在正常(r = -0.548*)和热胁迫条件(r = -0.466**)下均呈显著负相关。SCY与PH和NB/P在正常(r = 0.96, r = 0.179)和热胁迫(r = 0.235, r = 0.236)条件下均呈正相关但不显著。另一方面,SB/P与SCY在两种胁迫条件下均呈负相关但不显著(r = -0.317, r = -0.270)(表2)。与对照相比,热胁迫处理中籽棉产量(SCY)及其相关农艺性状(即PH、N/P、SB/P、NB/P和GOT)均显著降低(表3)。

### 4.4 纤维长度

纤维长度(SL)是从纺织工业角度来看最重要的纤维性状之一,在正常和热胁迫条件下,棉花基因型间表现出显著差异(表1)。结果表明,棉花基因型BH-254的纤维长度最高(29.2 mm),其次是BH-306(29.1 mm)和CIM-600(29.0 mm)(图2a)。另一方面,BH-232在正常(28.2 mm)和热胁迫处理(27.9 mm)下纤维长度最低,其次是BH-200(28.5 mm, 28.2 mm)。相关系数分析表明,在正常(r = -0.921**)和热胁迫处理(r = -0.898**)下,纤维长度(SL)与籽棉产量(SCY)之间存在高度显著的强负相关(表2)。

### 4.5 净光合速率(Pn)

光合作用是棉花的关键生理过程,负责实现最佳生长和发育以获得更高生产力。方差分析揭示,在正常和胁迫条件下,棉花基因型间净光合速率(Pn)存在显著差异(表1)。结果进一步表明,与对照相比,所有棉花基因型在热胁迫下的净光合活性(Pn)均显著下降(图2b)。热胁迫下Pn降低幅度最大的是BH-200(28.6%),从对照的24.7 μmol m⁻² s⁻¹降至胁迫条件下的19.2 μmol m⁻² s⁻¹(图2b)。然而,BH-306在热胁迫下Pn降低幅度最小(7.0%),尽管BH-306在对照和热胁迫处理下的总体净光合速率在所研究的棉花基因型中最低(图2b)。相关系数分析揭示,净光合速率(Pn)与籽棉产量(SCY)在对照(r = 0.838**)和热胁迫处理(r = 0.829**)下均呈强正相关(表2)。

### 4.6 活性氧(ROS)的积累

#### 4.6.1 过氧化氢(H₂O₂)

合并方差分析结果显示,在热胁迫条件下,棉花基因型间过氧化氢(H₂O₂)积累存在高度变异(表1)。进一步结果表明,与对照相比,所有棉花基因型在热胁迫条件下过氧化氢(H₂O₂)的积累均显著增加,表明胁迫下植株经历了更高的氧化胁迫。在热胁迫下,H₂O₂积累最高的是BH-306(13.1 μmol g⁻¹),而对照为9.6 μmol g⁻¹;H₂O₂积累最低的是BH-232,热胁迫下为7.2 μmol g⁻¹,而对照处理为4.8 μmol g⁻¹(图2c)。此外,过氧化氢(H₂O₂)与籽棉产量在对照(r = -0.972**)和热胁迫条件(r = -0.955**)下均呈非常强的负相关(表2)。

#### 4.6.2 酶促抗氧化酶的积累

合并方差分析揭示,在胁迫处理下,CAT、POX和SOD存在显著差异(表1)。然而,这些抗氧化酶在年度间的变异及其交互作用均不显著。进一步结果表明,热胁迫触发了棉花基因型中若干抗氧化酶(包括CAT、POX和SOD)的积累(图2d、图3a和b)。CAT积累增加幅度最大的是BH-254,热胁迫下CAT积累(238.0 U mg⁻¹ 蛋白)比对照(82.6 U mg⁻¹ 蛋白)高189%。然而,热胁迫下CAT积累最高的是BH-306(248.9 U mg⁻¹ 蛋白)。在研究的棉花基因型中,CAT积累与籽棉产量在两种条件下均呈强负相关且具有高度显著性(rₙ = -0.937**, rₕ = -0.904**)(表2)。POX积累最高的是BH-232(115.9 U mg⁻¹ 蛋白),POX积累最低的是BH-306(83.6 U mg⁻¹ 蛋白)。然而,POX积累增加百分比最高的是BH-306,热胁迫条件下POX积累比对照高168%(图3a)。相关系数分析揭示,POX积累与籽棉产量在对照(r = 0.920**)和热胁迫条件(r = 0.974**)下均呈强正相关且具有高度显著性(表2)。同样,在热胁迫条件下,棉花基因型BH-232的SOD活性最高(109.8 U mg⁻¹ 蛋白),BH-306的活性最低(84.8 U mg⁻¹ 蛋白)。T-SOD活性增加百分比最高的是BH-306(97.8%),从对照的42.9 U mg⁻¹ 蛋白增至热胁迫条件下的84.8 U mg⁻¹ 蛋白。

籽棉产量与N/P(r = 0.432*)、Pn(r = 0.829**)、POX(r = 0.974**)和T-SOD(r = 0.868**)在热胁迫条件下呈显著正相关。然而,在热胁迫条件下,SCY与GOT(r = -0.466**)、SL(r = -0.898**)、H₂O₂(r = -0.955**)和CAT(r = -0.904**)呈强负相关(表2)。

