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AbstractThe spikegrain structure and yield data of winter wheat observed at 10 winter wheat observation stations in Jiangsu agrometeorological observation stations in the China Meteorological Observation Network were used to design the assessment model and evaluation criteria of the effects of climate change on spikegrain structure and yield of winter wheat. The linear regression method was used to determine the parameters of the assessment model, and the climate fact extrapolation method was used to determine future climate change scenarios. The effects of climate change on spikegrain structure and yield of winter wheat in Jiangsu Province were calculated and analyzed finally. The results showed that with the climate change, the meteorological conditions during the growth and development of winter wheat changed, which caused the number of effective spikes to decrease, and the number of grains per spike and thousandgrain weight to increase, and this new type of spikegrain structure combination was beneficial to the increase of the unit yield of winter wheat. The variations of meteorological elements caused by climate change during winter wheat growth and development had different effects on spikegrain structure at different growth stages. The spikegrain structure had an"increasingdecreasing" periodic variation with the growth period overall, with a period of one to three stages. The relationship between winter wheat growth and development and meteorological conditions can be adjusted in real time through stressresistant cultivation techniques to achieve the highyield and highquality cultivation target of winter wheat production.
Key wordsYield per unit area; Spikegrain structure; Climate assessment
Received: October 13, 2018Accepted: December 22, 2018
Supported by 2016 Key Business Project of Jiangsu Meteorological Bureau (20161122).
Shun SHANG (1989-), male, P. R. China, research assistant, master, devoted to research about marine weather service.
*Corresponding author. Email: shangshun@qq.com.
Chao et al.［1］ believe that the fifth assessment report of IPCC is more objective and comprehensive than the previous reports, and global warming has become common consensus. Piao et al.［2］, Lobell et al.［3］ and Asseng et al.［4］believe that global warming seriously affects the sustainable development of world agriculture, and Guo et al.［5］believe that paying attention to the impact of climate change on crop production is an important task for Chinas safe agricultural production. Wheat is one of the top three food crops in the world, and according to this, the safety of winter wheat production is one of the key contents of food security and an important area for agriculture to cope with climate change. Chinas wheat production ranks first in the world all year round, accounting for about 20% of its total production. Jiangsu Province is the fifth largest wheat producer in China, with a production accounting for about 7% of national production. Therefore, fluctuations in the yield and quality of winter wheat in Jiangsu Province have an important impact on food security in China and the world. Many scholars at home and abroad have studied the impact of climate change on winter wheat production from different perspectives. For instance, Prasad et al.［6］, Wang et al.［7］, Tian et al.［8］, Quan et al.［9］and many other scholars believe that climate warming leads to obviously high temperature in winter, resulting in early jointing of winter wheat and increase of freezing damage. Many research teams concluded that climate change increased the vulnerability of winter wheat production in 2013 (Chang and Lan［10］, geng et al.［11］, Wang et al.［12］, Li et al.［13］, Jing et al.［14］, Wang et al.［15］, Li et al.［16］, Gao et al.［17］) and 2014 (Li et al.［18］, Wilcox and Makowski［19］, Johnen et al.［20］, Talukder et al.［21］, Mirjam et al.［22］and Nourdeldin et al.［23］). Shang et al.［24］systematically summarized and reviewed research papers at home and abroad on the relationship between winter wheat production and climate change, and deem that at present, at home and abroad, the main technical method for assessing the impact of climate change on wheat production is to generate future climate scenarios by extrapolating the trend of climate change facts or using climate models, use the mechanism or statistical model of the relationship between winter wheat growth and meteorological conditions to simulate winter wheat production condition under future climate scenarios, and make an assessment report about the effect of climate change on winter wheat yield finally. The authoritativeness of quantitative assessment reports on the effect of climate change on winter wheat yield has not been confirmed due to the differences in experimental design, selected materials and analytical methods among different researchers, and only the qualitative conclusion that climate change increases the vulnerability of wheat production is recognized. Especially, there are few reports on the effects of climate change on the yield formation of winter wheat, especially on the spikegrain structure, and these studies are difficult to apply in practical cultivation. Based on this, taking the dynamic data of spikegrain structure of winter wheat observed in the meteorological and phenological observation stations of Jiangsu Province from 1980 to 2011 as a sample, the effect of climate change on the formation of spikegrain structure and the final effect on the yield of winter wheat were analyzed.
Materials and Methods
Winter wheat and meteorological data
The spikegrain structure and yield data of winter wheat were derived from the 1980-2011 crop observation annual reports of 10 winter wheat observation stations in Jiangsu meteorological and phenological observation stations in the China Meteorological Observation Network (Table 1). The meteorological data were derived from the 1960-2011 observational monthly reports of the national basic meteorological observation sites at the same observation site. The specific observation data were provided by the Jiangsu Meteorological Information Center.
Table 1Jiangsu winter wheat observation stations
NameShort for nameLatitude Longitude
GanyuGY34.83119.12
XuzhouXZ34.28117.15
ShuyangSY34.10118.75
BinhaiBH34.03119.82
HuaianHA33.60119.03 DafengDF33.20120.48
XuyiXY32.98118.52
XinghuaXH32.93119.83
RugaoRG32.37120.57
KunshanKS31.42120.95
Processing method of winter wheat observation data
According to Specifications of Agrometeorological Observation of China Meteorological Administration［25］, units for yield analysis: the unit of number of spikes (NS for short) is spikes/m2; the unit of grain number per spike (GNPS) is grains/spike; the unit of grain weight (thousandgrain weight, TSW for short) is g/1 000 grains; and the unit yield (UY for short) is g/m2. The growth period of winter wheat was divided into 12 growth stages, as shown in Table 2.
Table 2Growth stages of winter wheat
NumberGrowth stageShort for growth stage
1SowingSproutingSOWSPR
2SproutingTriphyllousSPRTRI
3TriphyllousTilleringTRITIL
4TilleringOverwinteringTILOWI
5OverwinteringRegreeningOWIREG
6RegreeningSettingREGSET
7SettingJointingSETJOI
8JointingBootingJOIBOO
9BootingHeadingBOOHEA
10HeadingAnthesisHEAANT
11AnthesisMilkANTMIL
12MilkMatureMILMAT
13Growth stageGS
Interpolation was performed using GIS. The contour lines were analyzed, and a distribution map was drawn.
