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Article

Effects of Temperature and Radiation on Yield of Spring Wheat at Different Latitudes

Jiangsu Key Laboratory of Crop Cultivation and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Research Institute of Rice Industrial Engineering Technology, Yangzhou University, Yangzhou 225009, China
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(5), 627; https://doi.org/10.3390/agriculture12050627
Submission received: 30 March 2022 / Revised: 20 April 2022 / Accepted: 26 April 2022 / Published: 27 April 2022

Abstract

:
It is of great importance to investigate spring wheat yield affected by the climate at different latitudes in the Rice-Wheat Rotation System. Two spring wheat varieties used as the study objects were planted at two locations of different latitudes in 2017–2018 and 2018–2019. Six sowing dates were selected for planting the wheat seeds. The quantity of basic seedlings for the first sowing date was 300 × 104 ha−1, which was increased by 10% on each date in the following sowing proceeding. Results showed that as the latitude increased, the mean daily temperature and effective accumulated temperature decreased, the mean solar radiation and accumulated solar radiation increased; as the effective accumulated temperature decreased, the yield decreased by 0.18 t ha−1 on average; and dry matter accumulation decreased by 0.6 t ha−1 on average. As the sowing date was delayed, the mean daily temperature and mean daily solar radiation increased, and the effective accumulated temperature and accumulated solar radiation decreased. Due to the decrease in the accumulated solar radiation and increase in mean daily temperature, the yield decreased by 0.27 t ha−1 on average and the dry matter decreased by 0.39 t ha−1 on average by postponing one sowing date. The effective accumulated temperature and accumulated solar radiation were significantly positively correlated with wheat yield and dry matter accumulation, and the mean daily temperature was significantly negatively correlated with wheat yield and dry matter accumulation. The temperature productivity at a high latitude was higher than lower latitude. The radiation productivity at a high latitude was lower than lower latitude. The productivity of the temperature and radiation first increased and then decreased when the sowing time was delayed.

1. Introduction

The impact of climate change on food production has been a great concern for people since the recognition of global warming [1,2]. Gaffen DJ et al. predicted that the temperature would continue to rise based on the climate model and extreme weather would occur more frequently [3]. In the past 50 years, the annual average temperature has increased at a rate of 0.29 °C per decade. It is estimated that sunshine duration has decreased by 67.1h per decade according to linear trend estimation, especially in the last 15 years [4]. The decrease in sunshine duration also means a decrease in solar radiation. In the situation where temperature rises and radiation decreases, it is of utmost importance to study the effect of temperature and radiation on the output of wheat.
The change in temperature and radiation is an influential factor in the growth and production of wheat. The study of Asseng shows that when the temperature increases by 2 °C in the growth season, the yield decreases by 50% [5,6]. The mean daily temperature suitable for wheat growth is 16–18 °C. Furthermore, 0 °C is the minimum temperature required for wheat to sprout and wheat will stop sprouting and growing if the temperature is below 0 °C [7]. The optimum temperature for wheat to tiller is 13–18 °C, and tillering becomes suppressed if that temperature is exceeded. The temperature is suited to all stages of wheat growth if planted on the suitable date. If planted too late, the accumulated temperature will be insufficient, which will affect the wheat yield and dry matter accumulation [8,9]. In the reproductive growth stage of wheat, a high temperature affects the photosynthesis of wheat, which will cause the infertility of seeds and reduce the production of carbohydrates [10,11]. Radiation also affects the substance generation of wheat [12].
Jiangsu Province is one of the largest wheat production provinces in China, and the area of wheat growth accounts for about 8.6% of the total wheat growth area in China, ranking the fifth on the list [13]. Jiangsu Province takes the Huai River as the dividing line across the winter sowing spring wheat area and semi-winter wheat area. To the south of Huai River, there is a transition zone between the subtropical and warm temperate zone, mainly for spring wheat growth. To the north of Huai River, there is a warm temperate humid monsoon climate region, mainly used for planting semi-winter wheat varieties. Because the Huai River Basin is sensitive and vulnerable to climate change, changes in latitude will change the suitable planting area of different wheat types [14]. Since the 1990s, the development and application of mechanized high-yield rice cultivation techniques and the rice cultivation replacement project through which indica rice was changed to japonica rice in Jiangsu province led to rice harvest delays [15,16,17]. This led to a late planting of wheat in the Rice-Wheat Rotation System. The delay in the sowing date also caused a change in temperature and radiation during the growth period of wheat, which affected the yield of wheat. Although there have been a lot of studies on the effects of temperature and radiation on wheat yield, there are few studies on the effects of temperature and radiation on wheat yield under the conditions of relatively high yield cultivation, super late sowing and spring wheat moving northward in this region. Therefore, the study set up different planting dates to sow the spring wheat at different latitudes, aiming to explain the following: (1) differences of temperature and radiation at different sowing dates and at different latitudes, (2) the effects of temperature and radiation on the yield of spring wheat, and (3) the feasibility of northward migration of spring wheat from the perspective of temperature and radiation.

2. Materials and Methods

2.1. Experimental Site and Experimental Design

Experiments were carried out in Jianhu County, Yancheng City, Jiangsu Province (33°47′ N, 119°77′ E) and Donghai County, Lianyungang City, Jiangsu Province (34°35′ N, 118°45′ E) from 2017 to 2018 and 2018 to 2019. Both differ in latitude. Donghai County (HL) is located at a high latitude, has a warm temperate, humid monsoon climate and clayey soil. The field soil was a clay loam with nitrogen (1.55 g kg−1), potassium (90.6 mg kg−1), phosphorus (48.6 mg kg−1), and organic matter (23.8 g kg−1) in the topsoil (0–20 cm). The yield of rice in the previous crop in the experimental site was 9.95 t·ha−1. The experimental site is mainly planted with semi-winter wheat. Jianhu County (LL) is situated in the transitional zone between subtropics and the warm temperate zone. The field soil was a clay loam with total nitrogen (1.59 g kg−1), rapidly available potassium (96.6 mg kg−1), rapidly available phosphorus (45.6 mg kg−1), and organic matter (26.8 g kg−1) found in the topsoil (0–20 cm). The yield of rice in the previous crop in the experimental site was 10.26 t ha−1. Spring varieties and semi-winter varieties can grow in the experimental site, but spring varieties are given priority. Two spring varieties were selected for the experiment, namely Yangmai 23 (YM23) and Yangmai 25 (YM25), both of which have been widely planted in this area. Six sowing dates were selected for planting the wheat seeds, which were 31 October (S1), 10 November (S2), 20 November (S3), 30 November (S4), 10 December (S5), and 20 December (S6). The quantity of basic seedlings for the first sowing date was 300 × 104 ha−1, and increased by 10% for each date in the following sowing proceeding. During this period, seedlings were manually thinned. The slow and controlled release of fertilizer for wheat, made up of (N:P:K = 26:15:8) 750 kg·ha−1 and 75 kg·ha−1 urea (229.5 N ha−1 in total), were applied to the experimental field as base fertilizer; but no fertilizer was applied in the later stages. The seeds were planted in the row spacing of 22 cm and the sowing depth of about 2 cm. The plot area was 15 m2, and each variety was repeated twice.

