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Article

Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars

by
Yunhe Wang
1,†,
Cunyao Bo
1,†,
Xiaohua Wang
2,
Xincheng Yang
1 and
Hongwei Wang
1,*
1
College of Agriculture, Shandong Agricultural University, Taian 271018, China
2
College of Agriculture and Forestry Science, Linyi University, Linyi 276000, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2024, 14(10), 2438; https://doi.org/10.3390/agronomy14102438
Submission received: 24 September 2024 / Revised: 11 October 2024 / Accepted: 18 October 2024 / Published: 21 October 2024
(This article belongs to the Special Issue Genetic Identification and Characterisation of Crop Agronomic Traits and Stress Resistance—2nd Edition)
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Abstract

:
We selected 46 core winter–spring wheat cultivars from China’s main wheat-producing areas as experimental materials to clarify the differences in the physiological parameters of their cold resistance and provide a theoretical basis and high-quality germplasm for cold resistance breeding. We investigated differences in their cold resistance under field conditions for two consecutive years, and determined the physiological parameters of the cold resistance, yield, and quality indicators of different winter–spring wheat cultivars. Our results showed that the cold resistance of winter wheat cultivars was higher than that of spring wheat cultivars. The chlorophyll (Chl), soluble sugar (SS), soluble protein (SP), and free proline (Pro) contents of different winter–spring wheat cultivars were positively correlated with cold resistance, and malondialdehyde (MDA) content was negatively correlated with cold resistance. The five physiological parameters can be used as physiological indicators for the breeding of cold-resistant cultivars. The cold resistance, yield, and quality indicators of different spring and winter wheat cultivars were comprehensively evaluated by using the average membership value and comprehensive score. It was found that the average membership value and comprehensive score of winter wheat cultivars were higher than those of spring wheat cultivars. Through classification using the K-means method, the cold-resistant, high-yield, and high-quality cultivars were screened out, namely, Jimai23 (JM23), Jimai44 (JM44), Shannong57 (SN57), and Jinmai 919 (JM919).

1. Introduction

Wheat (Triticum aestivum L.) is one of the three major food crops around the world, accounting for 21% of the world’s food supply [1]. China is the world’s largest wheat producer and consumer, accounting for 17% and 16% of the world’s total wheat production and consumption, respectively [2]. As one of the main food crops in China and around the world, high and stable yields, high quality, and stress resistance have remained important goals to be pursued in wheat production [3,4]. In recent years, with the increase in extreme weather events and the improper selection of wheat cultivars, frost damage has had a serious impact on wheat growth worldwide [5]. In particular, the major wheat-producing countries, namely, China, the United States, Australia, and Canada, have suffered the most severe production losses due to frost damage [6,7,8]. The screening and breeding of cold-resistant wheat cultivars are of great significance for coping with low-temperature frost damage and ensuring wheat yield and quality.
It is necessary for wheat to spend a certain amount of time at low temperatures during the vernalization stage. Based on the low-temperature conditions and duration required during the vernalization stage, wheat can be divided into strong-winter, winter, semi-winter, weak-spring, and spring cultivars. Wheat can survive under low-temperature conditions during the vernalization stage; however, too low a temperature will have a certain influence on the growth and development of the wheat [9]. When the temperature drops below 0 °C, wheat suffers from low-temperature damage, the cell membrane structure is destroyed, the cell sap concentration and cytoplasm area increase, and the characteristics of the organelles also change, eventually leading to the death of cells and plants [10,11]. The results of other studies have shown that when the temperature is −10 °C, spring wheat will not survive; however, when the temperature is −15 °C or lower, winter wheat still shows a certain ability to survive [12].
The ability of wheat to survive winter conditions is referred to as cold resistance [13]. Plant cold resistance is a quantitative trait controlled by multiple genes and is closely related to physiological parameters such as plant photosynthesis, osmotic regulatory substances, membrane lipid peroxidation, and antioxidant enzyme activity [14,15]. Photosynthesis is the main material basis and energy source for the growth and development of all green plants. Roughly 90% of wheat yield is derived from the contribution of photosynthesis [16,17]. Low-temperature stress can affect the synthesis of photosynthetic pigments and the energy metabolism of plants [18]. When wheat is under low-temperature stress, the chlorophyll (Chl) content of wheat leaves shows a continuous downward trend [19,20]. Soluble sugar (SS) is widely considered to be a cold-resistant protective substance, and its presence has been confirmed in many cold-resistant plants [21,22]. Krasensky et al. [23] found that plants accumulate SS under low-temperature stress to increase the concentration of cell sap in order to prevent damage to protoplasts caused by freezing, thereby ensuring the stability and integrity of the cell membrane and reducing plant frost damage. As an important osmotic regulatory factor, soluble protein (SP) is dissolved in water in the form of a small molecule and has hydrophilic and water-retaining properties, which have a certain influence on the cold resistance of plants [24]. Free proline (Pro) plays a role in maintaining redox balance and cell homeostasis under low-temperature stress, removing the harmful effects of reactive oxygen species, and protecting cells from oxidative damage [25,26]. Malondialdehyde (MDA) is one of the key indicators of lipid peroxidation. Under low-temperature stress, a large number of active oxygen free radicals are produced in plants, thereby producing peroxidation products such as MDA, which cross-links with macromolecules such as proteins or nucleic acids to form polymers, destroying cell membranes and functional molecules in cells [27,28].
The yield and quality of wheat are a complex combination of various traits, which are mainly controlled by genotype and environmental factors [29]. Understanding the relationship between wheat cold resistance and physiological parameters can enable a more thorough scientific evaluation of wheat cold resistance and ensure wheat yield and quality. Conversely, physiological substances, such as the Chl, SS, SP, and Pro contents of wheat, also affect wheat yield and quality in the later stages [30,31]. Low-temperature stress can damage the functional leaves of wheat, thereby affecting the synthesis of carbohydrates, slowing down the transport of total SS and SP from stems and leaves to grains, reducing the number of grains and grain filling rate, and ultimately leading to a decrease in grain yield and quality [32,33].
A considerable amount of research has been performed on the cold resistance of wheat [34,35,36]; however, the authors of the referenced studies mainly focused on a few cultivars, or the studies were conducted at fixed temperatures in a laboratory, with such conditions differing from the frost damage that occurs under complex climatic conditions in the field [37]. Therefore, this study selected 46 core cultivars of winter and spring wheat as experimental materials to avoid the contingency caused by a few cultivars. The frost damage of different winter and spring wheat cultivars was investigated under complex climatic conditions in the field, which more realistically reflected the differences in cold resistance of different wheat cultivars. The novel use of physiological parameters to screen physiological indicators of cold resistance allowed for an analysis of the physiological and biochemical characteristics of wheat during cold resistance. The cold resistance, yield, and quality indicators of different cultivars of wheat were comprehensively evaluated by the average membership and comprehensive values and classified by the K-means method. The purpose was to screen out cold-resistant, high-yield, and high-quality wheat germplasms, providing better germplasms and a theoretical basis for the future cold-resistant breeding of wheat more in line with actual production.