Calculation method of climate change scenario data
Shang et al.［24］believe that it is one of the ideal methods to extrapolate climate change scenarios with climate facts, that is, the climate change trend is usually expressed by the climate change rate (CTR). According to this, let the continuous observation data be BY and the observation period be t, it can be expressed as:
BY=a+b×t……(1)
Then:
CTR=10×b……(2)
(2) CTR in the formula represents the variation of a meteorological element caused by climate change in the next 10 years.
Evaluation model on the climate change
Evaluation model of Spikegrain structure
SHANG et al.［26］deem that to assess the impact of meteorological conditions on production objects by the integrating regression method is better. Accordingly, let the evaluation object be Yi (t) (where in i is the spikegrain structure, and refers to the number of spikes, number of grains per spike and thousandgrain weight when i=1, 2 and 3, respectively), and the meteorological element be Xjk(t) (wherein j is the meteorological factor, and refers to the active accumulated temperature (AAAT), accumulated precipitation (AP) and radiation (RAD) when j=1, 2 and 3, respectively; and k is the assessment period, that is, different growth stages (see Table 2 for details), then: Yi(t)=a0+∑lj=1∑mk=1ajkXjk(t)……(3)
Equation (3) can also be written as:
Yi(t)=a0+∑mk=1∑lj=1ajkXjk(t)……(4)
Suppose:
YTij(t)=∑mk=1ajkXjk(t), YDik(t)=∑lj=1ajkXjk(t), equations (3) and (4) can be written as:
Yi(t)=a0+∑lj=1YTij(t)……(5)
Yi(t)=a0+∑mk=1YDik(t)……(6)
It can be seen from equation (5) that the effect of meteorological conditions on the spikegrain structure of winter wheat is equal to the sum of the effects of meteorological elements. It can be seen from equation (6) that the effect of meteorological conditions on the spikegrain structure of winter wheat is also equal to the sum of effects at various stages. Using the spikegrain structures actually observed in the 10 winter wheat observation stations in Jiangsu Province in 1980-2011 and the corresponding active accumulated temperature, accumulated precipitation and radiation at different growth stages in the same period, the ajk in (3) was obtained by linear regression method, to realize parameterization of the assessment equation.
Suppose that the variation of a certain element in the spikegrain structure of winter wheat caused by climate change is ΔYi, then
ΔYi=∑lj=1∑mk=1ajkΔXjk=∑lj=1∑mk=1ajkCTRjk……(7)
From equation (5) to (7), the effects of climate change on yield components (the number of spikes, number of grains per spike, and thousandgrain weight) can be calculated. CTRjk in equation (7) can be calculated by formula (2) using the corresponding active accumulated temperature, accumulated precipitation and radiation at different growth stages actually observed in the 10 winter wheat observation stations in Jiangsu Province in 1960-2011.
Evaluation model of Unit yield
The China Meteorological Administration［28］stipulates that the years harvest is divided into bumper year, slightly bumper year, common year with slight increase, common year with slight decrease, slightly lean year and lean year according to the percentage increase or decrease of the yield of the very year to the average (the latest five years). Accordingly, the effect of climate change on winter wheat yield is assessed by the percentage (set to be VPER)of unit yield variation caused by climate change to the unit yield of the normalclimate year. The criteria are shown in Table 3.
Table 3Criteria for assessment of yield variation caused by climate change Year typeBumper yearSlightly bumper yearCommon year with slight increaseCommon year with slight decreaseSlightly lean yearLean year
CriteriaVPER≥55＜VPER≤33＜VPER≤00＜VPER≤-3-3＜VPER≤-5VPER＜-5
According to the yield composition principle of winter wheat, the formula for calculating the percentage of yield variation caused by climate change in the unit yield of the normalclimate year:
VPER=(Y1+ΔY1)×(Y2+ΔY2)×(Y3+ΔY3)-Y1×Y2×Y3Y1×Y2×Y3 ×100(12)
In equation (12), Yi is the average observed value during the test period. Using this formula, the effect of climate change on winter wheat yield could be calculated.
Agricultural Biotechnology2019
Results and Analysis
According to the spikegrain structure data of winter wheat observed in 10 Agrometeorological stations in Jiangsu Province from 1980 to 2011, the relationships between spikegrain structure of winter wheat and the meteorological conditions (temperature, light and water) at each growth stage in Jiangsu Province were calculated. According to the meteorological data observed in 1960-2011, the variations in meteorological conditions (temperature, light and water) caused by meteorological changes in each station over the next 10 years were calculated through equation (2), and the variations in spikegrain structure caused by meteorological changes were calculated through equation (7). The variation in unit yield caused by variations in meteorological conditions during winter wheat growth and development caused by meteorological changes was calculated from equation (12). The specific statistical results are shown in Table 4-Table 9, Fig. 1.
Effect of climate change on number of spikes
(1) It could be seen from Table 4 that the variation in the number of effective spikes caused by climate change differed obviously between stations and had obvious regional characteristics. The variations in the province ranged from -57.33 to 97.17 spikes/［m2?(10a)］, with an average of -2.29 spikes/［m2?(10a)］, accounting for -0.91% of the normalclimate year value, that is, lower than 1%. The provinces overall number of effective spikes did not vary significantly with climate change. The variation in the number of effective spike caused by climate change was mainly increase in the northern and western parts Jiangsu and decrease in the central and southern Jiangsu and coastal areas, indicating that a large daily difference is conducive to the increase of number of effective panicles, and vice versa. (2) It could be seen from Table 4 that the effect of climate change on the number of spikes was different at different growth stages. In terms of the provincial average, the number of spikes was decreased due to the climate change from seeding to emergence, increased due to the climate change from emergence to tillering, decreased due to the climate change from tillering to setting, increased due to the climate change from setting to heading, and decreased due to the climate change from heading to maturation. Throughout the growth period, it was mainly reduced. The accumulated climate change during the growth period of winter wheat was characterized by warm winter, indicating that under normal production conditions, warm winter is not good for increasing the number of effective spikes.