2.2. Experimental Data Collection

The key growth periods of wheat, such as sowing date (SO), emergence stage (EM), jointing stage (JO), heading stage (HE), and mature stage (MA), were recorded. At different growth stages, 20 representative single stems were taken from each plot, they were killed for half an hour at 105 °C and then dried to constant weight at 80 °C. The dry matter weight at different stages was calculated according to the number of tillers at different stages. At the mature stage, the distance of one meter in each plot was taken to count the number of spikes, which was repeated four times to calculate the number of panicles per hectare according to row spacing. A total of fifty panicles were selected continuously in each plot to determine the number of grains per spike which was repeated three times. A total of four squares were taken from each plot for harvesting. The actual yield was determined after the grain moisture was dried to 14%.
The data of mean daily temperature and sunshine hours of wheat growing season in the two ecological points were provided by the meteorological observation stations in Donghai County, Lianyungang City, Jiangsu Province, China and Jianhu County, Yancheng City, Jiangsu Province, China. Based on the analysis of local meteorological data in the past 10 years, the temperature and radiation in this experiment were within the range of variation. Since radiation cannot be recorded directly, the Angstrom–Prescott (AP) equation was used to calculate the total daily radiation by latitude and sunshine hours.

2.3. Calculation Methods and Statistical Analysis

In this experiment, the Angstrom-Prescott (AP) equation was used to calculate solar radiation:
Q = QA(a + bs)
where Q (MJ m−2d−1) is the total solar radiation reaching the surface; QA (MJ m−2d−1) is astronomical radiation; “s” is the percentage of sunshine (%), “a” and “b” are empirical coefficients [18].
The formula for calculating the cumulative solar radiation (CSR) and mean daily solar radiation at each growth stage is as follows:
CSR = ∑Q × days of different growth stage (d)
Rmean = ∑Q/days of different growth stage (d)
The formula for calculating the effective accumulative temperature and mean daily temperature in each growth stage is as follows:
EAT = ∑ (T1 − T0) × days of growth stage (d) [T1 > T0, when T1 < T0, (T1 − T0) is calculated as 0].
Tmean = ∑T1/days of different growth stage (d)
where T1 and T0 (the lower limit temperature of wheat growth is 0 °C) are the mean daily temperature and biological zero temperature, respectively [19].
Negative accumulated temperature refers to the absolute value of the sum of mean daily temperatures of < 0 °C in a year. The calculation formula is
Negative accumulated temperature = ∑(T1 − T0) × Growth period [T1 < T0, when T1 > T0, (T1 − T0) is calculated as 0]
Utilization efficiency of temperature = Yield/EAT × 100%
Utilization efficiency of radiation = Yield/CSR × 100%
The data were recorded and sorted out using Microsoft Excel 2016 and statistically analyzed by SPSS22.0 (ANOVA). The means were compared by the least significant difference at the probability level of 0.05 (LSD, p = 0.05). Sigma Plot 10.0 was used for graphing.

3. Results

3.1. Differences of EAT and Tmean at Different Latitudes and Sowing Dates

The EAT of the two spring wheat cultivars showed the same pattern under different situations of latitudes, sowing dates and years (Table 1). When planted on the same date, the EAT in the whole growth stage was higher at HL than LL, and the maximum effective accumulative temperature was 101 °C d. At the same latitude, the EAT in the whole growth stage gradually decreased with the postponement of the sowing date. Compared with S1, the EAT of S2–S6 decreased by 64–110 °C d, 137–199 °C d, 172–267 °C d, 178–342 °C d and 168–354 °C d, respectively. The EAT from EM to JO, JO to HE and HE to MA decreased gradually.
The difference in Tmean between the two cultivars was not that significant at different latitudes and sowing dates (Table 2). Planted on the same sowing date, the Tmean at HL was 0.4–0.87 °C lower than LL. With the delayed sowing date at the same latitude, the change in Tmean of S1 and S2 was not very obvious while the Tmean of S3–S6 increased gradually. With the postponement of the sowing date, the Tmean from SO to EM gradually decreased, and decreased first and increased from EM to JO.

3.2. Difference of CSR and Rmean at Different Latitudes and Sowing Dates

The CSR of the two spring wheat varieties presented the same pattern at different latitudes and sowing date and the CSR in the whole growth stage had the same pattern as well (Table 3). During the whole growth period, the CSR at HL was higher than LL by 269–440 MJm−2. The CSR from JO to HE and HE to MA at HL was higher than LL. The CSR at the same latitude in the whole growth stage gradually decreased as the sowing date was delayed. Compared with S1, the CSR of S2–S6 decreased by 56–116 MJm−2, 102–169 MJm−2, 156–267 MJm−2, 166–331 MJm−2 and 214–411 MJm−2, respectively.
The Rmean in the whole growth stage at HL was 1.18–2.19 MJm−2d−1 higher than LL (Table 4). The Rmean of each growth period from seedling emergence to maturity at HL was higher than LL. At the same latitude and the Rmean increased gradually with the postponement of sowing date. Compared with S1, the Rmean of S2–S6 increased by −0.08–0.27 MJm−2d−1, 0.18–0.49MJm−2d−1, 0.23–0.77MJm−2d−1, 0.49–1.32MJm−2d−1 and 0.68–1.76 MJm−2d−1, respectively.

3.3. Differences in Yield under Different Temperature and Radiation Conditions

The yield of the two spring varieties showed the same pattern under different latitudes and sowing date conditions, and the annual change pattern was also the same (Table 5 and Table 6). Planted on the same sowing date, the yield at HL was 0.06–0.41 t·ha−1 lower than LL, the number of panicles at HL was −3.48–22.63 × 104 ha−1 lower than LL, and the 1000-grain weight at HL was 0.32–1.99 g lower than LL. At the same latitude, the yield of spring wheat decreased gradually with the postponement of sowing time, and compared with S1, the yield of S2–S6 decreased by 0.22–0.31 t·ha−1, 0.49–0.62 t·ha−1, 0.78–0.99 t·ha−1, 1.07–1.23 t·ha−1 and 1.23–1.39 t·ha−1, respectively. The grain number had the trend of increasing but this was not significant when the sowing date was delayed. As the sowing date was pushed back, the grain number per spike decreased gradually, and that of S2–S6 was 0.54–5.21 lower than that of S1. As the sowing date was pushed backward, the 1000-grain weight of S2–S6 was 0.34–4.72 g lower than that of S1.

