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Using an Integrated Response-Function Method to Explore Agro-Climatic Suitability for Spring Soybean Growth in North China YINGBIN HE, YANMIN YAO, HUAJUN TANG, YOUQI CHEN, JIANPING LI, PENG YANG, ZHONGXIN CHEN, XIAOPING XIN, LIMIN WANG, DANDAN LI, AND HUI DENG Key Laboratory of Resources Remote Sensing and Digital Agriculture of Chinese Ministry of Agriculture/Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China (Manuscript received 8 June 2010, in final form 9 December 2010) ABSTRACT To understand agro-climatic suitability for spring soybean growth in north China, an integrated cropresponse-function method was developed. This method includes crop-response functions for temperature, precipitation, and sunshine and is assessed by a weighting method based on the coefficient of determination. The results show that the most suitable area (S1) for spring soybean growth occupied approximately 21.35% of the total area of north China. Among three types of spring soybeans of early maturity, middle maturity, and late maturity, middle maturity was the most suitable variety to grow in the study area, covering nearly 1.133 3 106 km2 or about 99.75% of the total area of S1. As a result of this study, the authors suggest that breeders pay more attention to middle-maturity cultivars in north China. The findings from this study may provide useful information for policy makers issuing guidelines for agricultural production.

1. Introduction China is the fourth major soybean producer in the world after United States, Brazil, and Argentina. In the recent 30 years, the total production of soybean has been steadily increasing to reach approximately 16 million tons. Spring soybeans, which are an important crop in north China, account for more than two-thirds of the total area and quantity of soybeans grown across the nation (Kou and Feng 2008, 4–6). Until now, published research on the effects of climatic factors on soybeans concentrated on the response of soybean growth and final yield to climatic factors (Sinclair and Rawlins 1993; Lal et al. 1999; Bhatia et al. 2008). However, to guide agricultural production, some countries have introduced agro-climatic crop regionalization aiming at avoiding low-efficiency crops cultivation (Brown and Chapman 1960a,b, 1961; Nuttonson

Corresponding author address: Huajun Tang, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Zhongguancun South Avenue 12, Beijing 100081, China. E-mail: [email protected] DOI: 10.1175/2010JAMC2577.1 Ó 2011 American Meteorological Society

1965; Li 1987). The regionalization was based on identification of agro-climatic suitability (Ogunkun 1993; Satyavathi and Reddy 2004; Yang et al. 2010). Some studies related to agro-climatic suitability for crops, especially for soybeans, showed methods based on analysis of data for the whole life cycles of crops. Since crop growth and yield are largely determined by weather during the growing season, even minor deviations from the usual weather pattern in any growing phase will lead to a reduction in the efficiency of externally applied inputs and thus to yield reduction (Mall et al. 2004). In addition, response functions of single climatic factor developed for detecting crop agro-climatic suitability need to be integrated (Cutforth and Shaykewich 1990; Zhao et al. 2003; Wei et al. 2007). In light of the increasing concerns, this study seeks to achieve three objectives: 1) to develop an integrated crop-response-function method to evaluate agro-climatic suitability for spring soybean growth in north China; 2) to map agro-climatic suitability for spring soybean growth at a large geographic scale; 3) to provide the methodological basis for future study on the effect of climate change on agro-climatic suitability for spring soybeans.

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FIG. 1. The map of the study area.

2. Materials and method a. Study area In terms of agro-climatic thresholds for spring soybean growth ($108C annual activated accumulated temperature ranging between 19008 and 40008C, total annual precipitation ranging between 200 and 1200 mm, and total annual day light duration between 2300 and 3100 h) (Kou and Feng 2008, 4–6), the study area covers the whole of north China. It includes 12 provinces and two municipalities (see Fig. 1), extending from latitude 318469 to 538429 and from longitude 738289 to 1348559with an area of approximately 5.3 million km2. The climate varies gradually from subhumid and warm temperate in the Huanghuaihai Plain to subarid, arid, and cold temperate in the north. A single-cropping system of spring soybean prevails in the study area.

the duration of the life cycles for the three types, phenological changes provided from field observations are shown in Table 1 (Pan et al. 1982; Yan et al. 2008; Yang and Yang 2009).

c. Method description 1) CROP-RESPONSE FUNCTIONS Temperature, precipitation, and sunshine are the three most important climatic factors that affect crop growth (Peart et al. 1989; Hanks and Ritchie 1991). To calculate agro-climatic suitability of spring soybean in north China, the authors applied crop-response functions of temperature, precipitation, and sunshine as follows.

(i) Temperature The relationship between agro-climatic suitability of spring soybeans and temperature is shown using

b. Phenology of spring soybeans in north China There are many spring soybean varieties that are grown in north China in response to environmental- and economic-benefit drivers. The reason the authors selected north China to be the study area is that the physiological and phenological characteristics of spring soybean in north China are very similar (Qiu and Wang 2007, 3–6). Though there are different kinds of spring soybean varieties, all the varieties could be classified into early maturity, middle maturity, and late maturity in terms of cultivation calendar (Ding 1959; Li and Chang 1998). The life cycle of spring soybeans is composed of five important phases, see Table 1 (Qiu et al. 2009). To compare

S(Ti ) 5

[(Ti [(Ti0

Ti1)(Ti2 Ti1)(Ti2

Ti )Bi ] Bi

Ti ) ]

, with

Bi 5

(Ti2 (Ti0

Ti0 ) , Ti1 ) (1)

where S(Ti) is agro-climatic suitability related to temperature for the i life cycle phase of spring soybeans, ranging between 0 and 1; Ti refers to averaged temperature in the i life cycle phase; Ti1, Ti2, and Ti0 are minimum threshold temperature, maximum threshold temperature, and most suitable temperature for spring soybean growth in the i phase, respectively; and Bi is a intermediate variable (Cutforth and Shaykewich 1990; Ma 1996).