2. Materials and Methods

2.1. Experimental Design

This study was conducted in the experimental field of Zhaizi Village, Tai’an City, Shandong Province (36°1′51′′ N, 117°15′53″ E), from October 2022 to June 2024. The test site is located in the temperate continental monsoon climate zone, with an average annual temperature of 14.5 °C, average annual sunshine of 2759.1 h, and average annual precipitation of 901.4 mm. The soil texture is loam, and the previous crop of the test site was corn, which is planted twice a year. The temperature during the wheat-growing season is shown in Figure 1. The monthly minimum temperature in the 2022–2023 growing season was −15.1 °C, and the monthly minimum temperature in the 2023–2024 growing season was −13.9 °C. The 0–20 cm soil layer contained 78.92 mg·kg−1 of alkaline nitrogen, 53.63 mg·kg−1 of available phosphorus, 140.00 mg·kg−1 of quick-acting potassium, and 25.62 g·kg−1 of organic matter.
In this study, we selected 46 core winter–spring wheat cultivars from China’s main wheat-producing areas as experimental materials [38]. The cultivars were obtained from five provinces; namely, Shandong, Henan, Shanxi, Anhui, and Jiangsu (Table 1). The experiment adopted a randomized block design, with 3 replicate plots randomly set for each cultivar, a total of 138 experimental plots, and a plot area of 13.5 m2. Each cultivar was planted in 6 rows in the plot, with a row length of 9 m and a row spacing of 0.25 m. A protection row was set near the experimental site. Two sampling points of 1 m in length were set for each plot with bamboo poles for later trait investigation. The base fertilizer (N-P-K = 15-15-15) input was 750 kg·hm−2 of compound fertilizer, and 750 kg·hm−2 of urea was applied during the wheat jointing stage. After wheat sowing, the emergence of seedlings was checked promptly, and the seedlings were quickly transplanted for the plots with severe seedling shortages and broken ridges to avoid field emergence differences. The wheat was irrigated after sowing and during jointing and flowering, with 60 mm of water used each time. We used 20% clofopyralid EC + 6.9% fenoxaprop-ethyl emulsion in water at the wheat jointing stage, diluted with water at a ratio of 1:1000, and sprayed for weed control. We used 40% prothioconazole + 10% imidacloprid + 98% potassium dihydrogen phosphate + 0.01% brassinolide at the wheat heading stage, diluted with water at a ratio of 1:1000, and sprayed for pest control.

2.2. Testing Content and Methods of Measurement

2.2.1. Investigation of Frost Damage During the Winter Period of Wheat Under Field Conditions

According to the Rules of Field Investigation and Grading of Damage to Winter Wheat [39], the field frost damage levels of the tested wheat were classified during the wintering period.

2.2.2. Measurement of Chl Content

During the wheat greening period, a Chl meter (SPAD-502; Tokyo, Japan) was used to randomly select 10 representative leaves of different strains at each sampling point, with the front of the leaves facing upwards. The leaves were faced upwards and the relative chlorophyll content was measured at 1/3 of the distance from the stem, i.e., the SPAD value [40].

2.2.3. Measurement of SS Content

SS content was determined using the anthrone colorimetric method [41]. We used a plant SS content detection kit (Solarbio, Beijing, China). We weighed 0.1 g of wheat leaf tissue, added 1 mL of distilled water, and ground it into a homogenate. We poured it into a covered centrifuge tube and boiled it in water for 10 min. After cooling, it was centrifuged at 8000× g for 10 min at room temperature. We placed the supernatant in a 10 mL test tube and diluted it to 10 mL with distilled water. We pipetted 40 µL of the extract and mixed it with 40 µL of distilled water, 20 µL of working solution, and 200 µL of concentrated sulfuric acid, and placed this in a 95 °C water bath for 10 min. After cooling to room temperature, 200 μL was transferred it to a cuvette, and we measured the SS content at 620 nm by using a UV spectrophotometer (UV-30 Scan Spectrophotometer, Onda, Carpi, Italy).

2.2.4. Measurement of SP Content

SP content was determined by using the Coomassie Brilliant Blue G250 method [41]. We used a Bradford protein concentration determination kit (Solarbio, Beijing, China). We weighed 0.1 g of wheat leaf tissue, added 1 mL of extract, and ground it into homogenate. It was centrifuged at 8000× g for 10 min at room temperature, and then we took the supernatant and diluted it to 0.2 mg·mL−1 with distilled water. We pipetted 500 µL of the diluted supernatant and mixed it with 5 mL 1 × G250 staining solution, before it was kept at room temperature for 5 min. We measured the SP content by using a UV spectrophotometer (UV-30 Scan Spectrophotometer, Onda, Carpi, Italy) at 595 nm.

2.2.5. Measurement of Pro Content

Pro content was determined using the sulfosalicylic acid extraction and ninhydrin colorimetric method [41]. We used a Pro content detection kit (Solarbio, Beijing, China). We weighed about 0.1 g of wheat leaf tissue, added 1 mL of extract solution, and homogenized it in an ice bath. We placed it in a boiling water bath and shook it for 10 min. We then centrifuged it at 10,000× g for 10 min at room temperature and extracted the supernatant. Then, we pipetted 0.25 mL of the supernatant and mixed it with 0.25 mL of reagent 1 and 0.25 mL of reagent 2; then, we placed this in a boiling water bath for 30 min and shook it every 10 min. After cooling, we pipetted 0.2 mL into a cuvette and measured the Pro content at 520 nm by using a UV spectrophotometer (UV-30 Scan Spectrophotometer, Onda, Carpi, Italy).

2.2.6. Measurement of MDA Content

MDA content was determined using the thiobarbituric acid reaction method [42]. We used the MDA content detection kit (Solarbio, Beijing, China). We weighed about 0.1 g of wheat leaf tissue, added 1 mL of the extract solution, and homogenized this in an ice bath; then, we centrifuged it at 8000× g for 10 min at 4 °C, and extracted the supernatant. We pipetted 200 µL of the supernatant, 600 µL of the MDA detection working solution, and 200 µL of the reagent, mixed it thoroughly, kept it in a 100 °C water bath for 60 min, and cooled it in an ice bath. We centrifuged it at 10,000× g for 10 min at room temperature. We pipetted 1 mL into a cuvette and measured the MDA content at 532 nm and 600 nm in a UV spectrophotometer (UV-30 Scan Spectrophotometer, Onda, Carpi, Italy).

2.2.7. Measurement of Wheat Yield

After the wheat matured, it was harvested and threshed in different plots, and the yield of each cultivar of wheat was recorded after weighing [43].

2.2.8. Measurement of Wheat Grain Quality Traits

According to method AACC [44], the grain protein (GP) and wet gluten (WG) contents, grain hardness index (GHI), and sedimentation value (SV) of the wheat grains were determined using a near-infrared grain analyzer (DA7200; Stockholm, Switzerland), and the dough formation time (DFT) and dough stability time (DST) were determined using a farinograph (GWZJ/YS-26; Duisburg, Germany).

