CN113111311A - Screening method for wheat yield influence factors in region along Huaihe river - Google Patents
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Abstract
The invention relates to the technical field of agriculture, in particular to a screening method of wheat yield influence factors along a Huai-nationality area, which aims at obtaining precipitation factors, temperature factors, sunshine factors and wheat yield data of corresponding years along the Huai-nationality area so as to obtain correlation coefficients of the wheat yield of the corresponding years and the precipitation factors, the temperature factors and the sunshine factors, and screening the influence factors with the highest correlation coefficients according to correlation analysis results.
Description
Technical Field
The invention relates to the technical field of agriculture, in particular to a screening method of wheat yield influence factors in Huaihe district.
Background
In recent years, climate warming has become an important issue of close concern to global scientists and the public. The climate warming of China is characterized in that the temperature rise in winter and spring is obviously higher than that in summer and autumn, and the temperature rise at night is higher than that in the daytime. In recent 50 years, the average temperature of the earth surface in China rises by 1.1 ℃, which is higher than the average temperature rise range in the same period of the whole world, and the temperature is expected to rise by 1.2-2.0 ℃ again in 2050, and the temperature rise reaches 2.2-4.2 ℃ in 2100 years. Wheat is staple food of the second crop and nearly half of the population in the world, plays an important role in food safety in China, and temperature is one of important influence factors influencing the yield and quality of wheat. Many efforts have been made to counteract the effects of climate warming on wheat production. The Easterling and Miglietta researches show that the climate warming can reduce the yield of main crops in China, when the temperature rises to exceed 1 ℃, the yield of wheat begins to decrease, and when the temperature rises to exceed 3 ℃, the yield is about 20 percent lower. Research on the variegated bell shows that the climate warming changes the growth process of crops in China, shortens the growth period of overwintering crops such as winter wheat and the like, prolongs the growth period of warm-favored crops, has obvious influence on resources, agricultural production and environment by global warming, is extremely sensitive to the response of the agricultural production to climate change, and can change the farming period, the crop development period, the crop planting structure and the like by the climate change, so the research on the influence of the climate change on the grain yield has extremely important significance.
Anhui province is located in the east and west regions of China and in transition regions of warm temperate zones and subtropical zones, the wheat yield is very sensitive to climate change, and the climate has obvious influence on the wheat yield. The Anhui province is rich in warm and light resources along the Huai region, is an important grain production base of the Anhui province, mainly uses rice and wheat double cropping, plays a vital role in guaranteeing grain production in China, and global warming can lead to stable weakening of climate and reduce the capability of agricultural adaptation change, so that the threat of extreme weather on wheat growth and harvest is increased day by day, and even the safety production of wheat is seriously influenced.
In view of the above-mentioned drawbacks, the inventors of the present invention have finally obtained the present invention through a long period of research and practice.
Disclosure of Invention
The invention aims to solve the problems of how to screen the climate influencing factors of the wheat yield along the Huai region, scientifically utilize climate resources and reasonably arrange agricultural production, and provides a screening method of the climate influencing factors of the wheat yield along the Huai region.
In order to achieve the purpose, the invention discloses a method for screening climate influence factors of wheat yield along a Huai region, which comprises the following steps:
s1: acquiring precipitation factors of corresponding years according to the district along the Huai river;
s2: acquiring temperature factors of corresponding years for regions along the Huai river;
s3: acquiring sunshine factors of corresponding years for regions along the Huai river;
s4: acquiring wheat yield data of corresponding year in a region along the Huai river;
s5: obtaining the correlation coefficients of the wheat yield and the precipitation factor, the temperature factor and the sunshine factor in the corresponding year;
s6: from the correlation analysis result obtained in step S5, the influence factor having the highest correlation coefficient is selected.
The precipitation factor in the step S1 comprises annual precipitation, idle precipitation, wheat growth precipitation, winter precipitation and precipitation after winter.
The temperature factors in the step S2 include daily average temperature, pre-winter accumulated temperature, accumulated temperature of more than or equal to 0 ℃ in the wintering period, accumulated temperature in the wintering period and average temperature after wintering.
The sunshine factors in the step S3 include annual sunshine hours, sunshine hours before winter, winter sunshine hours, and grouting sunshine hours.
The corresponding year in the steps S1, S2, S3 and S4 is 1997-2017.