3.4. Differences in Dry Matter Formation under Different Temperature and Radiation Conditions

The dry matter accumulation of the two spring varieties showed the same change pattern at different latitudes and when sowed on different sowing dates, and the annual change was also the same pattern (Table 7). When planted on the same date, the dry matter accumulation at HL was 0.12–0.91 t·ha−1 less than LL. The difference in latitudes became increasingly smaller with the postponement of the sowing date. The dry matter accumulation during the whole growth period decreased gradually with the postponement of the sowing date. Compared with S1, the dry matter accumulation of S2–S6 decreased by 0.28–0.51·ha−1, 0.7–0.91 t·ha−1, 1.06–1.38 t·ha−1, 1.41–2.08 t·ha−1 and 1.68–2.38 t·ha−1, respectively.

3.5. Correlations between Temperature, Radiation and Yield at Different Latitudes

There was a very significant positive correlation between the effective temperature accumulation and yield in the whole growth stage and a very significant negative correlation between mean daily temperature and yield in the whole growth period, but the differences in the mean daily temperature in different years and at different latitudes were quite pronounced (Figure 1). The accumulated solar radiation and yield in the whole growth period had a significant positive correlation and a very significant negative correlation between the mean daily solar radiation and yield in the whole growth period (Figure 2). The yield/effective accumulated temperature reflects the temperature productivity (Figure 3). The temperature productivity at HL was higher than LL. The temperature productivity at HL decreased gradually, followed by S2 and at the lower latitude it gradually decreased, followed by S3. The yield/accumulated solar radiation represents the radiation productivity (Figure 4). The radiation productivity at HL was lower than LL, and the radiation productivity at both latitudes reached the maximum at S1 or S2.

3.6. Correlations between Temperature, Radiation and Dry Matter Accumulation at Different Latitudes

The correlations between dry matter accumulation and temperature were the same at different latitudes (Table 8 and Table 9). In the whole growth period, from seedling emergence to jointing stage, jointing to the heading stage and heading to the maturity stage, there was a very significant positive correlation between the effective accumulated temperature and dry matter accumulation, while the correlation between mean daily temperature and dry matter accumulation was significantly negative. There was a significant positive correlation between accumulated solar radiation and dry matter accumulation in the whole growth period and the each growth period. There was a significant negative correlation between the mean daily solar radiation and dry matter accumulation in the jointing to heading stage and the heading to maturity stage at Jianhu County.

4. Discussion

4.1. Effects of Latitude and Sowing Date on Temperature and Radiation Received by Wheat

Temperature and radiation are the main climatic factors affecting wheat yield [20,21]. Previous studies tried to improve the temperature and radiation utilization efficiency by changing the planting methods or adjusting the cultivation measures [22,23]. In this study, the effects of temperature and radiation on spring wheat were studied by choosing different sowing dates for different latitudes. For each latitude change at the ecological points, the number of growing days of wheat decreased or increased by 3 to 4 days, and the average temperature of the whole growing period increased or decreased by 0.2 °C [24]. Studies have shown that with an increase in the latitude, the mean daily temperature decreases, the effective accumulated temperature decreases, and the radiation increases in the whole growth period [25,26]. This study showed that with an increase in the planting latitude, the maturity stage of spring wheat was delayed by 4–5 d, the average temperature decreased by 0.66 °C, the effective accumulated temperature decreased by 50 °C d on average, and the accumulated solar radiation increased by 360 MJ m−2 on average. The delayed sowing date led to the delay of maturity, the shortening of the growth stage, an increase in mean daily temperature, and decrease in the effective accumulated temperature and radiation [27,28]. For each postponement of the sowing date in the study, the mean daily temperature increased by 0.18 °C, the effective accumulated temperature decreased by 53 °C d, and the accumulated solar radiation decreased by 60 MJm−2.

4.2. Effects of Temperature and Radiation on Wheat Material Production

Temperature and radiation have important effects on the formation of wheat matter. Increasing the accumulated temperature and accumulated solar radiation can improve dry matter accumulation and make them easy to transport [29,30]. When accumulated temperature reaches a certain value, the effect of increased accumulated temperature on biomass accumulation will decrease. An increase in mean daily temperature was not conducive to biomass accumulation [31]. In this study, the mean daily temperature was negatively correlated with dry matter accumulation, while accumulated temperature and accumulated solar radiation were positively correlated with dry matter accumulation. Interestingly, there was no correlation between daily radiation and dry matter accumulation in the jointing to heading stage and in the heading to maturity stage at a high latitude. This may be due to the mixed effect of temperature and radiation, which was that too high a temperature will have a negative impact on the plants, and higher radiation will not be fully utilized [32].
An increase in dry matter accumulation contributes to the relatively high yield [33]. In this study, the performance of yield was similar to the dry matter accumulation, for which a decrease was observed as accumulated temperature and accumulated solar radiation decreased. The gradual decrease in the yield was mainly due to the decrease in the grain number per spike and 1000-grain weight. At the suitable spike differentiation temperature, a high temperature accelerated spikelet differentiation and reduced spikelet floret [34,35]. A high temperature accelerates grain filling, shortens grain filling time and decreases 1000-grain weight [11,36]. In this study, when the sowing date for the jointing to heading stage was delayed, the temperature increased by 0.5 °C and the accumulated temperature decreased by 7.71 °C d. In the heading to maturity stage, the mean daily temperature increased by 0.32 °C and accumulated temperature decreased by 14.96 °C d when the sowing date was delayed. Therefore, the decrease in the effective accumulated temperature and accumulated solar radiation and an increase in mean daily temperature led to a decrease in the grain number per spike and 1000-grain weight, and finally led to the decreased yield.

4.3. Utilization Efficiency of Temperature and Radiation at Different Latitudes

The temperature and radiation productivity of wheat gradually decreased with a decrease in latitude and the postponement of the sowing date [37,38]. In this study, the temperature productivity at Donghai County was higher than Jianhu County and the radiation productivity at Donghai County was lower than Jianhu County. The influence of temperature led to the unfulfilled use of higher radiation resources. At Donghai County, temperature and radiation productivity decreased gradually after S2. At Jianhu County, the productivity decreased gradually after S3, and the radiation productivity decreased gradually after S2. Therefore, with the postponement of the sowing date, the productivity of temperature and radiation increased at first and then decreased.