(3) It could be seen from Table 4 that the combined effect of climate change (temperature, light and water) on the number of effective spikes differed at different stations. For instance, the number of effective spikes was increased in Ganyu in northern Jiangsu, by 67.19 spikes/［m2?(10a)］, and decreased in Kunshan in southern Jiangsu, by -57.33 spikes/［m2?(10a)］. The effects of temperature, light and water were also different at different growth stages at different observation stations. The variation of effective accumulated temperature caused a significant reduction, and the variations in cumulative precipitation and radiation caused an increase, of which the precipitation caused a greater increase. From the respective of the provincial average, the variation caused by effective accumulated temperature was -17.99 spikes/［m2?(10a)］; the variation caused by precipitation was 14.52 spikes/［m2?(10a)］; and the variation caused by radiation was 1.19 spikes/［m2?(10a)］. Therefore, the variations caused by the meteorological elements ranked as effective accumulated temperature > accumulated precipitation > radiation.
Effect of climate change on number of grains per spike
(1) It could be seen from Table 6 that climate change caused a variation in the number of grains. The variation differed between stations obviously, with obvious regional characteristics. The variations in the province ranged from -0.58 to 4.87 grains/［spike?(10a)］, with an average of 1.22 grains/［spike?(10a)］, accounting for about 4.19% of the value of the normalclimate year. Except Rugao among the coastal areas, the number of grains increased in all other observation stations, indicating that climate change caused the variation in the number of grains per spike in an increasing direction. (2) It could be seen from Table 6 that the effect of climate change on the number of grains per spike was different at different growth stages. In the whole province, the average presented an "increasingdecreasing" periodic variation, with a period of about 1 to 2 growth stages.
(3) It could be seen from Table 7 that the combined effect of climate change (temperature, light and water) on the number of grains per spike was different for different stations. The effects of temperature, light and water were different at different growth stages at different observation stations. In terms of the provincial average, the variation of effective accumulated temperature caused an increase in the number of grains, and the variation caused by the effective accumulated temperature was 4.93 grains/［spike?(10a)］; the variation caused by the accumulated precipitation was also positive, of 3.49 grains/［spike?(10a)］; and the variation caused by the variation in radiation was negative, of -7.21 grains/［spike?(10a)］. Therefore, the variations caused by these factors ranked as radiation > effective accumulated temperature > accumulated precipitation.
Effect of climate change on thousandgrain weight
(1) It could be seen from Table 8 that climate change caused a variation in thousandgrain weight. The variation differed between stations obviously, with obvious regional characteristics. The variations in the province ranged from -1.66 to 3.22 g/［1 000 grains?(10a)］, with an average of 1.31 g/［1 000 grains?(10a)］, accounting for 3.5% of value of the normalclimate year. In the province, 80% of the observation stations showed an increase, and the total decrease of stations with a decrease only accounted for 3%-4% of value of the normalclimate year, indicating that the grain weight mainly varied in an increasing direction.
(2) It could be seen from Table 8 that the effect of climate change on the thousandgrain weight was different at different growth stages. From the respective of the provincial average, the thousandgrain weight presented a "decreasingincreasing" periodic variation, with a period of 1 to 2 growth stages.
(3) It could be seen from Table 9 that the combined effect of climate change (temperature, light and water) on the thousandgrain weight was different at different stations. The effects of temperature, light and water were also different at different growth stages at different observation stations. In terms of the provincial average, the variation in effective accumulated temperature caused an increase, which was 1.92 g/［1 000 grains?(10a)］; the variation caused by the accumulated precipitation was a decrease, which was -3.98 g/［1 000 grains?(10a)］; and the variation caused by radiation was an increase, which was 3.36 g/［1 000 grains?(10a)］. That is, variations caused by the various factors were in order of the accumulated precipitation > radiation > effective accumulated temperature. Effect of climate change on unit yield
It could be seen from statistical analysis and Fig. 1 that the variations in unit yield of winter wheat in Jiangsu Province caused by climate change accounted for -4.32%-17.23% of the unit yield under normal climate condition, and the provincial average was 6.4%, reaching the standard of bumper year, that is, climate change was conducive to improvement of winter wheat yield Jiangsu Province. Different regions were unbalanced. Specifically, the worst region reached the slightly lean year standard, while most regions reached the bumper year standard. The regions where the yield of winter wheat was reduced by climate change were mainly in the southcentral part of southern Jiangsu and southeast part of northern Jiangsu, and the regions where the yield of winter wheat was increased by climate change were the northeast and southwest parts of northern Jiangsu, the west part of the central Jiangsu and the southwest part of southern Jiangsu.
Table 4Effect of climate change on the number of spikes at different growth stages
GSGYXZSYBHHADFXYXHRGKSAverage
SOWSPR-27.76-146.88-35.2526.4110.22-202.4575.06-7.42-16.75128.52-19.63
SPRTRI39.67-1133.9825.02-77.2968.579.04-57.342.1344.3111.71
TRITIL-111.2199.8-80.627.2144.631.56-11.4414.73-4.8857.051.68
TILOWI26.3368.4623.4-32.122.46-195.84-65.8345.61-13.98-17.74-15.93
OWIREG114.68-109.06-11.68-57.455.55153.95-40.48-22.65-42.69-56.56-1.63
REGSET45.116.8828.33-25.74-32.9-167.961.01-16.4662.4622.96-1.63
SETJOI30.3628.0535.9424.41-23.02-29.9-74.630.313.5186.0912.11
JOIBOO93.2459.42-21.911.28140.59-20.6686.398.73-36.33-74.6332.6
BOOHEA-66.77-30.8621.31-42.36-8.07252.9920.454.01-62.22-6.478.2
HEAANT-2.23-43.53-2.870.34-19.95-39.649.74-10.7-7.8445.24-7.14
ANTMIL-122.911.556.6835.32-41.64152.174.48-70.1217.22-236.6-17.39
MILMAT48.6772.613.67-3.03-43.52-14.99-46.56-33.7513.9-49.5-5.25
Sum67.195.440.98-40.667.06-42.2197.17-25.02-35.47-57.33-2.29