In the steps S1, S2, S3 and S4, the area along the Huai-nationality region includes Fengtai county, Funan county, Guzhen county, Huaiyuan county, Yingshang county and Shou county.
The method for obtaining the correlation coefficient in step S5 is to perform bivariate correlation analysis in SPSS software.
Compared with the prior art, the invention has the beneficial effects that: according to the method, meteorological data of rainfall, air temperature and sunshine hours in 1998-2017 years in the Anhui province along the Huai region are utilized to analyze and research the climate change trend of the region, the climate change characteristics of the wheat in the key growth period and the influence of the climate change characteristics on the wheat yield, so that the climate influence factors of the wheat yield in the region along the Huai region are screened, the scientific and reasonable response to climate change along the Huai region is facilitated, the influence of meteorological disasters on the wheat along the Huai region is reduced, and a theoretical basis is provided for the stable-yield and high-yield cultivation of the wheat in the region.
Drawings
FIG. 1 shows annual precipitation of Anhui province along Huai district 1997-2017;
FIG. 2 shows the precipitation amount of wheat in the growth period of 1997-2017 along the Huai district of Anhui province;
FIG. 3 shows the amount of precipitation in the wheat leisure period in Anhui province along Huai district 1997-2017;
FIG. 4 shows the temperature equalization in 1997-2017 days along Huai district of Anhui province;
FIG. 5 shows the highest temperature in 1997-2017 in the region of Huai district of Anhui province;
FIG. 6 shows the lowest temperature of Anhui province along the Huai district in 1997-2017 years;
FIG. 7 shows the accumulated temperature before winter in the area 1997-2017 along Huai of Anhui province;
FIG. 8 shows the accumulated temperature of Anhui province in 1997-2017 in vigorous growth and development period along Huai district;
FIG. 9 shows the daily temperature equalization in the growth and development period of Anhui province along Huai district 1997-2017;
FIG. 10 shows the annual sunshine hours 1997-2017 in the Huai district of Anhui province;
FIG. 11 shows the number of days before winter in 1997-2017 along Huai district of Anhui province;
FIG. 12 shows the number of sunshine hours in the winter season in 1997-2017 along the Huai district of Anhui province;
FIG. 13 shows the number of sunshine hours after overwintering in the area 1997-2017 along Huai district of Anhui province;
FIG. 14 is the average annual wheat yield in Anhui province along Huai district.
Detailed Description
The above and further features and advantages of the present invention are described in more detail below with reference to the accompanying drawings.
The meteorological data is from the gas image bureau of Anhui province, and comprises data of daily precipitation, average temperature, minimum temperature, maximum temperature and sunshine hours from 1998 to 2017 in 6 places of Fengtai county, Funan county, Guzhen county, Huaiyuan county, Yingshangxian county and Shou county of Anhui province along Huai district. According to the data, the wheat leisure period (6 months 1-9 months 30 days), the growth period (10 months 1-next year 5 months 31 days) and the precipitation amount of the whole year (6 months 1-next year 5 months 31 days) along the Huaihu province, the annual average air temperature and the annual sunshine hours, the accumulated temperature and the sunshine hours before wintering (seeding till the daily average air temperature 5d is stabilized at 0 ℃), the winter average temperature, the sunshine hours and the accumulated temperature of more than or equal to 0 ℃ are calculated, the annual probability of the accumulated temperature of more than or equal to 600 ℃, more than or equal to 650 ℃ and more than or equal to 750 ℃ before wintering is calculated, 1998-2017 years are divided into 4 stages of 1998-2002, 2003-2007, 2008-2012 and 2013-2017 years according to one stage of 5 years, and the air temperature, the sunlight hours and the sunshine hours in different stages are calculated. The yield data was from agriculture and committee of Anhui province.
The precipitation year type is divided by adopting the domestic more common precipitation year type division standard.
And (4) water-enriching year: pi > P +0.33 delta
In dry water: pi < P-0.33 delta
In the formula, Pi is the precipitation (mm) in the current year; p is the average precipitation (mm) for many years; delta is the mean square error (mm) of the precipitation for many years.