4.4. Adaptability of Growing Spring Wheat Northward

In the north of Jiangsu province, the stubble problem under the Rice-Wheat Rotation system is more serious, and requires adjustments. Global warming has provided the possibility for the spring wheat to move northward by one latitude and to grow in those regions [39]. There is little difference in the length of sunshine between the two places, and the wheat can blossom and produce grain at the right time. Before moving the spring wheat growth region northward, overwintering temperature and cold spells in late spring have to be considered. One issue is the frost injury that may occur in the tillering stage and another is the late spring cold at the jointing stage and booting stage. Generally speaking, the spring varieties can withstand a low temperature of −10 °C [40]. In this study, neither of these two experimental sites had a temperature as low as −10 °C, and all wheat crops were unaffected by cold spells in late spring. Negative accumulated temperature is an index with which to investigate the frost injury that may be inflicted upon wheat growth in winter and to assess whether wheat can be introduced or not [41]. In this study, the negative accumulated temperature in the past two years trended towards a higher position between the middle and high levels, and the lowest negative accumulated temperature at HL was as low as −74.9 °C. Only a small portion of leaves of YM23 in S1 yellowed, and other sowing stages were not affected by low temperature. Wheat is subjected to high temperature stress when the temperature exceeds 25 °C in the filling stage [11,42]. During the experiment in this study, the temperature at HL was over 25 °C for about 7–8 days, and the temperature difference between the latitudes was small. The influence of hot and dry air on wheat growth was less pronounced. Under the unified management of diseases and insect pests in the field, no serious diseases and insect pests appeared in wheat, and the incidence of powdery mildew in wheat planted in the north was less than that in wheat planted in the LL. If the spring varieties growth region moves northward, their yield would decrease, but the wheat yield from all sowing stages was higher than the average yield of wheat in the northern Jiangsu region (6 t ha1). Compared with semi-winter varieties, spring varieties have a shorter growth time and are not as demanding in terms of cold temperatures during vernalization as the semi-winter varieties [43]. In this experiment, moving the spring wheat variety northward by one latitude could alleviate the stubble problem and recover some yield loss. However, there is still some risk of spring wheat moving northward, and it is necessary to screen spring wheat varieties with early maturity and strong resistance due to overwintering and cold spells in later spring.

5. Conclusions

In this study, the effects of temperature and radiation on the yield of spring wheat were investigated by setting different sowing dates for different latitudes. If spring wheat moved northward, it would result in a decrease in the effective accumulated temperature and mean daily temperature, an increase in accumulated solar radiation, and decrease in yield and dry matter accumulation. The postponement of sowing date leads to the postponement of the growth stage, a reduction in growth days, a decrease in the effective accumulated temperature and accumulated solar radiation, and an increase in daily temperature. The mean daily temperature increased and the effective accumulated temperature and accumulated solar radiation decreased, which resulted in a reduction in the grain number per spike and 1000-grain weight. The effective accumulated temperature and accumulated solar radiation had significant positive correlations with yield, while the mean daily temperature had significant negative correlations with yield. There was a significant positive correlation between the effective accumulated temperature and accumulated solar radiation and dry matter accumulation, while there was a significant negative correlation between daily temperature and dry matter accumulation.

Author Contributions

Conceptualization, H.W.; methodology, N.Z.; validation, H.Z. and H.G.; formal analysis, Z.Z.; investigation, Z.Z. and B.L.; resources, Z.Z. and J.T.; writing—original draft preparation, Z.Z.; writing—review and editing, Z.Z. and Z.X.; supervision, H.Z. and H.W.; project administration, H.Z. All authors have read and agreed to the published version of the manuscript.