Table 5Effects of different meteorological elements on the number of spikes
FactorsGYXZSYBHHADFXYXHRGKSAverage
AAAT0.54-56.46-9.29-82.04-199.4963.32302.93-34.545.47-170.36-17.99
AP-12.41100.19-26.245.32123.1438.7-32.9218.78-8.37-61.0414.52
RAD79.06-38.2936.5136.0683.41-144.23-172.84-9.26-32.57174.071.19
Sum67.195.440.98-40.667.06-42.2197.17-25.02-35.47-57.33-2.29 Table 6Effect of climate change on the number of grains per spike at different growth stages
GSGYXZSYBHHADFXYXHRGKSAverage
SOWSPR13.1716.11-2.16-1.24-7.0220.835.42.6-2.88-1.74.31
SPRTRI-8.42.428.53-6.91-16.18-5.141.73-1.58-4.740.85-2.94
TRITIL7.91-11.25-6.121.25.70.98-4.530.34-0.260.36-0.57
TILOWI9.73-7.82-0.0510.52.1514.84-12.20.42-2.8-4.161.06
OWIREG-10.723.96-5.84-27.5815.94-11.710.38-1.133.882.34-3.05
REGSET3.997.0118.987.33-12.410.4412.62-1.56-4.11.984.43
SETJOI-9.22-6.830.24-3.37-1.167.66-11.73-9.48-0.181.47-3.26
JOIBOO-1.77-5.4516.9532.1637.714.756.94-1.924.4-8.818.5
BOOHEA-1.010.31-5.65-18.43-2.72-17.930.97-2.944.83-0.79-4.34
HEAANT-2.644.83-3.582.680.743.081.62-1.490.480.910.66
ANTMIL4.544.06-19.62.47-15.45-23.779.2516.391.697.33-1.31
MILMAT-3.82-6.63-0.651.98-7.30.84-103.34-0.90.35-2.28
Sum1.760.721.050.790.014.870.452.99-0.580.131.22
Table 7Effects of different meteorological elements on the number of grains per spike
FactorsGYXZSYBHHADFXYXHRGKSAverage
AAAT1.761.39-14.8657-28.45-7.7331.9315.93-8.260.634.93
AP2.33-63.093.6330.78-3.54-9.242.23.697.983.49
RAD-2.335.3312.82-59.84-2.3216.14-22.24-15.143.99-8.48-7.21
Sum1.760.721.050.790.014.870.452.99-0.580.131.22
Table 8Effect of climate change on the thousandgrain weight at different growth stages
FactorsGYXZSYBHHADFXYXHRGKSAverage
SOWSPR4.77-1.67-35.25-0.116.37-1.341.621.680.162.65-2.11
SPRTRI-2.52-0.2233.98-4.3711.792.873.083.440.17-4.634.36
TRITIL3.935.25-80.620.62-4.03-1.483.58-0.950.15-3.83-7.74
TILOWI3.840.5723.42.31-2.2-8.89-1.52-1.750.03-2.841.3
OWIREG-7.8-10.88-11.68-1.65-11.15.45-5.57-0.19-0.95-2.61-4.7
REGSET0.2410.6228.335.9612.01-0.63-9.313.55-0.72-6.414.36
SETJOI-4.71-2.3435.942.14-0.75-4.057.49-1.483.13-0.253.51
JOIBOO-3.59-1.21-21.915.83-28.17-3.59-5.43-5.561.459.25-5.29
BOOHEA1.57-0.3421.31-1.284.227.86-1.29-2.20.5-0.213.01
HEAANT-0.63-1.85-2.871.07-0.54-1.91-3.21-0.21-0.29-7.17-1.76
ANTMIL2.081.446.68-9.29.159.083.692.35-0.1913.983.91
MILMAT1.161.393.67-0.555.49-0.155.712.41-0.265.722.46
Sum-1.660.760.980.772.243.22-1.161.093.183.651.31
Table 9Effects of different meteorological elements on the thousandgrain weight
FactorsGYXZSYBHHADFXYXHRGKSAverage AAAT3.12-10.34-9.2912.4818.031.88-11.81-0.150.0315.241.92
AP0.929.19-26.24-1.9-14.610.450.44-1.6-0.04-6.37-3.98
RAD-5.71.9136.51-9.81-1.180.8910.212.843.19-5.223.36
Sum-1.660.760.980.772.243.22-1.161.093.183.651.31
Fig. 1Regional distribution of variation in unit yield of winter wheat caused by climate change in Jiangsu Province
Conclusions and Discussion
(1) Through this method, the main reason for the yield variation caused by climate change could be systematically analyzed to be the variation of spikegrain structure triggered by climate change, which further affected yield and quality. This is more practical than conclusions that obtained by conventional methods. Through comprehensive analysis, it was found that the spikegrain structure of winter wheat in Jiangsu varied with climate change, which was mainly reflected by reduced number of grains per spike and increased number of grains and thousandgrain weight, which caused the trend in unit yield of increasing with climate change. Zheng et al.［28］believe that the number of spikes, number of grains per spike and thousandgrain weight have positive effects on yield, and the contribution rates rank from large to small as follows: number of spikes > number of grains per spike > thousandgrain weight. Therefore, the research focus of Jiangsu winter wheat cultivation techniques to cope with climate change is the cultivation technique of ensuring enough spikes.
(2) Shang et al.［29］deem that with the climate change, the stage when meteorological conditions changed significantly during the growth and development of winter wheat in Jiangsu is the vegetative growth period, and this new combination mode of temperature, light and water is moving toward the direction of favoring the formation of large spikes (increase of both grain number and grain weight). However, Jiangsu is a ricewheat rotation area where farmers have been prolonging the growth period of rice in recent years to improve rice yield and quality. In early December 2015, snowfall had occurred, but rice still grew in the field and the harvest time was later than normal by about one month, which severely shortened the vegetative growth period of winter wheat, especially the prewinter growth period, which affected the number of effective spikes. Furthermore, with the climate change, the climatic conditions during the growth and development of winter wheat in Jiangsu have a tendency of going against the increase of the number of spikes. Due to the above two reasons which are superimposed, with the climate change, Jiangsus climatic conditions are more unfavorable for the increase of the number of effective spikes. Therefore, how to achieve enough spikes by properly adjusting the seeding rate, transforming from the current cultivation mode that determines the number of effective spikes by the number of effective tillers to the cultivation mode that determines the number of effective spikes by the number of basic seedlings and the number of effective tillers and changing the fertilizer and water control and other cultivation measures has become a subject that Jiangsu winter wheat production must face in response to climate change. (3) The trend of climate change is a longterm sequence of events, and the annual output of winter wheat is mainly determined under coordination of the growth and development of winter wheat with temperature, light and water. Therefore, the effective measure for wheat production science to cope with climate change is to establish a business system that monitors the growth dynamics of winter wheat in real time, timely assesses the impact of meteorological conditions on winter wheat production and carries out artificial irrigation to adjust the local microclimate during specific growth process, so as to make the meteorological conditions of the year suitable for the growth and development of winter wheat, that is, to reduce the impact of climate change on winter wheat production, maintain the dynamic balance between winter wheat growth period and growth, and achieve high yield and quality of winter wheat finally.