2.3. Statistical Analysis

Microsoft Excel (version 2020; Microsoft, Inc., Redmond, WA, USA) was used for data collation and chart preparation. SPSS statistical software (version 24; SPSS, Inc., Chicago, IL, USA) was used for one-way analysis of variance, and the average membership value and comprehensive score were calculated [45]. Cluster analysis was performed using the K-means method. Origin software (version 2021; Originlab, Inc., Northampton, MA, USA) was used for correlation analysis.
The membership value calculation formula is as follows
Uij = (Xij − Ximin)/(Xjmax − Xjmin)
The calculation formula of the inverse membership value is as follows
Uij = 1 − (Xij − Ximin)/(Xjmax − Xjmin)
The average membership value calculation formula is as follows
AUi = ∑Uij/n
In the formula, Uij represents the membership function value of the i-th cultivar for the j-th index; Xij represents the measured value of the j-th index of the i-th cultivar; Xjmax and Xjmin represent the maximum and minimum values of the j-th index, respectively; and AUi represents the average membership value of the i-th cultivar. Formula (1) indicates that a certain indicator is positively correlated with the comprehensive value of wheat cultivars; Formula (2) indicates that a certain indicator is negatively correlated with the comprehensive value of wheat cultivars.
The standard deviation coefficient calculation formula is as follows
Vj = ∑i = 1nXij − Xj − 2n − 1Xj-
The weight calculation formula for each indicator is as follows
Wj = Vj∑j = 1nVj
The comprehensive score calculation formula is as follows
D = ∑j = 1nUij × Wj
In the formula, Xj- represents the average value of the j-th index of each cultivar; Xij represents the measured value of the j-th index of the i-th cultivar; Vj represents the standard deviation coefficient of the j-th index; Wj represents the weight of the j-th index; and D represents the comprehensive score.

3. Results

3.1. Winter–Spring Characteristics and Frost Damage Levels of Different Wheat Cultivars

The cold resistance of wheat is closely related to its spring and winter characteristics. Strong-winter, winter, and semi-winter cultivars have higher cold resistance than weak-spring and spring cultivars. Frost damage to different winter–spring cultivars of wheat in the 2022–2023 growing season was more severe than in the 2023–2024 growing season (Table 2).
In the 2022–2023 growing season, the frost damage of different winter–spring wheat cultivars ranged from level 2 to level 5. Specifically, seventeen level 2 frost-damaged cultivars, such as Yannong161 (YN161), Yannong31 (YN31), and Yannong33 (YN33), had good cold resistance. These cultivars are generally strong-winter, winter, and semi-winter cultivars. Seventeen level 3 frost-damaged wheat cultivars, such as Yannong301 (YN301), Luyan128 (LY128), and Luyan955 (LY955), had average cold resistance. These cultivars are generally winter, semi-winter, and spring cultivars. Six level 4 frost-damaged cultivars, such as Yangmai24 (YM24), Yangmai25 (YM25), and Yangmai34 (YM34), and six level 5 frost-damaged cultivars, such as Jiuhaomai2 (JHM2), Yangmai15 (YM15), and Yangmai20 (YM20), had poor cold resistance; these are all spring cultivars.
In the 2023–2024 growing season, the frost damage of the different winter–spring cultivars of wheat was distributed at levels 2 to 4. Specifically, twenty level 2 frost-damaged cultivars, such as YN161, YN31, and YN33, had good cold resistance, with these being generally strong-winter, winter, and semi-winter cultivars; twenty level 3 frost-damaged wheat cultivars, such as YN301, LY128, and LY955, had average frost resistance, with these being generally winter, semi-winter, and spring cultivars; six level 4 frost-damaged cultivars, such as JHM2, YM15, and YM20, had poor frost resistance, and all are spring cultivars.

3.2. Comparison of the Physiological Parameters of Different Winter–Spring Wheat Cultivars

The Chl, SS, SP, Pro, and MDA contents of the different winter–spring wheat cultivars vary significantly (Table 3).
In the 2023–2024 growing season, the highest Chl content was found in the semi-winter cultivar Shannong55 (SN55), at 51.19 SPAD; the lowest value was found in the spring cultivar Yangmai27 (YM27), at 29.7 SPAD. The highest SS content was found in the semi-winter wheat cultivar YN31, at 51.19 mg·g−1 of fresh weight (FW); the lowest value was found in the spring wheat cultivar YM27, at 27.43 mg·g−1 of FW. The highest SP content was in found the semi-winter cultivar LY955, at 26.13 mg·g−1 of FW; the lowest value was found in the spring cultivar YM34, at 17.97 mg·g−1 of FW. The highest Pro content was found in the semi-winter cultivar SN55, at 235.38 μg·g−1; the lowest value was found in the spring cultivar Yangmai30 (YM30), at 66.11 μg·g−1. The highest MDA content was found in the spring cultivar YM24, at 35.36 nmol·g−1; the lowest value was found in the semi-winter cultivar JM44, at 17.35 nmol·g−1.
In the 2023–2024 growing season, the highest Chl content was found in the semi-winter cultivar Shannong40 (SN40), at 60.33 SPAD; the lowest value was found in the spring cultivar JHM2, at 42.23 SPAD. The highest SS content was found in the semi-winter wheat cultivar YN31, at 57.26 mg·g−1 of FW; the lowest value was found in the spring wheat cultivar YM27, at 27.72 mg·g−1 of FW. The highest SP content was found in the winter cultivar Luliang1 (LL1), at 29.64 mg·g−1 of FW; the lowest value was found in the spring cultivar YM34, at 23.12 mg·g−1 of FW. The highest Pro content was found in the semi-winter cultivar SN55, at 294.73 μg·g−1; the lowest value was found in the spring cultivar YM27, at 75.92 μg·g−1. The highest MDA content was found in the spring cultivar YM24, at 30.97 nmol·g−1; the lowest value was found in the winter cultivar LL1, at 12.78 nmol·g−1.

3.3. Relationship Between the Physiological Parameters of Cold Resistance of Different Winter–Spring Wheat Cultivars

As can be seen from Figure 2, there is a significant positive correlation between the cold resistance and Chl, SS, SP, and Pro contents of different winter–spring cultivars of wheat in the 2022–2023 growing season. The correlation coefficients were 0.58, 0.39, 0.44, and 0.69; there was a significant negative correlation with MDA content, and the correlation coefficient was −0.52.
In the 2023–2024 growing season, the cold resistance of different winter–spring cultivars of wheat had a significant positive correlation with the Chl, SS, SP, and Pro contents. The correlation coefficients were 0.60, 0.50, 0.42, and 0.51, respectively, with MDA content showing a significant negative correlation with a correlation coefficient of −0.40.
The results show that the higher the Chl, SS, SP, and Pro contents of wheat, the higher its cold resistance; the lower the MDA content, the higher the cold resistance of wheat. The five physiological parameters can all be used as indicators to evaluate the cold resistance of wheat.

3.4. Comparison of Wheat Yields of Different Winter–Spring Cultivars

The yields of different winter–spring wheat cultivars show significant differences (Figure 3).
In the 2022–2023 growing season, the wheat cultivars with the highest yields were the semi-winter cultivar LY 955, the winter cultivar Shannong38 (SN38), and the semi-winter cultivar YN31, with yields of 9635.71, 9422.10, and 9219.09 kg·hm−2, respectively; the cultivars with the lowest yields were the spring cultivars YM15, YM20, and Ningmai35 (NM35), with yields of 1066.07, 1174.87, and 1321.10 kg·hm−2, respectively.
In the 2023–2024 growing season, the wheat cultivars with the highest yields were the semi-winter cultivars LY955, SN57, and Zhengmai1860 (ZM1860), with yields of 10,417.12, 10,052.73, and 9750.982 kg·hm−2, respectively; the cultivars with the lowest yields were the spring cultivars NM35, YM30, and JHM2, with yields of 6070.66, 6066.43, and 5952.492 kg·hm−2, respectively.