Funding

Hongcheng Zhang, Jiangsu Demonstration Project of Modern Agricultural Machinery Equipment and Technology, Yangzhou University: (NJ2020-58, NJ2019-33, NJ2021-63).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mahmood, T.; Khalid, S.; Abdullah, M.; Ahmed, Z.; Shah, M.; Ghafoor, A.; Du, X. Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance. Cells 2019, 9, 105. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Cooney, C.M. Health scenarios for a warming world. Environ. Health Perspect. 2010, 118, a382. [Google Scholar] [CrossRef] [PubMed]
  3. Gaffen, D.J.; Ross, R.J. Increased summertime heat stress in the US. Nature 1998, 396, 529–530. [Google Scholar] [CrossRef]
  4. Zhu, B.; Sun, J.L.; Hu, R.C.; Wei, X.Y.; Zhai, L. Analysis on the change characteristics of agroclimatic resources in Jiangsu Province in recent 50 years. In Proceedings of the Annual Meeting of Chinese Meteorological Society, Shenyang, China, 1 September 2012; pp. 799–806. [Google Scholar]
  5. Asseng, S.; Foster, I.; Turner, N.C. The impact of temperature variability on wheat yields. Glob. Chang. Biol. 2011, 17, 997–1012. [Google Scholar] [CrossRef]
  6. Amir, J.; Sinclair, T.R. A model of the temperature and solar-radiation effects on spring wheat growth and yield. Field Crops Res. 1991, 28, 47–58. [Google Scholar] [CrossRef]
  7. Bao, Y.X. Meteorology; Southern Version China Agriculture Press: Beijing, China, 2002. [Google Scholar]
  8. Liu, L.; Ji, H.; An, J.; Shi, K.; Yan, Z. Response of biomass accumulation in wheat to low-temperature stress at jointing and booting stages. Environ. Exp. Bot. 2018, 157, 46–57. [Google Scholar] [CrossRef]
  9. LI, Q.Y.; Nian, L.; Liu, W.D.; Li, L.; Zhou, S.M.; Jun, Y. Effects of accumulated temperature before winter on Growth and Development of Wheat in Henan Province. Chin. J. Agrometeorol. 2010, 31, 563–569. (In Chinese) [Google Scholar]
  10. Shah, N.; Paulsen, G. Interaction of drought and high temperature on photosynthesis and grain-filling of wheat. Plant Soil 2003, 257, 219–226. [Google Scholar] [CrossRef]
  11. Jing, J.; Guo, S.; Li, Y.; Li, W. The alleviating effect of exogenous polyamines on heat stress susceptibility of different heat resistant wheat (Triticum aestivum L.) varieties. Sci. Rep. 2020, 10, 7467. [Google Scholar] [CrossRef] [PubMed]
  12. Driever, S.M.; Lawson, T.; Andralojc, P.J.; Raines, C.A.; Parry, M.A. Natural variation in photosynthetic capacity, growth, and yield in 64 field-grown wheat genotypes. J. Exp. Bot. 2014, 65, 4959–4973. [Google Scholar] [CrossRef] [Green Version]
  13. Beijing Orient Aige Agriculture Consulting Co. LTD. Table 1.3.4, Area of Wheat by Province in China, 2000–2009. In China Agricultural Commodities Yearbook; Beijing, China, April 2011; Volume 17. [Google Scholar]
  14. Zhang, Y.Q.; Liu, C.M.; You, Q.L.; Chen, C.C.; Xie, W.X.; Ye, Z.W.; Li, X.C.; He, Q.N. Decrease in light precipitation events in Huai River Eco-economic Corridor, a climate transitional zone in eastern China. Atmos. Res. 2019, 226, 240–254. [Google Scholar] [CrossRef]
  15. Cheng, S.L.; Xiao, H.R.; Zhu, X.M.; Ma, Z.B.; Shi, L.; Zhou, M.; Zhu, D.W. The mechanical transplanting technology of raising rice seedlings in field and the study, innovation and development of raising rice seedlings equipment of mechanization in southward of china. Chin. Agric. Mech. 2005, 02, 42–45. [Google Scholar]
  16. Gong, J.L.; Xing, Z.P.; Hu, Y.J.; Zhang, H.C.; Dai, Q.G.; Huo, Z.Y.; Xu, K.; Wei, H.Y.; Gao, H. The relative advantages of “changing indica to japonica” and the countermeasures of production development. Chin. Rice 2013, 19, 1–6. (In Chinese) [Google Scholar]
  17. Zhang, H.C.; Zhang, J.; Gong, J.L.; Chang, Y.; Li, M.; Gao, H.; Dai, Q.G.; Huo, Z.Y.; Xu, K.; Wei, H.Y. The productive advantages and formation mechanisms of “indica rice to japonica rice”. Sci. Agric. Sin. 2013, 46, 686–704. (In Chinese) [Google Scholar]
  18. He, Q.H.; Xie, Y. Study on Climatological calculation method of Total Solar radiation in China. J. Nat. Resour. 2010, 25, 308–319. (In Chinese) [Google Scholar]
  19. Chen, T.Y.; Yuan, J.Q.; Liu, Y.Y.; Xu, K.; Guo, B.W.; Dai, Q.G.; Huo, Z.Y.; Zhang, H.C.; Li, G.H. Effects of different sowing dates on crop yield, quality, and annual light-temperature resources utilization for rice–wheat double cropping system in the lower reaches of the Yangtze-Huaihe Rivers valley. Acta Agron. Sin. 2020, 46, 1566–1578. [Google Scholar]
  20. Lewis, S.; Faricelli, M.E.; Appendino, M.L.; Valárik, M.; Dubcovsky, J. The chromosome region including the earliness per se locus Eps-Am1 affects the duration of early developmental phases and spikelet number in diploid wheat. J. Exp. Bot. 2008, 59, 3595–3607. [Google Scholar] [CrossRef]
  21. Mondal, S.; Rutkoski, J.E.; Velu, G.; Singh, P.K.; Crespo-Herrera, L.A.; Guzmán, C.; Bhavani, S.; Lan, C.; He, X.; Singh, R.P. Harnessing Diversity in Wheat to Enhance Grain Yield, Climate Resilience, Disease and Insect Pest Resistance and Nutrition Through Conventional and Modern Breeding Approaches. Front. Plant Sci. 2016, 7, 991. [Google Scholar] [CrossRef] [Green Version]
  22. Sabine, D.M.; Jeuffroy, M.H. Incorporating radiation and nitrogen nutrition into a model of kernel number in wheat. Crop Sci. 2001, 41, 415–423. [Google Scholar] [CrossRef]
  23. Manderscheid, R.; Burkart, S.; Bramm, A.; Weigel, H.J. Effect of CO2 enrichment on growth and daily radiation use efficiency of wheat in relation to temperature and growth stage. Eur. J. Agron. 2003, 19, 411–425. [Google Scholar] [CrossRef]
  24. Williams, G.D.V. Wheat phenology in relation to latitude, longitude and elevation on the Canadian great plains. Can. J. Plant Sci. 1971, 1, 1–12. [Google Scholar] [CrossRef]
  25. Nie, Y.W. Effects of Sowing Date and Latitude on Growth, Yield and Quality of Different Temperature Sensitive Wheat Varieties; Henan Agricultural University: Zhengzhou, China, 2018. [Google Scholar]
  26. Yang, H.B.; Xu, C.Z.; Li, C.G.; Li, F.Y. Growth and Required Accumulated Temperature of Winter Wheat under Different Sowing Time. China Agric. Meteorol. 2009, 30, 201–203. [Google Scholar]