First, annual precipitation, precipitation type and precipitation change in growth period of wheat
1. Variation of precipitation between years
Annual precipitation, growth period precipitation and leisure period precipitation along the Huai region are shown in figures 1-3, and it can be seen from the figures that annual fluctuation of the precipitation is large in the Anhui region along the Huai region for nearly 20 years, and the annual precipitation generally tends to increase from 2010. Wherein the annual average precipitation is 966.6mm, the annual maximum precipitation is 1396.1mm (2017 years), and the annual minimum precipitation is 662.5mm (1999 years); the average precipitation amount of the wheat in the idle period (6-9 months) is 595.1mm, the highest precipitation amount is 978.0mm (2003), and the lowest precipitation amount is 225.2mm (2001); the average precipitation amount of the wheat in the growth period (10-5 months) is 370.6mm, the highest precipitation amount is 658.2mm (2017 years), and the lowest precipitation amount is 149.9mm (2010 years). The annual precipitation variation coefficients of the wheat at the leisure period and the growth period are 23.0%, 31.4% and 30.0% respectively, which indicates that the fluctuation of the precipitation at the leisure period of the wheat is large.
2. Variation of precipitation at different time intervals
Divide Anhui province into 5 main time quantums along Huai district one year: 6-7 months, in the early period of leisure; 8-9 months, and in the later leisure period; 1 to 12 months and 10 days in 10 months, and in the early winter; 12 months and 10 days to 3 months and 1 day, and a wintering period; 3, 1-5, 20 days, and the growth and development are vigorous.
TABLE 1 precipitation (mm) in wheat growth period and leisure period
| Point in time | 1998～2002 | 2003～2007 | 2008～2012 | 2013～2017 |
| 6 to 7 months | 366.24 | 519.01 | 288.79 | 304.03 |
| 8-9 months | 163.62 | 234.85 | 230.10 | 277.03 |
| 10 to 12 months | 120.98 | 87.48 | 71.36 | 157.26 |
| 12-3 months | 112.66 | 99.7 | 94.3 | 102.65 |
| 3-5 months | 154.36 | 161.92 | 157.26 | 154.56 |
| All year round | 917.86 | 1102.96 | 841.81 | 995.53 |
From the analysis of the table 1, the annual precipitation is mainly concentrated in 6-9 months of leisure time from 1998 to 2017, and accounts for 57.7% -68.3% of the annual precipitation. In general, the average precipitation in the leisure period and every 5 years all the year is in the trend of increasing, decreasing and increasing, wherein the precipitation is the highest between 2003-2007; the annual average precipitation change in the wintering period and the growth and development vigorous period is small; the average precipitation in the early winter is in a descending trend before 2008-2012, and is in an ascending trend after the period. Therefore, the increase in average precipitation in the late leisure period and the early winter period in nearly ten years may be the main cause of the increase in average precipitation throughout the year.
Second, the variation of annual average temperature and temperature during the growth period of wheat
1. Annual average temperature, annual average maximum temperature and annual average minimum temperature
The daily average temperature, the annual daily average maximum temperature and the minimum air temperature of the Anhui province along the Huai region are shown in figures 4-6, and it can be known from the figures that the annual average temperature, the annual daily average maximum temperature and the minimum air temperature change ranges of the Anhui province along the Huai region are respectively 15.09-16.45, 19.59-21.43 and 11.41-12.60 ℃ between 1998-2017, the maximum values are respectively 9.01%, 9.39% and 10.43% higher than the minimum values, the maximum values of the three indexes respectively appear in 2007, 2004 and 2007, the minimum values respectively appear in 2005, 2003 and 2003, and the minimum values respectively rise year by year at the rates of 0.0071, 0.0063 and 0.0108 ℃ per year. The annual average temperature, the annual average maximum temperature and the annual average minimum temperature coefficient of variation are respectively 2.07%, 1.89% and 2.47%, so that the annual average daily minimum temperature variation range is the largest, the annual average daily temperature variation range is in the middle, and the annual average daily temperature is increased year by year mainly due to the annual average daily minimum temperature increase.
2. Changes of pre-winter accumulated temperature, accumulated temperature in vigorous growth and development period and daily average temperature
The accumulated temperature in the early winter accumulated temperature growth and development vigorous period and the daily average temperature in the growth and development vigorous period in the Huai region of Anhui province are shown in figures 7-9, and it can be known from the figures that the variation ranges of the accumulated temperature in the early winter accumulated temperature, the accumulated temperature in the growth and development vigorous period and the daily average temperature in the Huai region of Anhui province are 525.3-759.3 ℃, 1063.1-1316.1 and 13.1-16.3 ℃ respectively, the maximum values of the three indexes respectively appear in 1998, 2017 and 2017, and the minimum values all appear in 2009 and respectively increase at the rates of 1.18, 3.15 and 0.04 ℃ per year.