3.5. Comparison of Quality Indices of Different Winter–Spring Wheat Cultivars

The GP content, WG content, DFT, DST, GHI, and SV of different winter–spring wheat cultivars are significantly different (Table 4).
In the 2022–2023 growing season, the spring cultivar YM27 had the highest GP content, at 16.39%; in comparison, the spring cultivar YM20 had the lowest GP content, at 12.37%. The semi-winter cultivar JM919 had the highest WG content, at 37.83%; in comparison, the spring cultivar Ningmai36 (NM36) had the lowest, at 23.38. The semi-winter cultivar Zhengmai366 (ZM366) had the longest DFT, at 5.60 min; the spring cultivar YM34 had the shortest DFT, at 3.47 min. The semi-winter cultivar JM44 had the longest DST, at 39.20 min; the semi-winter cultivar JM23 had the shortest DST, at 3.53 min. The semi-winter cultivar SN55 had the highest GHI, at 79.60; in comparison, the spring cultivar YM24 had the lowest GHI, at 55.33. The winter cultivar LL1 had the highest SV, at 43.97 mL; the spring cultivar YM34 had the lowest SV, at 17.45 mL.
In the 2023–2024 growing season, the spring cultivar YM27 had the highest GP content, at 16.22; the spring cultivar NM36 had the lowest GP content, at 12.59%. The semi-winter cultivar JM919 had the highest WG content, at 35.58%; the spring cultivar YM34 had the lowest WG content, at 23.46%. The semi-winter cultivars Zhengmai918 (ZM918) and JM919 had the longest DFT, both at 5.70 min; the spring cultivar YM15 had the shortest DFT, at 3.30 min. The semi-winter cultivar JM44 had the longest DST, at 42.20 min; the spring cultivar YM34 had the shortest DST, at 3.47 min. The GHI was the highest in the semi-winter cultivar Annong1589 (AN1589), at 78.91, and the lowest value was found in the spring cultivar YM24, at 56.58. The highest SV was found in the winter cultivar LL1, at 38.23 mL, and the lowest value was found in the spring cultivar YM34, at 17.45 mL.

3.6. Comprehensive Evaluation and Screening of Different Winter–Spring Wheat Cultivars

The average membership values and comprehensive scores of the cold resistance, yield, and quality indicators of the different winter–spring wheat cultivars were calculated. In general, the higher the average membership value and comprehensive score, the better the comprehensive traits of the cultivar. The K-means method was used to cluster the average membership values and comprehensive scores of the tested cultivars. After three clustering iterations, the cultivars were clustered into five groups. The average membership values and comprehensive scores of wheats in the first to the fifth groups decreased in sequence (Table 5 and Table 6).
In the 2022–2023 growing season, the average membership values of the examined wheat cultivars were distributed between 0.08 and 0.76, and the comprehensive scores were distributed between 0.24 and 2.40. The final cluster center values of the first group were the highest, at 0.72 and 2.3, including the semi-winter cultivars JM23, JM44, SN57, and Jinmai 919 (JM919); the cluster center values of the fifth group were the lowest, at 0.11 and 0.31, including the spring cultivars YM24, JHM2, YM15, YM20, and YM30.
In the 2023–2024 growing season, the average membership values of the examined wheat cultivars were distributed between 0.10 and 0.77, and the comprehensive scores were distributed between 0.26 and 2.19. The final cluster center values of the first group were the highest, at 0.68 and 2.07, including the semi-winter cultivars JM23, JM44, LY955, ZM136, ZM36, JM919, and AN1589; the cluster center values of the fifth group were the lowest, at 0.14 and 0.39, including the spring cultivars JHM2, YM15, YM20, YM24, YM30, and YM34.

4. Discussion

Wheat cold resistance is a complex biological characteristic determined by multiple factors [46]. Different winter–spring wheat varieties have different levels of cold resistance [47]. In this study, we investigated the cold resistance of 46 core winter–spring wheat cultivars from China’s main wheat-producing areas under field conditions; measured five physiological parameters of wheat during the greening period, including the Chl, SS, SP, Pro, and MDA contents; analyzed the relationship between wheat cold resistance and these physiological parameters; and screened out effective physiological indices of cold resistance. In addition, the level of physiological parameters also affects the formation of wheat yield and quality in the later stages.
The results of previous studies have shown that winter wheat cultivars have higher cold resistance than spring wheat cultivars [48]. Mu et al. [49] conducted an indoor freezing test and found that strong-winter wheat cultivars have the highest level of cold resistance, followed by winter and semi-winter cultivars, and spring wheat cultivars were found to have the lowest level of cold resistance. However, the authors of some studies have suggested that there is no necessary connection between the spring–winter characteristics of wheat and its cold resistance [50]. In this study, we also found that strong-winter, winter, and semi-winter wheat cultivars have a higher level of cold resistance than weak-spring and spring wheat cultivars.
Venzhik et al. [51] found that low-temperature stress has a direct impact on the synthesis and function of Chl in wheat leaves. Low-temperature stress reduces the activity of Chl synthase, thereby inhibiting the synthesis of Chl, which is similar to the results of this study in that the cold resistance of wheat is positively correlated with Chl content. After frost damage, the content of osmotic regulating substances such as SS and SP in wheat increases, increasing the concentration of cell sap and reducing plant frost damage [52,53]. Alexander et al. [54] found that wheat cultivars with strong frost resistance under low-temperature conditions will accumulate photosynthetic pigments, SS, and SP; in comparison, wheat cultivars with poor frost resistance will not accumulate SS, which is similar to the results of this study.
Low molecular weight compounds in the plant antioxidant system also participate in the plant’s defense against low-temperature stress. Pro acts as an osmotic regulator and cell membrane protector, exerting antioxidant functions and improving the cold resistance of wheat [55,56]. Ali et al. [57] showed that wheat cultivars with strong cold resistance under low-temperature stress can accumulate more Pro and have higher levels of antioxidant enzyme activity, which can reduce the degree of damage to wheat under adverse conditions, maintain higher photosynthetic efficiency, and allow for higher yields. Zhang et al. [58] showed that winter wheat varieties accumulate more Pro than spring varieties under low-temperature stress, improving the ability of wheat to resist low-temperature environments. In this study, we found that winter wheat cultivars under low-temperature stress have higher Pro content than spring wheat cultivars, which plays an important role in wheat’s resistance to low-temperature stress. The MDA content in plants can reflect the degree of damage to cell membranes under adverse stress conditions. The greater the degree of stress the plant suffers, the higher the MDA content [59,60]. In this study, we found that the cold resistance of different winter–spring wheat cultivars has a significant negative correlation with MDA content. Low-temperature freezing damage causes a large amount of MDA to accumulate in spring wheat cultivars, accelerating freezing damage to wheat.
The authors of other studies have highlighted that low-temperature stress has a negative impact on both wheat yield and quality [61,62]. Low-temperature stress limits the production of nitrogen compounds and non-structural carbohydrates, thereby reducing the transport of SP and SS from the stem to the grain, resulting in a decrease in wheat yield and quality [63,64]. The results of this study show that the yield and quality indicators of winter wheat cultivars; namely, WG content, DFT, DST, GHI, and SV, were higher than those of spring wheat cultivars. Low-temperature frost damage caused leaf damage to spring wheat cultivars with weak cold resistance, reduced nutrient synthesis and transportation, and reduced yield and quality. In this study, we found that the spring variety YM27 had the highest GP content, which may be determined by variations in characteristics and cold resistance-related genes. Some wheat cultivars were damaged by frost in the early growth stage but had better recovery ability in the later stages and could still maintain high yield and quality [65,66,67].
The effects of different natural environments on wheat growth and development vary; however, because this study was conducted only in Shandong Province, the results of this study have certain limitations. This study spanned two growing seasons and may not capture the effects of long-term trends or changes in climate conditions on wheat cold resistance, as cold resistance may change significantly over a longer time frame or under more diverse conditions. In addition, there are potential interactions between wheat cold resistance and factors such as pests and diseases, drought and flood disasters, and adaptability to different soil conditions, which affect the growth and development of wheat. In future experimental plans, we will combine different climate and environmental conditions to conduct a more in-depth study of the relationship between wheat cold resistance and biological and non-biological factors, so as to provide a more practical theoretical basis for wheat stress resistance breeding.