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［11］ GENG T , FU W, CHEN Q, et al. Spatialtemporal feature of climate resources and adaptation of winter wheat during last 20 years in Henan Province［J］. Journal of Triticeae Crops, 2013, 3(4): 652-661.
［12］ WANG JY, YE W, LIM H, et al. Variations of winter wheat growth stages under climate changes in Shandong Province［J］. Chinese Agricultural Science Bulletin, 2013, 29(14): 161-166.
Key wordsYield per unit area; Spikegrain structure; Climate assessment
Received: October 13, 2018Accepted: December 22, 2018
Supported by 2016 Key Business Project of Jiangsu Meteorological Bureau (20161122).
Shun SHANG (1989-), male, P. R. China, research assistant, master, devoted to research about marine weather service.
*Corresponding author. Email: shangshun@qq.com.
Chao et al.［1］ believe that the fifth assessment report of IPCC is more objective and comprehensive than the previous reports, and global warming has become common consensus. Piao et al.［2］, Lobell et al.［3］ and Asseng et al.［4］believe that global warming seriously affects the sustainable development of world agriculture, and Guo et al.［5］believe that paying attention to the impact of climate change on crop production is an important task for Chinas safe agricultural production. Wheat is one of the top three food crops in the world, and according to this, the safety of winter wheat production is one of the key contents of food security and an important area for agriculture to cope with climate change. Chinas wheat production ranks first in the world all year round, accounting for about 20% of its total production. Jiangsu Province is the fifth largest wheat producer in China, with a production accounting for about 7% of national production. Therefore, fluctuations in the yield and quality of winter wheat in Jiangsu Province have an important impact on food security in China and the world. Many scholars at home and abroad have studied the impact of climate change on winter wheat production from different perspectives. For instance, Prasad et al.［6］, Wang et al.［7］, Tian et al.［8］, Quan et al.［9］and many other scholars believe that climate warming leads to obviously high temperature in winter, resulting in early jointing of winter wheat and increase of freezing damage. Many research teams concluded that climate change increased the vulnerability of winter wheat production in 2013 (Chang and Lan［10］, geng et al.［11］, Wang et al.［12］, Li et al.［13］, Jing et al.［14］, Wang et al.［15］, Li et al.［16］, Gao et al.［17］) and 2014 (Li et al.［18］, Wilcox and Makowski［19］, Johnen et al.［20］, Talukder et al.［21］, Mirjam et al.［22］and Nourdeldin et al.［23］). Shang et al.［24］systematically summarized and reviewed research papers at home and abroad on the relationship between winter wheat production and climate change, and deem that at present, at home and abroad, the main technical method for assessing the impact of climate change on wheat production is to generate future climate scenarios by extrapolating the trend of climate change facts or using climate models, use the mechanism or statistical model of the relationship between winter wheat growth and meteorological conditions to simulate winter wheat production condition under future climate scenarios, and make an assessment report about the effect of climate change on winter wheat yield finally. The authoritativeness of quantitative assessment reports on the effect of climate change on winter wheat yield has not been confirmed due to the differences in experimental design, selected materials and analytical methods among different researchers, and only the qualitative conclusion that climate change increases the vulnerability of wheat production is recognized. Especially, there are few reports on the effects of climate change on the yield formation of winter wheat, especially on the spikegrain structure, and these studies are difficult to apply in practical cultivation. Based on this, taking the dynamic data of spikegrain structure of winter wheat observed in the meteorological and phenological observation stations of Jiangsu Province from 1980 to 2011 as a sample, the effect of climate change on the formation of spikegrain structure and the final effect on the yield of winter wheat were analyzed.
Materials and Methods
Winter wheat and meteorological data
The spikegrain structure and yield data of winter wheat were derived from the 1980-2011 crop observation annual reports of 10 winter wheat observation stations in Jiangsu meteorological and phenological observation stations in the China Meteorological Observation Network (Table 1). The meteorological data were derived from the 1960-2011 observational monthly reports of the national basic meteorological observation sites at the same observation site. The specific observation data were provided by the Jiangsu Meteorological Information Center.
Table 1Jiangsu winter wheat observation stations
NameShort for nameLatitude Longitude
GanyuGY34.83119.12
XuzhouXZ34.28117.15
ShuyangSY34.10118.75
BinhaiBH34.03119.82
HuaianHA33.60119.03 DafengDF33.20120.48
XuyiXY32.98118.52
XinghuaXH32.93119.83
RugaoRG32.37120.57
KunshanKS31.42120.95
Processing method of winter wheat observation data
According to Specifications of Agrometeorological Observation of China Meteorological Administration［25］, units for yield analysis: the unit of number of spikes (NS for short) is spikes/m2; the unit of grain number per spike (GNPS) is grains/spike; the unit of grain weight (thousandgrain weight, TSW for short) is g/1 000 grains; and the unit yield (UY for short) is g/m2. The growth period of winter wheat was divided into 12 growth stages, as shown in Table 2.
Table 2Growth stages of winter wheat
NumberGrowth stageShort for growth stage
1SowingSproutingSOWSPR
2SproutingTriphyllousSPRTRI
3TriphyllousTilleringTRITIL
4TilleringOverwinteringTILOWI
5OverwinteringRegreeningOWIREG
6RegreeningSettingREGSET
7SettingJointingSETJOI
8JointingBootingJOIBOO
9BootingHeadingBOOHEA
10HeadingAnthesisHEAANT
11AnthesisMilkANTMIL
12MilkMatureMILMAT
13Growth stageGS
Interpolation was performed using GIS. The contour lines were analyzed, and a distribution map was drawn.
Calculation method of climate change scenario data
Shang et al.［24］believe that it is one of the ideal methods to extrapolate climate change scenarios with climate facts, that is, the climate change trend is usually expressed by the climate change rate (CTR). According to this, let the continuous observation data be BY and the observation period be t, it can be expressed as:
BY=a+b×t……(1)
Then:
CTR=10×b……(2)
(2) CTR in the formula represents the variation of a meteorological element caused by climate change in the next 10 years.