The temperature accumulation before winter, the temperature accumulation during the growth and development vigorous period and the daily average temperature during the growth and development vigorous period in the region along Huai province of Anhui province are shown in Table 2:
TABLE 2 temperature and days of growth period of wheat in different time periods
| Point in time | 1998～2002 | 2003～2007 | 2008～2012 | 2013～2017 |
| Average daily temperature | 15.87 | 15.87 | 15.77 | 15.96 |
| Year probability that the accumulated temperature before winter is more than or equal to 600 DEG C | 60％ | 60％ | 60％ | 80％ |
| Year probability that the accumulated temperature before winter is more than or equal to 650 DEG C | 20％ | 60％ | 40％ | 60％ |
| Year probability that the accumulated temperature before winter is more than or equal to 750 DEG C | 20％ | 0 | 0 | 20％ |
| Accumulated temperature of more than or equal to 0 ℃ in the wintering period | 104.85 | 98.72 | 97.35 | 86.14 |
| Average temperature of winter | 2.313 | 1.481 | 1.495 | 1.955 |
| Days of wintering | 40.0 | 53.2 | 45.4 | 33.2 |
| Day-to-day average temperature in vigorous growth stage | 14.72 | 15.34 | 14.948 | 15.48 |
| Accumulated temperature during vigorous growth | 1192.01 | 1242.29 | 1209.92 | 1250.51 |
As can be seen from the analysis in Table 2, the difference of the daily average temperature is small between 1998 and 2007, the temperature is increased from 15.77 ℃ to 15.96 ℃ between 2008 to 2017, the probability of the pre-winter accumulated temperature being more than or equal to 600 ℃ per year is increased from 60% to 80% between 1998 and 2012, and the probability of the pre-winter accumulated temperature being more than or equal to 650 ℃ per year is increased from 20% between 1998 and 2002 to 60% between 2013 and 2017. The average temperature of the winter period day is divided into three stages, the maximum average temperature of the winter period day between 1998 and 2002 is 2.313 ℃, the average temperature of the winter period day between 2003 and 2012 is reduced, and the average temperature of the winter period day between 2013 and 2017 is increased. The number of days in the wintering period is increased firstly and then decreased, the longest duration time in the wintering period is 53.2 days in 2003-2007, and then the duration time is decreased rapidly, so that the number of days in the wintering period is obviously shortened in the last decade. The average daily temperature and accumulated temperature in the vigorous growth period are both in the trend of rising first, then falling and then rising, and the highest values are both in the years of 2013-2017 and are respectively 15.48 ℃ and 1250.51 ℃.
Third, change of sunshine duration
1. Annual variation in sunshine duration
As shown in the graphs of FIGS. 10-13, the sunshine duration in Huai region of Anhui province and the sunshine duration in wheat growth period are 1588.9-2141.4 h, average 1900.5h, highest value in 2013, lowest value in 1998, rising at a rate of 5.9h per year, and descending at 974.1-1467.6 h, average 1157.8 h. The change ranges of the sunshine hours before winter, in the winter period and after winter are respectively 216.1-473.8 h, 53.7-305.4 h and 486.4-740.8 h, wherein the sunshine hours before winter slowly increase at the rate of 0.08h per year, the sunshine hours in the winter period decrease at the rate of 3.01h per year, and the sunshine hours after winter increase at the rate of 1.59h per year, so that the sunshine hours in the winter period have great influence on the increase of the sunshine hours per year.
2. Change of sunshine hours in different time periods
The change of the sunshine hours of wheat in different time periods along the Huai district in Anhui province is shown in Table 3:
TABLE 3 variation of the number of hours of wheat sunshine in different periods of time
| Time period | 1998～2002 | 2003～2007 | 2008～2012 | 2013～2017 |
| All year round | 1826.9 | 1950.0 | 1911.7 | 1913.5 |
| Before winter | 310.8 | 294.7 | 302.1 | 321.5 |
| Winter season | 189.0 | 224.5 | 210.9 | 151.4 |
| After winter | 614.4 | 704.5 | 655.8 | 631.8 |
Correlation of wheat yield and climatic conditions
The average annual wheat yield along the Huai region between the years 2008 + 2017 is shown in fig. 14, and it can be known from the graph that the average annual wheat yield in the Huang-Huai region shows an increasing trend year by year, a decline occurs between the years 2009 + 2011, a gradual rise occurs between the years 2012 + 2017, and the yield level is relatively stable in the years 2013 + 2017.