5. Conclusions

In the 2022–2023 growing season, seventeen level 2 frost-damaged cultivars such as YN161, seventeen level 3 frost-damaged cultivars such as YN301, six level 4 frost-damaged cultivars such as YM24, and six level 5 frost-damaged cultivars such as JHM2 were found; in the 2023–2024 growing season, twenty level 2 frost-damaged cultivars such as YN301, twenty level 3 frost-damaged cultivars such as YN301, and six level 4 frost-damaged cultivars such as JHM2 were found. Level 2 and level 3 frost-damaged cultivars are generally strong-winter, winter, and semi-winter wheat cultivars, and level 4 and level 5 frost-damaged cultivars are generally weak-spring and spring wheat cultivars. The cold resistance of winter wheat cultivars is greater than that of spring wheat cultivars. The Chl, SS, SP, and Pro contents of the different winter–spring wheat cultivars are positively correlated with cold resistance; in comparison, MDA content is negatively correlated with cold resistance. These five physiological parameters can be used as physiological indicators for the breeding of cold-resistant cultivars. After comprehensively evaluating the average membership values and comprehensive scores of the cold resistance, yield, and quality indicators of the different winter and spring wheat cultivars, it was found that the average membership values and comprehensive scores of winter wheat cultivars were higher than those of spring wheat cultivars. The average membership values and comprehensive scores of the different winter and spring wheat cultivars were classified using the K-means method, and the cold-resistant, high-yield, and high-quality cultivars were screened out, namely, JM23, JM44, SN57, and JM919.
In the process of cold-resistance breeding, the five physiological parameters of cold resistance selected in this study can help breeders judge the cold resistance of different wheat cultivars from the perspective of physiological indicators of cold resistance, and provide a theoretical basis for cold-resistance breeding. In addition, the four wheat cultivars selected in this study, namely, JM23, JM44, SN57, and JM919, can provide more cultivar options for growers and breeders who pursue high yields, high quality, and high cold resistance.