  27. Wang, Y.; Zhang, Z.; Liang, Y.; Han, Y.; Han, Y.; Tan, J. High Potassium Application Rate Increased Grain Yield of Shading-Stressed Winter Wheat by Improving Photosynthesis and Photosynthate Translocation. Front. Plant Sci. 2020, 11, 134–144. [Google Scholar] [CrossRef] [PubMed]
  28. Lv, L.H.; Liang, S.B.; Zhang, J.T.; Yao, Y.R.; Dong, Z.Q.; Zhang, L.H.; Jia, X.L. Response of yield and light energy utilization of different wheat varieties to accumulated temperature before winter. J. Wheat Crops 2017, 8, 1047–1055. [Google Scholar]
  29. Porter, J.R. Rising temperatures are likely to reduce crop yields. Nature 2005, 436, 174. [Google Scholar] [CrossRef] [Green Version]
  30. Lawlor, D.; Day, W.; Johnston, A.; Legg, B.; Parkinson, K. Growth of spring barley under drought: Crop development, photosynthesis, dry-matter accumulation and nutrient content. J. Agric. Sci. 1981, 96, 167–186. [Google Scholar] [CrossRef]
  31. Lu, H.; Hu, Y.; Wang, C.; Liu, W.; Ma, G.; Han, Q.; Ma, D. Effects of High Temperature and Drought Stress on the Expression of Gene Encoding Enzymes and the Activity of Key Enzymes Involved in Starch Biosynthesis in Wheat Grains. Front. Plant Sci. 2019, 10, 1414. [Google Scholar] [CrossRef] [PubMed]
  32. Deng, N.Y.; Ling, X.X.; Sun, Y.; Zhang, C.D.; Fahad, S.; Peng, S.B.; Cui, K.H.; Nie, L.X.; Huang, J. Influence of temperature and solar radiation on grain yield and quality in irrigated rice system. Eur. J. Agron. 2015, 64, 37–46. [Google Scholar] [CrossRef]
  33. Liu, Z.; Gao, J.; Gao, F.; Liu, P.; Zhao, B.; Zhang, J. Photosynthetic Characteristics and Chloroplast Ultrastructure of Summer Maize Response to Different Nitrogen Supplies. Front. Plant Sci. 2018, 9, 576. [Google Scholar] [CrossRef]
  34. Yang, X.; Wang, B.; Chen, L.; Li, P.; Cao, C. The different influences of drought stress at the flowering stage on rice physiological traits, grain yield, and quality. Sci. Rep. 2019, 9, 3742. [Google Scholar] [CrossRef] [Green Version]
  35. Yang, W. Monograph on Crop Cultivation; China Agriculture Press: Beijing, China, 2011. [Google Scholar]
  36. Hakala, K.; Jauhiainen, L.; Himanen, S.J.; Rötter, R.; Salo, T.; Kahiluoto, H. Sensitivity of barley varieties to weather in Finland. J. Agric. Sci. 2012, 150, 145–160. [Google Scholar] [CrossRef] [Green Version]
  37. Li, L. The Analysis of Changes in Climatic Resources, Potential and Utilization of Wheat in Henan Province in Different Latitudes; Henan Agricultural University: Zhengzhou, China, 2010; p. 38. [Google Scholar]
  38. Xu, J.; Zhou, S.; Liu, L.Y.; He, X.N.; Nan, Z.W.; Meng, W.W.; Wang, N.; Han, W.; Wang, X.Q.; Liu, K.C. Effects of Harvest and Sowing Dates on Annual Yield and Resource Utilization Efficiency of Wheat and Maize. Shandong Agric. Sci. 2020, 10, 100–107. [Google Scholar]
  39. Dakhil, M.A.; Halmy, M.; Hassan, W.A.; El-Keblawy, A.; Pan, K.; Abdelaal, M. Endemic Juniperus Montane Species Facing Extinction Risk under Climate Change in Southwest China: Integrative Approach for Conservation Assessment and Prioritization. Biology 2021, 10, 63. [Google Scholar] [CrossRef] [PubMed]
  40. Bigler, C.; Bugmann, H. Climate-induced shifts in leaf unfolding and frost risk of European trees and shrubs. Sci. Rep. 2018, 8, 9865. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Deng, Z.Y.; Zhang, Q.; Pu, J.Y.; Liu, D.X.; Guo, H.; Wang, Q.F.; Zhao, H.; Wang, H.L. Impact of climate warming on crop planting and production in northwest china. Acta Ecol. Sin. 2008, 28, 3760–3768. [Google Scholar] [CrossRef]
  42. Li, P.F.; Ma, B.L.; Xiong, Y.C. Modern hexaploid wheat differs from diploid and tetraploid ancestors in the importance of stress tolerance versus stress avoidance. Crop Pasture Sci. 2018, 69, 265–277. [Google Scholar] [CrossRef]
  43. Winfield, M.; Lu, C.; Wilson, I.; Coghill, J.; Edwards, K. Plant responses to cold: Transcriptome analysis of wheat. Plant Bio-Technol. J. 2010, 8, 749–771. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Correlation between temperature and yield during the whole growth period. HL1: 2017–2018 Donghai County test site, HL2: 2018–2019 Donghai County test site, LL1: 2017–2018 Jianhu County test site, LL2: 2018–2019 Jianhu County test site.
Figure 1. Correlation between temperature and yield during the whole growth period. HL1: 2017–2018 Donghai County test site, HL2: 2018–2019 Donghai County test site, LL1: 2017–2018 Jianhu County test site, LL2: 2018–2019 Jianhu County test site.
Agriculture 12 00627 g001
Figure 2. Correlation between radiation and yield during the whole growth period. HL1: 2017–2018 Donghai County test site, HL2: 2018–2019 Donghai County test site, LL1: 2017–2018 Jianhu County test site, LL2: 2018–2019 Jianhu County test site.
Figure 2. Correlation between radiation and yield during the whole growth period. HL1: 2017–2018 Donghai County test site, HL2: 2018–2019 Donghai County test site, LL1: 2017–2018 Jianhu County test site, LL2: 2018–2019 Jianhu County test site.
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Figure 3. The ratio of yield to effective accumulative temperature at two latitudes in 2017–2018 and 2018–2019. S1, S2, S3, S4, S5 and S6 represent the sowing dates of 31October, 10 November, 20 November, 30 November, 10 December and 20 December, respectively. HL: Donghai County test site, LL: Jianhu County test site. The vertical strip represents the standard error of the average value of the two varieties (nasty 2).
Figure 3. The ratio of yield to effective accumulative temperature at two latitudes in 2017–2018 and 2018–2019. S1, S2, S3, S4, S5 and S6 represent the sowing dates of 31October, 10 November, 20 November, 30 November, 10 December and 20 December, respectively. HL: Donghai County test site, LL: Jianhu County test site. The vertical strip represents the standard error of the average value of the two varieties (nasty 2).
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Figure 4. The ratio of yield to cumulative solar radiation at two latitudes in 2017–2018 and 2018–2019. S1, S2, S3, S4, S5 and S6 represent the sowing dates of31 October, 10 November, 20 November, 30 November, 10 December and 20 December, respectively. HL: Donghai County test site, LL: Jianhu County test site. The vertical strip represents the standard error of the average value of the two varieties (nasty 2).