Evaluation model on the climate change
Evaluation model of Spikegrain structure
SHANG et al.［26］deem that to assess the impact of meteorological conditions on production objects by the integrating regression method is better. Accordingly, let the evaluation object be Yi (t) (where in i is the spikegrain structure, and refers to the number of spikes, number of grains per spike and thousandgrain weight when i=1, 2 and 3, respectively), and the meteorological element be Xjk(t) (wherein j is the meteorological factor, and refers to the active accumulated temperature (AAAT), accumulated precipitation (AP) and radiation (RAD) when j=1, 2 and 3, respectively; and k is the assessment period, that is, different growth stages (see Table 2 for details), then: Yi(t)=a0+∑lj=1∑mk=1ajkXjk(t)……(3)
Equation (3) can also be written as:
Yi(t)=a0+∑mk=1∑lj=1ajkXjk(t)……(4)
Suppose:
YTij(t)=∑mk=1ajkXjk(t), YDik(t)=∑lj=1ajkXjk(t), equations (3) and (4) can be written as:
Yi(t)=a0+∑lj=1YTij(t)……(5)
Yi(t)=a0+∑mk=1YDik(t)……(6)
It can be seen from equation (5) that the effect of meteorological conditions on the spikegrain structure of winter wheat is equal to the sum of the effects of meteorological elements. It can be seen from equation (6) that the effect of meteorological conditions on the spikegrain structure of winter wheat is also equal to the sum of effects at various stages. Using the spikegrain structures actually observed in the 10 winter wheat observation stations in Jiangsu Province in 1980-2011 and the corresponding active accumulated temperature, accumulated precipitation and radiation at different growth stages in the same period, the ajk in (3) was obtained by linear regression method, to realize parameterization of the assessment equation.
Suppose that the variation of a certain element in the spikegrain structure of winter wheat caused by climate change is ΔYi, then
ΔYi=∑lj=1∑mk=1ajkΔXjk=∑lj=1∑mk=1ajkCTRjk……(7)
From equation (5) to (7), the effects of climate change on yield components (the number of spikes, number of grains per spike, and thousandgrain weight) can be calculated. CTRjk in equation (7) can be calculated by formula (2) using the corresponding active accumulated temperature, accumulated precipitation and radiation at different growth stages actually observed in the 10 winter wheat observation stations in Jiangsu Province in 1960-2011.
Evaluation model of Unit yield
The China Meteorological Administration［28］stipulates that the years harvest is divided into bumper year, slightly bumper year, common year with slight increase, common year with slight decrease, slightly lean year and lean year according to the percentage increase or decrease of the yield of the very year to the average (the latest five years). Accordingly, the effect of climate change on winter wheat yield is assessed by the percentage (set to be VPER)of unit yield variation caused by climate change to the unit yield of the normalclimate year. The criteria are shown in Table 3.
Table 3Criteria for assessment of yield variation caused by climate change Year typeBumper yearSlightly bumper yearCommon year with slight increaseCommon year with slight decreaseSlightly lean yearLean year
CriteriaVPER≥55＜VPER≤33＜VPER≤00＜VPER≤-3-3＜VPER≤-5VPER＜-5
According to the yield composition principle of winter wheat, the formula for calculating the percentage of yield variation caused by climate change in the unit yield of the normalclimate year:
VPER=(Y1+ΔY1)×(Y2+ΔY2)×(Y3+ΔY3)-Y1×Y2×Y3Y1×Y2×Y3 ×100(12)
In equation (12), Yi is the average observed value during the test period. Using this formula, the effect of climate change on winter wheat yield could be calculated.
Agricultural Biotechnology2019
Results and Analysis
According to the spikegrain structure data of winter wheat observed in 10 Agrometeorological stations in Jiangsu Province from 1980 to 2011, the relationships between spikegrain structure of winter wheat and the meteorological conditions (temperature, light and water) at each growth stage in Jiangsu Province were calculated. According to the meteorological data observed in 1960-2011, the variations in meteorological conditions (temperature, light and water) caused by meteorological changes in each station over the next 10 years were calculated through equation (2), and the variations in spikegrain structure caused by meteorological changes were calculated through equation (7). The variation in unit yield caused by variations in meteorological conditions during winter wheat growth and development caused by meteorological changes was calculated from equation (12). The specific statistical results are shown in Table 4-Table 9, Fig. 1.
Effect of climate change on number of spikes
(1) It could be seen from Table 4 that the variation in the number of effective spikes caused by climate change differed obviously between stations and had obvious regional characteristics. The variations in the province ranged from -57.33 to 97.17 spikes/［m2?(10a)］, with an average of -2.29 spikes/［m2?(10a)］, accounting for -0.91% of the normalclimate year value, that is, lower than 1%. The provinces overall number of effective spikes did not vary significantly with climate change. The variation in the number of effective spike caused by climate change was mainly increase in the northern and western parts Jiangsu and decrease in the central and southern Jiangsu and coastal areas, indicating that a large daily difference is conducive to the increase of number of effective panicles, and vice versa. (2) It could be seen from Table 4 that the effect of climate change on the number of spikes was different at different growth stages. In terms of the provincial average, the number of spikes was decreased due to the climate change from seeding to emergence, increased due to the climate change from emergence to tillering, decreased due to the climate change from tillering to setting, increased due to the climate change from setting to heading, and decreased due to the climate change from heading to maturation. Throughout the growth period, it was mainly reduced. The accumulated climate change during the growth period of winter wheat was characterized by warm winter, indicating that under normal production conditions, warm winter is not good for increasing the number of effective spikes.
(3) It could be seen from Table 4 that the combined effect of climate change (temperature, light and water) on the number of effective spikes differed at different stations. For instance, the number of effective spikes was increased in Ganyu in northern Jiangsu, by 67.19 spikes/［m2?(10a)］, and decreased in Kunshan in southern Jiangsu, by -57.33 spikes/［m2?(10a)］. The effects of temperature, light and water were also different at different growth stages at different observation stations. The variation of effective accumulated temperature caused a significant reduction, and the variations in cumulative precipitation and radiation caused an increase, of which the precipitation caused a greater increase. From the respective of the provincial average, the variation caused by effective accumulated temperature was -17.99 spikes/［m2?(10a)］; the variation caused by precipitation was 14.52 spikes/［m2?(10a)］; and the variation caused by radiation was 1.19 spikes/［m2?(10a)］. Therefore, the variations caused by the meteorological elements ranked as effective accumulated temperature > accumulated precipitation > radiation.