Author Contributions

Conceptualization, Y.W. and C.B.; formal analysis, Y.W.; methodology, Y.W. and C.B.; resources, X.W. and H.W.; software, Y.W. and X.Y.; writing—original draft, Y.W., X.Y. and C.B.; writing—review and editing, X.W. and H.W.; visualization, H.W.; supervision, C.B.; project administration, C.B.; funding acquisition, H.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2022YFF1001504).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agronomy 14 02438 g001
Figure 1. The monthly maximum temperature, monthly minimum temperature, and monthly average temperature during the wheat growing season ((A) 2022–2023; (B) 2023–2024).
Figure 1. The monthly maximum temperature, monthly minimum temperature, and monthly average temperature during the wheat growing season ((A) 2022–2023; (B) 2023–2024).
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Figure 2. Correlation between cold resistance level (CRL) and chlorophyll content (CC), soluble sugar content (SSC), soluble protein content (SPC), proline content (PC), and malondialdehyde content (MC) in different winter–spring wheat cultivars ((A) 2022–2023; (B) 2023–2024).
Figure 2. Correlation between cold resistance level (CRL) and chlorophyll content (CC), soluble sugar content (SSC), soluble protein content (SPC), proline content (PC), and malondialdehyde content (MC) in different winter–spring wheat cultivars ((A) 2022–2023; (B) 2023–2024).
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Figure 3. Yield of different winter–spring wheat cultivars ((A) 2022–2023; (B) 2023–2024). Note: Different letters following the data within each column indicate significant differences at p < 0.05 (n = 3).
Figure 3. Yield of different winter–spring wheat cultivars ((A) 2022–2023; (B) 2023–2024). Note: Different letters following the data within each column indicate significant differences at p < 0.05 (n = 3).
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Table 1. Wheat cultivars and their sources.
Table 1. Wheat cultivars and their sources.
CultivarsCodeCultivar Source
Yannong31YN31Yantai Agricultural Science Research Institute, Shandong Province
Yannong33YN33
Yannong161YN161
Yannong301YN301
Yannong745YN745
Jimai23JM23Shandong Academy of Agricultural Sciences
Jimai44JM44
Jimai60JM60
Luyan128LY128Shandong Luyan Agricultural Variety Co., Ltd. Shandong, China
Luyan955LY955
Shannong38SN38Shandong Agricultural University
Shannong40SN40
Shannong48SN48
Shannong55SN55
Shannong56SN56
Shannong57SN57
Shannong59SN59
Shannong69SN69
Luliang1LL1
Zhengmai113ZM113Henan Academy of Agricultural Sciences
Zhengmai136ZM136
Zhengmai366ZM366
Zhengmai918ZM918
Zhengmai1860ZM1860
Zhengmai1905ZM1905
Zhengmai2118ZM2118
Zhengmai7698ZM7698
Zhengshi9170ZS9170
Zhoumai36ZM36Zhoukou Academy of Agricultural Sciences
Jinmai919JM919Shanxi Agricultural University
Wanke1838WK1838Anhui Academy of Agricultural Sciences
Quanmai725QM725
JIUhaomai2JHM2Anhui Luyan Seed Industry Co., Ltd. Anhui, China
Annong1589AN1589Anhui Agricultural University
Yangmai15YM15Jiangsu Lixiahe Agricultural Science Research Institute
Yangmai20YM20
Yangmai24YM24
Yangmai25YM25
Yangmai27YM27
Yangmai30YM30
Yangmai34YM34
Ningmai13NM13Jiangsu Academy of Agricultural Sciences
Ningmai35NM35
Ningmai36NM36
Ningzhongmai1NZM1
Zhenmai12ZM12Zhenjiang Agricultural Science Research Institute in Jiangsu Hilly Region
Table 2. Winter and spring characteristics and frost damage levels of different wheat cultivars.
Table 2. Winter and spring characteristics and frost damage levels of different wheat cultivars.
CultivarsWinter-Spring Characteristics2022/2023 Frost Damage Level2023/2024 Frost Damage Level
SN38Strong-winter22
YN161Winter22
YN30133
SN5622
SN5932
LL122
YN31Semi-winter22
YN3322
YN74522
JM2322
JM4422
JM6022
LY12833
LY95533
SN4022
SN4832
SN5522
SN5722
SN6922
ZM3633
ZM13633
ZM36633
ZM91832
ZM186033
ZM190533
ZM211833
ZM769833
ZS917033
JM91933
WK183822
QM72533
AN158922
NZM133
ZM113Weak-spring22
JHM2Spring54
YM1554
YM2054
YM2443
YM2543
YM2754
YM3054
YM3443
NM3554
NM3643
NM1343
ZM1243
Table 3. The chlorophyll content (CC), soluble sugar content (SSC), soluble protein content (SPC), free proline content (PC), and malondialdehyde content (MC) of the different wheat cultivars.
Table 3. The chlorophyll content (CC), soluble sugar content (SSC), soluble protein content (SPC), free proline content (PC), and malondialdehyde content (MC) of the different wheat cultivars.
CultivarsYear of 2022/2023Year of 2023/2024
CC
(SPAD)		SSC
(mg·g−1 FW)		SPC
(mg·g−1 FW)		PC
(μg·g−1)		MC
(nmol·g−1)		CC
(SPAD)		SSC
(mg·g−1 FW)		SPC
(mg·g−1 FW)		PC
(μg·g−1)		MC
(nmol·g−1)
SN3848.47 abc39.59 efg21.63 def218.96 ab21.72 ijk58.70 abc43.53 bcd25.56 bcd252.97 a13.89 lmn
YN16146.77 def40.42 def20.34 fgh140.52 fgh28.28 bcd56.23 abc48.03 abc26.15 bcd149.24 ghi23.62 bcd
YN30143.47 lmn48.22 abc19.85 ghi82.48 klm24.24 efg52.73 ghi53.47 ab24.76 fgh126.31 ijk16.63 ghi
SN5650.90 ab34.98 ijk21.30 def200.52 b24.60 def58.00 abc49.82 abc24.75 fgh210.68 bcd16.56 hij
SN5946.90 cde38.24 efg21.98 def168.27 de22.98 ghi58.07 abc50.05 abc26.11 bcd152.22 fgh17.78 ghi
LL150.50 abc37.01 hij25.06 ab212.12 ab18.00 pq56.77 abc48.66 abc29.64 a231.53 ab12.78 n
YN3142.37 nop51.19 a20.95 def88.09 jkl20.36 klm51.83 hij57.26 a26.02 bcd102.86 mno16.63 ghi
YN3344.60 hij43.83 cde21.21 def144.04 efg19.88 mno53.60 def50.54 abc26.72 bcd180.15 def14.77 klm
YN74541.60 opq33.87 klm19.33 jkl150.89 def20.50 jkl51.47 ijk43.56 bcd25.34 cde184.80 cde16.13 ijk
JM2347.70 bcd38.66 efg21.34 def174.77 cd22.18 hij57.63 abc47.21 abc26.09 bcd89.27 op15.63 ijk
JM4447.57 bcd42.60 cde21.67 def202.65 b17.35 q57.40 abc51.51 abc26.75 bcd131.34 hij13.45 mn
JM6048.23 abc38.03 fgh21.61 def199.96 b22.52 hij56.20 abc48.44 abc26.94 bcd138.98 op19.28 efg
LY12850.13 abc35.55 ijk24.35 bc80.89 klm25.23 def55.97 abc50.67 abc24.16 ijk87.78 op19.14 efg