Figure 4. The ratio of yield to cumulative solar radiation at two latitudes in 2017–2018 and 2018–2019. S1, S2, S3, S4, S5 and S6 represent the sowing dates of31 October, 10 November, 20 November, 30 November, 10 December and 20 December, respectively. HL: Donghai County test site, LL: Jianhu County test site. The vertical strip represents the standard error of the average value of the two varieties (nasty 2).
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Table 1. Difference in the effective accumulative temperature at different latitudes and sowing dates (°C d).
Table 1. Difference in the effective accumulative temperature at different latitudes and sowing dates (°C d).
VarietiesLatitudeTreatment2017–20182018–2019
SO-EMEM-JOJO-HEHE-MAWhole Growth PeriodSO-EMEM-JOJO-HEHE-MAWhole Growth Period
YM23HLS114149548083019701225644988111995
S214747641580418681335054588351931
S316346138479518031464694537901858
S417543837578317431514614097741796
S519742836977717431784033997781758
S622441336677917321993894107681766
LLS111961044987020481146364618882098
S212454141186219381195784608321989
S313348738284618491275444128221905
S414243539981317891425093817991831
S515444336580717701524533847891779
S617044136179417661674303847901771
YM25HLS114151447783919701225944918352041
S214750240981018681335474448291953
S316347139780118321465064377941882
S417545937079417981514933997781821
S519744037777917921784254107681781
S622442437478018021994344027551790
LLS111964043387920711146734529102148
S212456141086719621196044528672042
S313352639983718951275674228431960
S414248036982318131425303858301887
S515449433281317941524803718031807
S617045736479917901674593707981794
Table 2. Difference in mean daily temperature at different latitudes and sowing dates (°C).
Table 2. Difference in mean daily temperature at different latitudes and sowing dates (°C).
VarietiesLatitudeTreatment2017–20182018–2019
SO-EMEM-JOJO-HEHE-MAWhole Growth PeriodSO-EMEM-JOJO-HEHE-MAWhole Growth Period
YM23HLS114.103.2114.5420.248.8112.163.9013.0920.808.95
S28.183.3214.8120.618.709.483.6713.4821.418.99
S32.395.2616.0020.938.739.713.5114.1621.959.03
S41.1310.4317.0521.168.821.557.1814.6222.109.13
S51.4511.2516.7921.579.271.5011.1915.3322.229.42
S61.8712.5217.4021.639.711.9111.8015.7522.599.99
LLS114.844.5313.2119.779.4916.265.1112.4518.899.81
S211.274.1314.6820.059.3711.934.8313.5119.359.71
S36.344.2115.2820.159.3511.564.7014.2119.569.73
S44.264.6115.3420.339.486.385.0814.6519.989.80
S51.719.2415.2120.709.862.877.0414.7820.7710.01
S62.0110.7515.0220.9010.372.758.7714.7821.3510.51
YM25HLS114.103.3014.9020.458.7712.164.0413.2621.419.08
S28.183.4715.1420.778.669.483.9213.4521.839.05
S32.395.3116.5521.088.839.713.7414.5522.079.11
S41.1310.6816.8021.479.071.557.3315.3322.229.21
S51.4511.2717.1521.639.491.5011.1915.7522.599.50
S61.8712.4717.8321.6610.061.9112.0516.0822.8810.07
LLS114.844.6913.1219.989.5616.265.2412.9119.369.96
S211.274.2315.2020.159.4411.934.9713.6819.709.87
S36.344.4915.3420.429.4911.564.8214.5420.089.91
S44.264.9615.3520.589.566.385.2014.7920.749.99
S51.719.6815.1120.859.942.877.2414.8421.1410.11
S62.0110.6315.8321.0210.462.759.0114.8121.5610.59
Table 3. Differences in cumulative solar radiation at different latitudes and sowing dates (MJ m2).
Table 3. Differences in cumulative solar radiation at different latitudes and sowing dates (MJ m2).
VarietiesLatitudeTreatment2017–20182018–2019
SO-EMEM-JOJO-HEHE-MAWhole Growth PeriodSO-EMEM-JOJO-HEHE-MAWhole Growth Period
YM23HLS1148117656868125789211225957202528
S21761157483622246212211055287162472
S348786843961424099211635036682426
S474061137561223104708374196432369
S569760338458622476796144046432341
S672350640256821676765754276212300
LLS111510424596262243678105556702101
S27110074585962131828345255912032
S31909104165832100848544396101988
S427279140057020331198443536231939
S549854037555519673516473306071935
S647950937253718983566033086211888
YM25HLS1148121355366325789211535907162551
S21761189474623246212211594987212501
S348788943862224369212214726572442
S474062937861423614708704046432387
S569760740656822796796424276212369
S672351939457522106766274056212329
LLS111510524746202262678575356862146
S27110364446072158828644996422087
S31909524005962138848944096552042
S427283737157820591198873296541990
S549857834356119803516803036261959
S647951838952419103566322926131893
Table 4. Differences in mean daily cumulative solar radiation at different latitudes and sowing dates (MJ m2 d−1).
Table 4. Differences in mean daily cumulative solar radiation at different latitudes and sowing dates (MJ m2 d−1).
VarietiesLatitudeTreatment2017-20182018-2019
SO-EMEM-JOJO-HEHE-MAWhole Growth PeriodSO-EMEM-JOJO-HEHE-MAWhole Growth Period
YM23HLS114.818.9717.2116.6111.999.168.7015.6518.4611.70
S29.799.5617.2715.9511.958.749.1315.5418.3711.89
S38.4011.1318.2916.1712.176.1310.0315.7118.5512.19
S48.4014.5617.0316.5412.227.3413.2814.9718.3812.47
S58.3015.8717.4616.2812.488.0817.0615.5418.3912.93
S68.9315.3319.1315.7812.678.5617.4416.4318.2713.37
LLS114.418.3413.5114.2210.639.566.6915.0014.269.91
S26.428.3916.3613.8610.558.207.1915.4513.7510.01
S39.078.6716.6413.8910.887.677.6315.1514.5310.25
S48.259.3115.3714.2411.055.408.7013.5915.5810.48
S57.7811.2515.6114.2211.247.3010.1212.7015.9710.99
S67.6112.4215.5214.1211.436.4712.3111.8316.7911.30
YM25HLS114.819.1217.2916.1811.939.168.7315.9418.3711.70
S29.799.6717.5415.9811.898.749.3515.0918.9811.97
S38.4011.2618.2516.3612.246.1310.2615.7318.2412.21
S48.4014.6417.1916.5812.427.3413.1715.5418.3912.50
S58.3015.5818.4615.7812.598.0816.8916.4318.2713.02
S68.9315.2618.7515.9712.858.5617.4116.2118.8113.46
LLS114.418.2814.3614.1010.679.566.8615.2814.6010.03
S26.428.4916.4414.1110.638.207.3215.1314.5910.18
S39.078.9015.3714.5310.967.677.8414.1115.5910.42
S48.259.5115.4714.4611.135.408.9612.6716.3610.64
S57.7811.3315.6014.4011.257.3010.3012.1116.4711.07
S67.6112.0516.8913.8011.446.4712.3911.6716.5811.27
Table 5. Effects of different temperature and radiation on wheat yield.
Table 5. Effects of different temperature and radiation on wheat yield.
VarietyLatitudeTreatment2017–20182018–2019