Effect of climate change on number of grains per spike
(1) It could be seen from Table 6 that climate change caused a variation in the number of grains. The variation differed between stations obviously, with obvious regional characteristics. The variations in the province ranged from -0.58 to 4.87 grains/［spike?(10a)］, with an average of 1.22 grains/［spike?(10a)］, accounting for about 4.19% of the value of the normalclimate year. Except Rugao among the coastal areas, the number of grains increased in all other observation stations, indicating that climate change caused the variation in the number of grains per spike in an increasing direction. (2) It could be seen from Table 6 that the effect of climate change on the number of grains per spike was different at different growth stages. In the whole province, the average presented an "increasingdecreasing" periodic variation, with a period of about 1 to 2 growth stages.
(3) It could be seen from Table 7 that the combined effect of climate change (temperature, light and water) on the number of grains per spike was different for different stations. The effects of temperature, light and water were different at different growth stages at different observation stations. In terms of the provincial average, the variation of effective accumulated temperature caused an increase in the number of grains, and the variation caused by the effective accumulated temperature was 4.93 grains/［spike?(10a)］; the variation caused by the accumulated precipitation was also positive, of 3.49 grains/［spike?(10a)］; and the variation caused by the variation in radiation was negative, of -7.21 grains/［spike?(10a)］. Therefore, the variations caused by these factors ranked as radiation > effective accumulated temperature > accumulated precipitation.
Effect of climate change on thousandgrain weight
(1) It could be seen from Table 8 that climate change caused a variation in thousandgrain weight. The variation differed between stations obviously, with obvious regional characteristics. The variations in the province ranged from -1.66 to 3.22 g/［1 000 grains?(10a)］, with an average of 1.31 g/［1 000 grains?(10a)］, accounting for 3.5% of value of the normalclimate year. In the province, 80% of the observation stations showed an increase, and the total decrease of stations with a decrease only accounted for 3%-4% of value of the normalclimate year, indicating that the grain weight mainly varied in an increasing direction.
(2) It could be seen from Table 8 that the effect of climate change on the thousandgrain weight was different at different growth stages. From the respective of the provincial average, the thousandgrain weight presented a "decreasingincreasing" periodic variation, with a period of 1 to 2 growth stages.
(3) It could be seen from Table 9 that the combined effect of climate change (temperature, light and water) on the thousandgrain weight was different at different stations. The effects of temperature, light and water were also different at different growth stages at different observation stations. In terms of the provincial average, the variation in effective accumulated temperature caused an increase, which was 1.92 g/［1 000 grains?(10a)］; the variation caused by the accumulated precipitation was a decrease, which was -3.98 g/［1 000 grains?(10a)］; and the variation caused by radiation was an increase, which was 3.36 g/［1 000 grains?(10a)］. That is, variations caused by the various factors were in order of the accumulated precipitation > radiation > effective accumulated temperature. Effect of climate change on unit yield
It could be seen from statistical analysis and Fig. 1 that the variations in unit yield of winter wheat in Jiangsu Province caused by climate change accounted for -4.32%-17.23% of the unit yield under normal climate condition, and the provincial average was 6.4%, reaching the standard of bumper year, that is, climate change was conducive to improvement of winter wheat yield Jiangsu Province. Different regions were unbalanced. Specifically, the worst region reached the slightly lean year standard, while most regions reached the bumper year standard. The regions where the yield of winter wheat was reduced by climate change were mainly in the southcentral part of southern Jiangsu and southeast part of northern Jiangsu, and the regions where the yield of winter wheat was increased by climate change were the northeast and southwest parts of northern Jiangsu, the west part of the central Jiangsu and the southwest part of southern Jiangsu.
Table 4Effect of climate change on the number of spikes at different growth stages
GSGYXZSYBHHADFXYXHRGKSAverage
SOWSPR-27.76-146.88-35.2526.4110.22-202.4575.06-7.42-16.75128.52-19.63
SPRTRI39.67-1133.9825.02-77.2968.579.04-57.342.1344.3111.71
TRITIL-111.2199.8-80.627.2144.631.56-11.4414.73-4.8857.051.68
TILOWI26.3368.4623.4-32.122.46-195.84-65.8345.61-13.98-17.74-15.93
OWIREG114.68-109.06-11.68-57.455.55153.95-40.48-22.65-42.69-56.56-1.63
REGSET45.116.8828.33-25.74-32.9-167.961.01-16.4662.4622.96-1.63
SETJOI30.3628.0535.9424.41-23.02-29.9-74.630.313.5186.0912.11
JOIBOO93.2459.42-21.911.28140.59-20.6686.398.73-36.33-74.6332.6
BOOHEA-66.77-30.8621.31-42.36-8.07252.9920.454.01-62.22-6.478.2
HEAANT-2.23-43.53-2.870.34-19.95-39.649.74-10.7-7.8445.24-7.14
ANTMIL-122.911.556.6835.32-41.64152.174.48-70.1217.22-236.6-17.39
MILMAT48.6772.613.67-3.03-43.52-14.99-46.56-33.7513.9-49.5-5.25
Sum67.195.440.98-40.667.06-42.2197.17-25.02-35.47-57.33-2.29
Table 5Effects of different meteorological elements on the number of spikes
FactorsGYXZSYBHHADFXYXHRGKSAverage
AAAT0.54-56.46-9.29-82.04-199.4963.32302.93-34.545.47-170.36-17.99
AP-12.41100.19-26.245.32123.1438.7-32.9218.78-8.37-61.0414.52
RAD79.06-38.2936.5136.0683.41-144.23-172.84-9.26-32.57174.071.19
Sum67.195.440.98-40.667.06-42.2197.17-25.02-35.47-57.33-2.29 Table 6Effect of climate change on the number of grains per spike at different growth stages
GSGYXZSYBHHADFXYXHRGKSAverage
SOWSPR13.1716.11-2.16-1.24-7.0220.835.42.6-2.88-1.74.31
SPRTRI-8.42.428.53-6.91-16.18-5.141.73-1.58-4.740.85-2.94