LY95541.10 pqr50.83 ab26.13 a114.77 hij19.28 opq59.13 ab31.74 jkl23.95 jkl109.90 klm18.42 fgh
SN4049.90 abc43.27 cde20.85 def170.94 cd19.52 nop60.33 a43.97 bcd25.14 efg219.80 ab15.38 jkl
SN4847.13 cde38.07 fgh20.73 efg208.76 b27.56 bcd56.37 abc44.81 bcd27.11 bcd205.28 bcd18.67 fgh
SN5551.53 a32.68 klm21.45 def235.38 a24.66 def58.00 abc41.35 cde24.80 fgh249.73 a20.65 cde
SN5748.47 abc33.24 klm21.58 def215.61 ab23.45 fgh58.93 abc40.29 def27.71 b226.31 ab18.78 fgh
SN6945.93 fgh42.18 def21.49 def194.98 bc27.37 bcd55.93 abc45.31 bcd27.52 bcd201.55 bcd16.25 ijk
ZM3650.33 abc45.72 bcd21.28 def209.51 b30.02 bcd59.87 ab52.90 ab25.44 bcd215.97 bc22.08 bcd
ZM13645.07 ghi33.31 klm22.43 de121.49 ghi28.89 bcd53.77 def45.82 bcd26.74 bcd143.97 hij18.28 fgh
ZM36647.30 bcd36.86 hij22.47 de130.22 fgh29.60 bcd57.20 abc46.86 bcd27.6 bc108.07 lmn19.21 efg
ZM91842.90 mon38.46 efg21.28 def121.55 ghi25.90 def51.07 jkl45.7 bcd25.35 cde144.74 hij22.08 bcd
ZM186044.27 ijk44.30 cde20.24 fgh141.22 fgh19.99 lmn53.60 def51.18 abc25.61 bcd106.95 mno16.13 ijk
ZM190545.07 ghi37.06 hij19.66 ab156.96 def22.59 hij49.10 lmn46.70 bcd24.14 ijk112.71 klm18.25 fgh
ZM211844.23 jkl37.64 ghi20.67 efg143.53 efg24.08 efg53.93 def47.44 abc25.52 bcd170.44 efg16.48 hij
ZM769841.33 pqr36.01 ijk20.37 fgh144.42 efg25.54 def49.77 klm46.68 bcd25.77 bcd205.05 bcd16.44 hij
ZS917049.93 abc39.88 def21.45 def102.63 ijk24.83 def58.50 abc49.47 abc26.56 bcd121.66 jkl16.91 ghi
JM91944.65 hij42.28 def20.81 def141.56 fgh28.78 bcd53.40 efg44.78 bcd24.34 hij180.70 def24.93 bcd
WK183846.20 fgh28.40 pq20.83 def114.91 ghi29.65 bcd55.67 bcd44.24 bcd26.34 bcd102.67 mno25.16 bcd
QM72547.77 bcd39.83 def19.23 lmn82.15 klm21.03 jkl56.27 abc49.17 abc23.77 lmn158.75 fgh15.64 ijk
AN158941.77 opq28.57 pq20.74 efg97.29 ijk25.18 def51.37 ijk35.10 ijk26.24 bcd87.41 op21.36 bcd
NZM147.93 bcd43.38 cde20.63 efg139.35 fgh31.79 abc56.60 abc47.65 abc26.18 bcd83.10 p24.66 bcd
ZM11348.80 abc31.35 mno22.81 cd139.51 fgh32.85 ab58.83 abc45.47 bcd26.06 bcd154.97 fgh26.74 ab
JHM240.44 rs30.07 nop18.98 mno92.97 jkl28.72 bcd42.23 o39.82 efg25.33 cde99.66 nop25.05 bcd
YM1542.73 mno37.58 ghi21.91 def77.14 klm32.49 abc50.73 jkl36.63 hij26.89 bcd126.66 ijk23.51 bcd
YM2040.73 qrs29.46 opq20.89 def82.62 klm28.31 bcd50.47 jkl39.20 fgh25.76 bcd101.34 nop26.02 abc
YM2443.47 lmn29.44 opq18.94 mno85.22 klm35.36 a53.07 fgh34.75 ijk23.93 jkl98.46 nop30.97 a
YM2545.17 fgh38.78 efg19.41 ijk94.59 jkl25.16 def54.43 cde47.05 abc25.25 def86.01 op22.33 bcd
YM2739.70 s27.43 q18.9 nop80.46 klm30.2 bcd46.33 n27.72 m23.63 mn75.92 p23.55 bcd
YM3040.77 qrs28.70 pq18.92 mno66.11 m29.00 bcd50.27 jkl29.49 klm24.61 ghi126.10 ijk22.08 bcd
YM3444.40 ijk30.70 nop17.97 p82.68 klm25.23 def53.13 dfg39.71 efg23.12 n130.20 ijk17.67 ghi
NM3540.47 rs31.94 lmn18.31 op83.16 klm28.62 bcd47.37 mn28.56 lm24.25 ijk76.49 p20.36 def
NM3645.97 fgh31.84 lmn20.04 fgh88.06 jkl25.99 def54.40 cde37.92 ghu25.68 bcd85.71 op18.08 fgh
NM1346.63 edf30.74 nop19.28 klm68.05 lm27.08 cde57.23 abc33.41 jll23.89 klm86.45 op21.36 bcd
ZM1243.77 klm38.68 efg21.1 def89.47 jkl32.48 abc50.93 jkl43.63 bcd26.15 bcd125.36 ijk26.38 ab
Note: Different letters following the data within each column indicate significant differences at p < 0.05 (n = 3).
Table 4. Grain protein content (GPC), wet gluten content (WGC), dough formation time (DFT), dough stability time (DST), grain hardness index (GHI), and sedimentation value (SV) of different winter–spring wheat cultivars.
Table 4. Grain protein content (GPC), wet gluten content (WGC), dough formation time (DFT), dough stability time (DST), grain hardness index (GHI), and sedimentation value (SV) of different winter–spring wheat cultivars.
CultivarsYear of 2022/2023Year of 2023/2024
GPC
(%)		WGC
(%)		DFT
(min)		DST
(min)		GHISV
(mL)		GPC
(%)		WGC
(%)		DFT
(min)		DST
(min)		GHISV
(mL)
SN3812.87 pqr27.80 ijk4.03 klm5.33 hi74.92 def32.24 ghi14.00 jkl25.02 nop4.10 klm6.97 ghi73.08 jkl28.40 ijk
YN16113.79 jkl34.54 b4.37 ghi7.40 f70.67 lm30.70 ghi14.07 ghi34.86 a4.40 ghi7.60 f70.99 mn29.58 hij
YN30114.16 hij24.65 pq3.90 nop4.00 opq70.81 lm27.42 klm14.45 def25.95 lm3.87 no4.63 opq71.24 mn27.04 kl
SN5613.65 klm29.52 ef4.90 def4.40 klm71.95 ijk39.05 bc14.27 efg25.92 lm4.20 jkl6.90 ghi73.92 ij29.74 hij
SN5914.36 ghi31.72 d5.03 cde4.77 jkl67.20 n37.25 cde14.82 cd33.00 b3.50 qr6.40 jkl69.81 n37.59 a
LL113.56 lmn33.14 c3.97 mno14.60 c70.08 m43.97 a14.03 hij33.50 b3.87 no7.13 fgh70.03 n38.23 a
YN3114.24 ghi25.80 no4.00 lmn4.00 opq73.80 fgh25.55 nop14.34 efg25.82 lm3.97 mno4.10 rst74.67 ghi26.64 klm
YN3313.28 nop24.39 pqr3.60 rst4.17 nop73.43 ghi26.29 mno13.87 lmn24.29 pqr3.77 op4.10 rst74.16 hij23.96 opq
YN74514.08 hij25.29 op3.53 st4.27 lmn73.05 hij24.11 qr14.21 fgh25.29 mno3.60 pq4.07 rst73.71 ijk24.59 nop
JM2314.93 cde35.47 b4.77 def7.37 f77.27 bc30.41 hij14.63 def35.45 a5.00 b9.03 d77.00 bcd30.73 fgh
JM4415.64 b30.40 e4.77 def39.20 a76.32 cde30.10 ijk15.43 b29.99 cd5.03 b42.20 a76.13 def31.80 efg
JM6013.47 mno36.97 a4.30 hij3.53 t72.53 ijk29.60 ijk14.29 efg35.48 a4.10 klm3.57 tu72.07 klm25.33 lmn
LY12813.69 klm33.01 c4.30 hij5.40 hi73.70 fgh32.40 ghi13.29 pq33.71 b4.40 ghi6.63 hij73.94 ij34.93 bc
LY95514.26 ghi33.10 c4.47 ghi4.20 mno75.71 cde30.43 hij14.48 def35.36 a4.50 fgh8.23 e75.78 efg32.52 def
SN4012.60 qr27.10 klm4.60 fgh4.63 klm71.10 lm34.26 def12.99 qr27.51 ij4.67 def7.03 fgh70.51 mn32.16 def
SN4814.11 hij30.54 e4.43 ghi4.37 klm78.97 a33.70 efg14.34 efg28.08 hi4.00 lmn4.17 qrs78.40 abc27.62 k
SN5513.45 mno29.12 fg4.47 ghi4.88 ijk79.60 a31.76 ghi14.79 cd27.52 ij4.40 ghi8.63 de78.60 ab28.50 1ijk
SN5715.22 bcd33.13 c5.47 ab4.65 klm71.72 jkl42.43 ab14.31 efg24.87 opq4.33 hij5.97 klm71.82 lm25.23 lmn
SN6913.46 mno28.78 fgh3.93 mno4.98 ijk71.46 klm28.68 jkl13.97 klm27.54 ij3.97 mno5.97 klm71.82 lm25.23 lmn
ZM3614.44 fgh27.38 jkl5.33 abc18.52 b75.63 cde37.46 cde14.25 efg27.58 ij5.70 a19.56 b76.06 def37.29 a