The correlation coefficient of wheat yield to climatic conditions is shown in table 4:
TABLE 4 correlation coefficient of wheat yield with climate conditions
| Index (I) | r | Index (I) | r | Index (I) | r |
| Annual precipitation | 0.476 | Average daily temperature | 0.139 | Annual sunshine duration | -0.148 |
| Precipitation in leisure time | 0.146 | Accumulated temperature before winter | 0.386 | Number of days before winter | 0.093 |
| Precipitation of wheat in growth period | 0.628* | Accumulated temperature of more than or equal to 0 ℃ in the wintering period | 0.402 | Sunshine hours in winter | -0.700* |
| Precipitation before overwintering | 0.520 | Accumulated temperature in the winter season | 0.037 | Sunshine hours after winter | -0.251 |
| Precipitation after overwintering | 0.549 | Even temperature after overwintering | 0.396 | Sunshine hours in grouting period | -0.400 |
r0.05＝0.3551；r0.01＝0.4556
The analysis of the table 4 shows that the correlation between the precipitation and the yield of the wheat is the highest, wherein the correlation coefficient between the precipitation and the yield of the wheat in the growth period reaches a significant level; the temperature and the wheat yield are positively correlated, but not reach obvious level, the sunshine hours and the wheat yield are negatively correlated, wherein the correlation coefficient between the sunshine hours and the wheat yield in the winter period reaches obvious level. Therefore, the influence of precipitation in Anhui along Huai-nationality regions in the last 20 years on the yield of wheat grains is obvious, and the precipitation in the growth period of wheat is a key influence factor of the yield of wheat.
The foregoing is merely a preferred embodiment of the invention, which is intended to be illustrative and not limiting. It will be understood by those skilled in the art that various changes, modifications and equivalents may be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. A screening method of wheat yield influence factors in regions along Huaihe river is characterized by comprising the following steps:
s1: acquiring precipitation factors of corresponding years according to the district along the Huai river;
s2: acquiring temperature factors of corresponding years for regions along the Huai river;
s3: acquiring sunshine factors of corresponding years for regions along the Huai river;
s4: acquiring wheat yield data of corresponding year in a region along the Huai river;
s5: obtaining the correlation coefficients of the wheat yield and the precipitation factor, the temperature factor and the sunshine factor in the corresponding year;
s6: from the correlation analysis result obtained in step S5, the influence factor having the highest correlation coefficient is selected.
2. The method for screening wheat yield impact factors along Huaihe river district according to claim 1, wherein the precipitation factor in step S1 includes annual precipitation, idle precipitation, wheat growth precipitation, winter precipitation, and winter precipitation.
3. The method for screening wheat yield influencing factors along Huaihe district according to claim 1, wherein the temperature factors in step S2 include average daily temperature, accumulated temperature before winter, accumulated temperature greater than or equal to 0 ℃ during winter, accumulated temperature during winter and average temperature after winter.
4. The method as claimed in claim 1, wherein the sunshine factors in step S3 include annual sunshine duration, pre-winter sunshine duration, post-winter sunshine duration, and filling-in-season sunshine duration.
5. The method for screening wheat yield influencing factors along Huaihe district according to claim 1, wherein the corresponding years in the steps S1, S2, S3 and S4 are 1997-2017.
6. The method for screening wheat yield impact factors along Huai-regional areas according to claim 1, wherein the steps S1, S2, S3 and S4 include Fengtai county, Funan county, Guzhen county, Huaiyuan county, Yingshangxian county and Shou county along the Huai-regional areas.
7. The method for screening wheat yield influencing factors along Huaihe district according to claim 1, wherein the method for obtaining the correlation coefficient in step S5 is to perform bivariate correlation analysis in SPSS software.
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| CN113609453A (en) * | 2021-08-10 | 2021-11-05 | 中国科学院科技战略咨询研究院 | Quantitative monitoring method and device for influence of temperature rise on agriculture and fishery |
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