Panicles
(× 104 ha−1)
Grain per Panicle1000-Grain Weight
(g)
Yield
(t·ha−1)
Panicles
(× 104 ha−1)
Grain per Panicle1000-Grain Weight
(g)
Yield (t·ha−1)
YM23HLS1482.98 cd37.62 a41.62 ab7.40 b480.38 c37.72 a42.17 bc7.51 b
S2477.35 cd37.27 a41.28 b7.17 c477.31 c36.89 bc41.69 bcd7.29 c
S3484.26 bcd35.95 b40.30 c6.85 e484.88 bc35.34 d40.94 de6.89 d
S4485.24 bcd35.17 c39.17 d6.57 fg490.88 abc34.88 de39.53 gh6.62 e
S5493.83 abc34.50 d38.42 e6.24 h486.38 bc33.96 fg39.28 gh6.38 fg
S6497.07 ab33.70 e37.75 f6.17 h505.75 ab33.60 g38.44 i6.19 h
LLS1485.50 bcd37.67 a42.10 a7.56 a486.63 bc37.30 ab43.70 a7.69 a
S2490.52 abc36.33 b41.64 ab7.32 b491.58 abc36.55 c42.46 b7.47 b
S3490.23 abc35.75 bc41.24 b7.00 d498.70 abc35.10 de41.51 cd7.19 c
S4495.05 abc34.40 d40.56 c6.68 f505.10 ab34.60 ef40.42 ef6.91 d
S5500.20 a33.40 ef39.43 d6.47 g509.00 a33.35 g39.99 fg6.49 ef
S6502.90 a32.87 f38.97 de6.23 h509.83 a32.35 h38.98 hi6.32 gh
YM25HLS1480.91 c37.72 a41.90 a7.46 b488.51 cd37.55 a41.99 b7.57 ab
S2486.89 bc36.62 b41.06 b7.17 d493.24 bc36.44 b40.85 cd7.32 cd
S3489.13 abc35.70 c40.63 bc6.79 e497.93 bc35.45 c40.49 cde6.81 e
S4500.50 ab34.47 d39.33 de6.59 fg493.95 bc34.21 d40.03 def6.58 f
S5507.10 a33.45 e38.54 fg6.32 h512.43 ab32.79 e39.19 f6.33 g
S6508.02 a32.97 e37.73 g6.16 i504.24 abc32.44 e39.16 f6.20 g
LLS1486.65 bc37.77 a42.26 a7.61 a486.30 d37.35 a43.76 a7.72 a
S2487.15 bc36.60 b41.89 a7.34 c493.55 bc36.04 bc42.83 b7.40 bc
S3496.05 abc35.74 c40.94 b7.07 d494.45 bc35.18 c42.03 b7.22 d
S4502.88 ab34.47 d40.05 cd6.68 ef507.80 abc34.03 d40.96 c6.90 e
S5507.30 a33.25 e39.42 de6.54 g514.63 a32.74 e40.76 cde6.55 f
S6506.73 a33.03 e39.16 ef6.28 h510.00 ab32.14 e39.94 ef6.33 g
Data followed by different lower-case letters are significantly different at the 5% probability level as determined by the LSD test.
Table 6. Correlation between experimental point, sowing date and yield components (F value).
Table 6. Correlation between experimental point, sowing date and yield components (F value).
2017–20182018–2019
Panicles Grain per PanicleGrain WeightYieldPaniclesGrain per PanicleGrain WeightYield
latitude (L)5.35 *12.91 **87.59 **102.88 **6.83 *14.34 **89.29 **101.24 **
Variety (V)8.79 **6.91 *0.183.924.0619.44 **3.970
Sowing (S)10.76 **259.65 **171.57 **716.10 **6.19 **234.29 **92.71 **441.29 **
L × V1.3911.70 **0.651.042.812.126.15 *0.35
L × S0.131.412.442.160.420.671.413.75 *
V × S0.771.10.350.560.652.421.860.27
P × V × S0.340.821.050.590.40.650.680.65
Values are means ± SE. * and ** are significant at p = 0.05 and p = 0.01 levels, respectively.
Table 7. Effects of different temperature and radiation on dry matter accumulation.
Table 7. Effects of different temperature and radiation on dry matter accumulation.
VarietiesLatitudeSowing2017–20182017–2018
JOHEMAJOHEMA
YM23HLS14.14 a9.64 a15.05 a4.24 a9.94 a15.24 a
S24.05 ab9.49 b14.76 b4.11 b9.73 b14.93 a
S33.77 c9.10 c14.13 c3.98 c9.51 c14.55 b
S43.64 d8.86 d13.73 d3.84 d9.25 d14.10 c
S53.50 e8.66 e13.30 e3.74 e9.10 e13.84 cd
S63.47 e8.61 e13.28 e3.70 e8.95 e13.56 d
LLS14.43 a10.33 a15.68 a4.64 a10.62 a16.07 a
S24.24 b10.06 b15.18 b4.47 b10.40 ab15.73 b
S34.14 bc9.82 c14.77 c4.22 c10.09 c15.23 c
S43.92 d9.61 d14.38 d3.99 d9.80 d14.74 d
S53.86 e9.40 e14.06 e3.65 e9.32 e13.99 e
S63.78 e9.23 f13.75 f3.58 e9.13 e13.69 e
YM25HLS14.21 a9.85 a15.27 a4.33 a10.16 a15.52 a
S24.07 b9.71 b14.98 b4.22 a10.01 b15.22 b
S33.83 c9.45 c14.51 c4.07 b9.70 c14.71 c
S43.63 d9.26 d14.20 d3.88 c9.42 d14.23 d
S53.50 ed9.04 e13.74 e3.72 d9.16 e13.82 e
S63.33 e8.86 f13.42 f3.62 d9.02 f13.60 e
LLS14.49 a10.60 a15.94 a4.79 a10.81 a16.32 a
S24.34 b10.27 b15.43 b4.59 b10.56 b15.88 b
S34.20 c10.06 c15.10 bc4.53 b10.40 b15.62 b
S44.04 d9.81 d14.55 c4.25 c10.06 c15.08 c
S53.91 e9.59 e14.30 cd4.03 d9.73 d14.54 d
S63.82 e9.38 f13.94 d3.87 e9.43 e14.09 e
Data followed by different lower-case letters are significantly different at the 5% probability level as determined by the LSD test.
Table 8. Correlation between temperature and radiation on dry matter of spring wheat in different periods at Donghai County.
Table 8. Correlation between temperature and radiation on dry matter of spring wheat in different periods at Donghai County.
EM-JOJO-HEHE-MAWhole Growth Period
EAT0.9501 **0.6463 **0.9745 **0.9451 **
Tmean−0.9444 **−0.6159 *−0.9579 **−0.7970 **
CSR0.9666 **0.6324 *0.9823 **0.9862 **
Rmean−0.9630 **−0.31310.3365−0.9445 **
Values are means ± SE. * and ** are significant at p = 0.05 and p = 0.01 levels, respectively.
Table 9. Correlation between temperature and radiation on dry matter of spring wheat in different periods at Jianhu County.
Table 9. Correlation between temperature and radiation on dry matter of spring wheat in different periods at Jianhu County.
EM-JOJO-HEHE-MAWhole Growth Period
EAT0.9762 **0.8576 **0.9712 **0.9063 **
Tmean−0.7918 **−0.7183 **−0.9288 **−0.7363 **
CSR0.9156 **0.8644 **0.8702 **0.9899 **
Rmean−0.8977 **0.5891 *−0.7970 **−0.9390 **
Values are means ± SE. * and ** are significant at p = 0.05 and p = 0.01 levels, respectively.
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Zhang, Z.; Zhou, N.; Xing, Z.; Liu, B.; Tian, J.; Wei, H.; Gao, H.; Zhang, H. Effects of Temperature and Radiation on Yield of Spring Wheat at Different Latitudes. Agriculture 2022, 12, 627. https://doi.org/10.3390/agriculture12050627

AMA Style

Zhang Z, Zhou N, Xing Z, Liu B, Tian J, Wei H, Gao H, Zhang H. Effects of Temperature and Radiation on Yield of Spring Wheat at Different Latitudes. Agriculture. 2022; 12(5):627. https://doi.org/10.3390/agriculture12050627

Chicago/Turabian Style

Zhang, Zhenzhen, Nianbing Zhou, Zhipeng Xing, Bingliang Liu, Jinyu Tian, Haiyan Wei, Hui Gao, and Hongcheng Zhang. 2022. "Effects of Temperature and Radiation on Yield of Spring Wheat at Different Latitudes" Agriculture 12, no. 5: 627. https://doi.org/10.3390/agriculture12050627

APA Style

Zhang, Z., Zhou, N., Xing, Z., Liu, B., Tian, J., Wei, H., Gao, H., & Zhang, H. (2022). Effects of Temperature and Radiation on Yield of Spring Wheat at Different Latitudes. Agriculture, 12(5), 627. https://doi.org/10.3390/agriculture12050627

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