ZM13615.04 cde30.47 e5.60 a7.43 f75.81 cde38.23 cd15.36 b29.94 cd5.63 a8.70 de76.74 cde37.71 a
ZM36613.88 ijk29.33 fg4.30 hij9.63 d73.64 fgh26.04 nop13.87 lmn29.22 def4.40 ghi9.03 d73.23 jkl26.78 klm
ZM91814.32 ghi27.47 jkl3.77 opq3.73 rst61.04 p26.51 lmn14.15 ghi26.29 kl3.83 no5.20 mno60.54 pq21.34 rst
ZM186013.68 klm28.4 ghi4.10 jkl7.90 ef76.49 cde24.37 pqr14.46 def28.35 ghi3.80 nop7.57 f75.06 fgh25.06 lmn
ZM190513.53 mno24.53 pq4.13 ijk5.77 h71.04 lm25.18 opq13.45 op24.65 opq3.80 nop6.50 ijk71.36 mn27.01 kl
ZM211814.17 hij29.46 efg3.97 mno7.73 ef76.47 cde37.63 cde13.95 klm29.63 cde4.20 jkl7.57 f77.54 abc31.46 efg
ZM769814.73 efg30.48 e5.17 bcd9.23 d74.70 efg37.40 cde14.85 cd30.20 c4.97 bc8.43 e75.35 efg33.23 cde
ZS917014.29 ghi28.91 fgh4.43 ghi18.53 b78.29 ab33.48 fgh14.44 def28.61 fgh4.30 ijk19.18 b78.05 abc32.10 def
JM91915.26 bcd37.83 a5.57 a4.83 ijk76.20 cde34.60 def15.12 bc35.58 a5.70 a7.20 fgh76.06 def35.29 b
WK183814.48 fgh27.01 klm3.87 nop4.60 klm64.52 o25.55 nop14.79 cd26.94 jk3.97 mno4.83 op65.23 o25.14 lmn
QM72515.34 cde33.40 c4.67 efg4.40 klm60.29 p28.54 jkl15.39 b28.33 ghi4.73 de4.73 opq61.22 p27.94 jk
AN158914.50 fgh27.43 jkl4.50 fgh6.43 g76.75 bcd33.45 fgh14.50 def28.94 efg4.80 cd7.37 fg78.91 a33.87 bcd
NZM113.38 mno26.45 mn3.67 pqr3.90 pqr60.92 p24.54 opq13.20 pq26.74 k3.90 mno5.47l m60.72 pq24.01 opq
ZM11313.40 mno26.71 lmn4.07 jkl8.20 e76.00 cde22.45 r14.06 ghi26.41 kl4.20 jkl8.33 e75.18 fgh23.74 opq
JHM212.60 qr25.32 op3.67 pqr4.73 jkl57.98 q23.39 qr12.74 r25.71 lmn3.87 no4.70 opq58.56 rs25.37 lmn
YM1513.25 nop24.49 pq3.67 pqr6.33 g57.53 qr23.44 qr13.85 mn24.58 opq3.30 r4.50 pqr57.02 st22.27 qrs
YM2012.37 r23.54 qr4.10 jkl4.23 mno56.90 qrs24.66 opq12.74 r25.71 lmn3.87 no4.70 opq58.56 rs25.37 lmn
YM2413.63 klm23.7 qr3.67 pqr3.83 qrs55.33 s18.73 s13.78 no23.62 st3.47 qr3.73 stu56.58 t20.17 t
YM2513.53 mno27.9 hij3.53 st5.33 hi61.37 p27.14 klm14.11 ghi24.13 qrs3.60 pq5.53 lm62.11 p20.78 st
YM2716.39 a34.85 b4.57 fgh4.53 klm58.22 q25.54 nop16.22 a33.46 b4.50 fgh5.40 lmn60.66 pq29.97 ghi
YM3014.78 def25.36 op3.63 qrs4.33 lmn56.98 qrs17.64 s14.70 de25.23 mno3.33 r4.33 pqr58.05 rst17.62 u
YM3413.79 jkl23.72 qr3.47 t3.63 st56.14 rs17.45 s14.01 ijk23.46 t3.47 qr3.47 u57.15 st17.45 u
NM3512.99 opq28.46 fgh4.57 fgh7.73 ef64.96 o25.59 nop13.90 klm28.98 efg4.53 fgh7.20 fgh65.93 o25.65 lmn
NM3612.52 qr23.38 r3.97 mno3.53 t61.21 p24.41 pqr12.59 r23.85 rst3.97 mno4.90 nop59.53 qr23.11 pqr
NM1313.37 mno26.91 klm4.37 ghi6.37 g71.19 lm32.23 ghi13.29 pq25.84 lm4.60 efg7.13 fgh72.14 klm30.70 fgh
ZM1215.16 bcd31.72 d4.07 jkl14.38 c75.35 def25.52 nop15.31 b29.69 cde4.33 hij14.86 c77.81 abc24.90 mno
Note: Different letters following the data within each column indicate significant differences at p < 0.05 (n = 3).
Table 5. Average membership values and comprehensive scores of the different winter–spring wheat cultivars.
Table 5. Average membership values and comprehensive scores of the different winter–spring wheat cultivars.
CultivarsYear of 2022/2023Year of 2023/2024
Average Membership ValueComprehensive ScoreAverage Membership ValueComprehensive Value
SN380.511.920.51.42
YN1610.592.030.621.83
YN3010.421.530.421.21
SN560.612.110.531.52
SN590.581.90.621.82
LL10.622.090.591.8
YN310.491.80.51.41
YN330.421.640.431.19
YN7450.441.670.451.25
JM230.692.30.722.17
JM440.762.30.772.16
JM600.582.040.571.68
LY1280.541.850.541.75
LY9550.581.980.651.99
SN400.51.860.521.56
SN480.571.970.531.57
SN550.572.080.61.74
SN570.742.40.511.4
SN690.471.730.471.33
ZM360.652.070.642
ZM1360.672.130.652.07
ZM3660.491.680.471.41
ZM9180.371.280.380.97
ZM18600.461.650.471.36
ZM19050.411.50.381.1
ZM21180.551.920.531.64
ZM76980.622.010.591.82
ZS91700.61.960.581.74
JM9190.72.20.682.19
WK18380.451.590.471.26
QM7250.521.610.461.31
AN15890.592.070.631.93
NZM10.321.170.280.8
ZM1130.481.770.511.42
JHM20.090.260.120.44
YM150.10.250.10.29
YM200.080.240.130.47
YM240.170.580.190.44
YM250.280.940.260.66
YM270.350.80.411.27
YM300.120.240.110.26
YM340.170.620.220.46
NM350.230.660.280.95
NM360.220.840.230.64
NM130.391.320.431.33
ZM120.491.50.531.56
Table 6. The results of cluster analysis.
Table 6. The results of cluster analysis.
YeasClass-NumberGroup ClassificationFinal Cluster Center Average Membership ValueFinal Cluster Center Comprehensive Value
2022/20231JM23, JM44, SN57, JM9190.722.30
2YN161, YN31, JM60, LY128, LY955, SN55, SN38, SN40, SN48, SN56, SN59, LL1, ZM2118, ZM7698, ZS9170, ZM136, ZM36, AN15890.581.99
3YN301, YN33, YN745, SN69, ZM1905, ZM1860, ZM366, ZM113, ZM918, WK1838,
QM725, NM13, ZM12		0.451.57
4YM25, YM27, YM34, NM35, NM36, NZM10.260.84
5JHM2, YM15, YM20, YM24, YM300.110.31
2023/20241JM23, JM44, LY955, ZM136, ZM36, JM919, AN15890.682.07
2YN161, JM60, LY128, SN55, SN40, SN48,
SN56, SN59, LL1, ZM2118, ZM7698, ZS9170, ZM12		0.571.69
3YN301, YN31, YN33, YN745, SN38, SN57, SN69, ZM1905, ZM1860, ZM366, ZM113, WK1838, QM725, YM27, NM130.461.31
4ZM918, YM25, NM35, NM36, NZM10.290.80
5JHM2, YM15, YM20, YM24, YM30, YM340.140.39
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Wang, Y.; Bo, C.; Wang, X.; Yang, X.; Wang, H. Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars. Agronomy 2024, 14, 2438. https://doi.org/10.3390/agronomy14102438

AMA Style

Wang Y, Bo C, Wang X, Yang X, Wang H. Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars. Agronomy. 2024; 14(10):2438. https://doi.org/10.3390/agronomy14102438

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Wang, Yunhe, Cunyao Bo, Xiaohua Wang, Xincheng Yang, and Hongwei Wang. 2024. "Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars" Agronomy 14, no. 10: 2438. https://doi.org/10.3390/agronomy14102438

APA Style

Wang, Y., Bo, C., Wang, X., Yang, X., & Wang, H. (2024). Analysis of the Physiological Parameters of Cold Resistance in Core Winter and Spring Wheat Cultivars. Agronomy, 14(10), 2438. https://doi.org/10.3390/agronomy14102438

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