#### 4.6.3 籽棉产量(SCY)

籽棉产量是最重要的性状,是可供不同工业使用的最终产品。在本研究中,棉花基因型、胁迫处理及其互作对籽棉产量均表现出显著差异(表1)。五个棉花基因型的平均数据揭示了热胁迫对籽棉产量的严重影响(图3c)。结果表明,热胁迫使SCY降低幅度从BH-254的15.1%到BH-232的27.0%不等。热胁迫下SCY最高的是BH-232(1646.7 kg ha⁻¹),其次是BH-200(1492.7 kg ha⁻¹),最低的是BH-306(1202 kg ha⁻¹)(图3c)。相关系数分析揭示,在热胁迫条件下,籽棉产量与N/P(r = 0.432*)、Pn(r = 0.829**)、POX(r = 0.974**)和T-SOD(r = 0.868**)之间存在高度显著的正相关。然而,在热胁迫条件下,SCY与GOT(r = -0.466**)、SL(r = -0.898**)、H₂O₂(r = -0.955**)和CAT(r = -0.904**)呈强负相关(表2)。

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## 5. 讨论

热胁迫是提高棉花产量和纤维品质的主要限制因素,因为它影响若干与产量和品质相关的理化和代谢过程(Xu等,2020)。开发耐高温且高产的棉花新基因型并改良现有基因型是植物育种家应对气候变化的首要目标。为实现这一目标,在胁迫条件下对现有种质进行籽棉产量及其相关理化、农艺和纤维相关性状的筛选和评估,对于评估这些性状的遗传多样性程度至关重要(Yousaf等,2022)。通过合并方差分析获得的结果表明,棉花基因型在所研究性状上存在足够的基因型变异,表明所研究基因型中存在一定程度的遗传变异性,可用于开发耐热棉花基因型,如Riaz等(2021)所建议的那样。然而,所研究性状在年度变异源上的变异不表明不同生长季的影响微乎其微,建议合并数据,如Saroj等(2021)所推荐和使用的。

结果表明,热胁迫下籽棉产量相关性状的表现大幅降低(图4)。株高、单株节数和单株果枝数在胁迫下显著降低。这可能是由于节间距离减小以及由于叶绿素含量和净光合速率降低导致的同化物供应减少(Abro等,2021)。棉花基因型CIM-600因较高的株高、单株节数和单株果枝数而表现最佳。其他几项研究也将CIM-600归类为耐热棉花品种(Majeed等,2021)。

纤维数量和品质也受到温度升高的显著影响。在本研究中,衣分(GOT)和纤维长度在胁迫条件下显著降低。GOT和纤维长度的降低与细胞分裂和光合能力下降有关(Abro等,2021)。相关分析还表明,在对照和热胁迫条件下,籽棉产量与GOT和纤维长度呈负相关但强相关,如Bhatti等(2020)、Abro等(2021)、Aslam等(2022)所示。

光合作用是决定产量潜力和可持续性的关键生理过程之一。然而,热胁迫通过抑制和停止植物光合作用对植物生长和发育产生不利影响(Hassanuzzaman等,2013)。结果表明,热胁迫下净光合速率表现出差异响应(图3)。据观察,热胁迫显著降低了棉花基因型的净光合速率。胁迫条件下净光合速率的降低或有时被抑制可能归因于叶绿素含量的降低、类囊体膜离子电导率的增加以及RuBisCo活性的破坏(Crafts-Brandner和Law,2000;Karademir等,2018)。

棉花中的热胁迫伴随着氧化胁迫,这会破坏生化代谢化合物的组成和浓度。棉花氧化胁迫的主要影响之一是活性氧(ROS)的积累增加,尤其是过氧化氢,它会增加脂质双分子层的过氧化和细胞膜的降解。因此,棉花植株中较低的H₂O₂浓度可以作为耐热性的指标(Majeed等,2019)。在本研究中,所有棉花基因型在热胁迫条件下H₂O₂浓度均有所增加。然而,H₂O₂积累最高的是BH-306,这似乎是生产力最低且对热敏感的棉花基因型。很明显,较高浓度的ROS(如H₂O₂)与热胁迫下籽棉产量呈强负相关,如相关分析所示。Zhang等(2014)、Majeed等(2019)也报道了类似的研究结果,他们报告在胁迫条件下籽棉产量与过氧化氢浓度之间存在高度负相关。

为了检查、最小化或解毒活性氧的不利影响,棉花植株在热胁迫下会产生若干酶促和非酶促抗氧化酶,它们作为解毒或清除剂发挥作用(Gür等,2010;Sekmen等,2014)。CAT积累最高的是BH-306,而CAT活性最低的是BH-232。然而,在热胁迫条件下,POX和T-SOD的积累在BH-232中最高,这是BH-232在胁迫条件下H₂O₂积累最低和籽棉产量最高的主要原因。许多其他研究人员也展示了相同的结果,他们揭示抗氧化酶活性的增加会降低耐性基因型中ROS的积累,这对经济产量具有非常显著和积极的影响(Gür等,2010;Sekmen等,2014)。然而,在45°C时SOD的积累降低,而CAT、POX和APX的浓度则随着温度的升高而持续增加(Sarwar等,2018)。

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## 6. 结论

本研究发现,热胁迫通过显著降低株高(PH)、单株节数(N/P)、单株果枝数(SB/P)、单株铃数(NB/P)、衣分(GOT)、净光合速率(Pn)、纤维长度(SL)和籽棉产量(SCY),对植株生长和发育产生了非常不利的影响。然而,过氧化氢(H₂O₂)的浓度在热胁迫下增加,表明氧化胁迫的发生。为应对热胁迫和较高浓度H₂O₂的不利影响,棉花基因型增加了某些酶促抗氧化酶(即CAT、POX和T-SOD)的积累。基于研究结果,建议在国家高温易发地区种植耐热棉花基因型BH-232。