TRITIL7.91-11.25-6.121.25.70.98-4.530.34-0.260.36-0.57
TILOWI9.73-7.82-0.0510.52.1514.84-12.20.42-2.8-4.161.06
OWIREG-10.723.96-5.84-27.5815.94-11.710.38-1.133.882.34-3.05
REGSET3.997.0118.987.33-12.410.4412.62-1.56-4.11.984.43
SETJOI-9.22-6.830.24-3.37-1.167.66-11.73-9.48-0.181.47-3.26
JOIBOO-1.77-5.4516.9532.1637.714.756.94-1.924.4-8.818.5
BOOHEA-1.010.31-5.65-18.43-2.72-17.930.97-2.944.83-0.79-4.34
HEAANT-2.644.83-3.582.680.743.081.62-1.490.480.910.66
ANTMIL4.544.06-19.62.47-15.45-23.779.2516.391.697.33-1.31
MILMAT-3.82-6.63-0.651.98-7.30.84-103.34-0.90.35-2.28
Sum1.760.721.050.790.014.870.452.99-0.580.131.22
Table 7Effects of different meteorological elements on the number of grains per spike
FactorsGYXZSYBHHADFXYXHRGKSAverage
AAAT1.761.39-14.8657-28.45-7.7331.9315.93-8.260.634.93
AP2.33-63.093.6330.78-3.54-9.242.23.697.983.49
RAD-2.335.3312.82-59.84-2.3216.14-22.24-15.143.99-8.48-7.21
Sum1.760.721.050.790.014.870.452.99-0.580.131.22
Table 8Effect of climate change on the thousandgrain weight at different growth stages
FactorsGYXZSYBHHADFXYXHRGKSAverage
SOWSPR4.77-1.67-35.25-0.116.37-1.341.621.680.162.65-2.11
SPRTRI-2.52-0.2233.98-4.3711.792.873.083.440.17-4.634.36
TRITIL3.935.25-80.620.62-4.03-1.483.58-0.950.15-3.83-7.74
TILOWI3.840.5723.42.31-2.2-8.89-1.52-1.750.03-2.841.3
OWIREG-7.8-10.88-11.68-1.65-11.15.45-5.57-0.19-0.95-2.61-4.7
REGSET0.2410.6228.335.9612.01-0.63-9.313.55-0.72-6.414.36
SETJOI-4.71-2.3435.942.14-0.75-4.057.49-1.483.13-0.253.51
JOIBOO-3.59-1.21-21.915.83-28.17-3.59-5.43-5.561.459.25-5.29
BOOHEA1.57-0.3421.31-1.284.227.86-1.29-2.20.5-0.213.01
HEAANT-0.63-1.85-2.871.07-0.54-1.91-3.21-0.21-0.29-7.17-1.76
ANTMIL2.081.446.68-9.29.159.083.692.35-0.1913.983.91
MILMAT1.161.393.67-0.555.49-0.155.712.41-0.265.722.46
Sum-1.660.760.980.772.243.22-1.161.093.183.651.31
Table 9Effects of different meteorological elements on the thousandgrain weight
FactorsGYXZSYBHHADFXYXHRGKSAverage AAAT3.12-10.34-9.2912.4818.031.88-11.81-0.150.0315.241.92
AP0.929.19-26.24-1.9-14.610.450.44-1.6-0.04-6.37-3.98
RAD-5.71.9136.51-9.81-1.180.8910.212.843.19-5.223.36
Sum-1.660.760.980.772.243.22-1.161.093.183.651.31
Fig. 1Regional distribution of variation in unit yield of winter wheat caused by climate change in Jiangsu Province
Conclusions and Discussion
(1) Through this method, the main reason for the yield variation caused by climate change could be systematically analyzed to be the variation of spikegrain structure triggered by climate change, which further affected yield and quality. This is more practical than conclusions that obtained by conventional methods. Through comprehensive analysis, it was found that the spikegrain structure of winter wheat in Jiangsu varied with climate change, which was mainly reflected by reduced number of grains per spike and increased number of grains and thousandgrain weight, which caused the trend in unit yield of increasing with climate change. Zheng et al.［28］believe that the number of spikes, number of grains per spike and thousandgrain weight have positive effects on yield, and the contribution rates rank from large to small as follows: number of spikes > number of grains per spike > thousandgrain weight. Therefore, the research focus of Jiangsu winter wheat cultivation techniques to cope with climate change is the cultivation technique of ensuring enough spikes.
(2) Shang et al.［29］deem that with the climate change, the stage when meteorological conditions changed significantly during the growth and development of winter wheat in Jiangsu is the vegetative growth period, and this new combination mode of temperature, light and water is moving toward the direction of favoring the formation of large spikes (increase of both grain number and grain weight). However, Jiangsu is a ricewheat rotation area where farmers have been prolonging the growth period of rice in recent years to improve rice yield and quality. In early December 2015, snowfall had occurred, but rice still grew in the field and the harvest time was later than normal by about one month, which severely shortened the vegetative growth period of winter wheat, especially the prewinter growth period, which affected the number of effective spikes. Furthermore, with the climate change, the climatic conditions during the growth and development of winter wheat in Jiangsu have a tendency of going against the increase of the number of spikes. Due to the above two reasons which are superimposed, with the climate change, Jiangsus climatic conditions are more unfavorable for the increase of the number of effective spikes. Therefore, how to achieve enough spikes by properly adjusting the seeding rate, transforming from the current cultivation mode that determines the number of effective spikes by the number of effective tillers to the cultivation mode that determines the number of effective spikes by the number of basic seedlings and the number of effective tillers and changing the fertilizer and water control and other cultivation measures has become a subject that Jiangsu winter wheat production must face in response to climate change. (3) The trend of climate change is a longterm sequence of events, and the annual output of winter wheat is mainly determined under coordination of the growth and development of winter wheat with temperature, light and water. Therefore, the effective measure for wheat production science to cope with climate change is to establish a business system that monitors the growth dynamics of winter wheat in real time, timely assesses the impact of meteorological conditions on winter wheat production and carries out artificial irrigation to adjust the local microclimate during specific growth process, so as to make the meteorological conditions of the year suitable for the growth and development of winter wheat, that is, to reduce the impact of climate change on winter wheat production, maintain the dynamic balance between winter wheat growth period and growth, and achieve high yield and quality of winter wheat finally.
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