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TABLE 1. Phenological phases and their duration for the three types of spring soybeans grown in north China. Phase Emergence Seedling growth Flower bud differentiation Flowering and pods formation Pod filling and maturity Type

Period

Early maturity Middle maturity Late maturity

1–10 May 1–10 May 1–10 May

11 May–2 Jun 11 May–2 Jun 11 May–2 Jun

3–22 Jun 3 Jun–2 Jul 3 Jun–12 Jul

23 Jun–4 Jul 3–14 Jul 13–24 Jul

5 Jul–3 Aug 15 Jul–18 Aug 25 Jul–2 Sep

12 12 12

30 35 40

Duration (days) Early maturity Middle maturity Late maturity

10 10 10

23 23 23

20 30 40

(ii) Precipitation The relationship between agro-climatic suitability of spring soybeans and precipitation is shown using 8 P > > > i > > P > < il S(Pi ) 5 1 > > > Pih > > > :P i

Pi , Pil Pil # Pi # Pih ,

(2)

Pi . Pih

where S(Pi) is agro-climatic suitability related to precipitation for the i life cycle phase of spring soybeans, ranging between 0 and 1; Pi is the averaged precipitation in the i life cycle phase; and Pi1 and Pih are minimum threshold of suitable precipitation and maximum threshold of suitable precipitation in the i phase, respectively (Xu et al. 2000; Zhao et al. 2003).

usually makes different contributions to the final output (Qian et al. 2004). Therefore, it is necessary to weight them. In this article, the weighting method based on the coefficient of determination (R2) was applied to calculate weighting values (Collins et al. 2001; Wei et al. 2007). We established linear regressions between the averaged agro-climatic suitability of temperature, precipitation, and sunshine for the different phenological phases and the averaged yield per area unit in a given region of the study area, then calculated the coefficients of determination (R2). The weighting value for a single climatic factor in a given phenological phase was the percentage of coefficient of determination for this climatic factor in the sum of coefficients of determination for the climatic factors in all the phenological phases, ati 5

(iii) Sunshine The relationship between agro-climatic suitability of spring soybeans and sunshine is shown using ( e S(Si ) 5 1

[(Si Si0 )/bi ]2

Si , Si0 , Si $ Si0

(3)

where S(Si) is agro-climatic suitability related to sunshine for the i life cycle phase of spring soybeans, ranging between 0 and 1; Si is the averaged sunshine in the i life cycle phase; Si0 is the most suitable sunshine duration in the i phase; and bi is constant in the i phase (Huang 1996).

m

,

(4)

åi åt R2ti

where ati refers to weighting value for climatic factor t (temperature, precipitation, or sunshine) in the i life cycle phase; R2ti is the coefficient of determination for climatic factor t in the i life cycle phase; n represents the total number of phenological phases in the life cycle of spring soybeans; and m is the total number of climatic factors (Wei et al. 2007).

3) AGRO-CLIMATIC SUITABILITY FOR THE WHOLE LIFE CYCLE OF SPRING SOYBEANS

Based on the Eqs. (1)–(4), agro-climatic suitability for a type of spring soybean for the whole life cycle was calculated using

2) THE WEIGHTING METHOD The agro-climatic suitability for the whole life cycle of spring soybeans was determined by the climatic suitability of temperature, precipitation, and sunshine in the different phenological phases of the crop. Moreover, climatic suitability for each of the phenological phases

R2ti n

n

Sc 5

m

åi åt ati 3 Sti,

(5)

where Sc refers to agro-climatic suitability of a type of spring soybean (early maturity, middle maturity, or late maturity) for the whole life cycle (with values that range

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FIG. 2. Location of weather stations in the study area.

between 0 and 1) and Sti is agro-climatic suitability related to a climatic factor t in the i life cycle phase. Since spring soybean in north China is usually a singlecropping variety, different types of early maturity, middle maturity, and late maturity are incompatible in cultivation date at a site. Thus, the authors selected the variety with the highest suitability to be the final output to guide agricultural production. The agro-climatic suitability for the whole life cycle of spring soybean was calculated using S 5 max(Sc ),

(6)

where S is agro-climatic suitability for the whole life cycle of spring soybean, with values that range between 0 and 1. The authors applied geometrical interval method to rank agro-climatic suitability S into five grades: S1 (very suitable), S2 (suitable), M (middle level), U1 (unsuitable), and U2 (very unsuitable).

d. Data collection and processing 1) DATA COLLECTION All the meteorological data used in this study were acquired from 341 standard weather stations located in the study area and belonging to the China Meteorological Administration (see Fig. 2). These data were the averaged daily values for the period 1971–2000. The data of yield per area unit for spring soybeans were obtained from the China Statistics Bureau. The statistical data were the averaged annual values for the period 1991–2000. Because the availability of per area yield

data is restricted, the weather data for the same period 1991–2000 were used when developing linear regressions between the averaged agro-climatic suitability of temperature, precipitation, and sunshine for the different phenological phases and the averaged yield per area unit in a given region of the study area. The parameters needed for Eqs. (1)–(3) are mainly subject to climatic conditions, but not constrained to physiological characteristics. In other words, parameters taken from the literature could represent spring soybean for the whole study area. These parameters could be found in the relevant publications (Huang 1996; Cao and Zhang 2000; Yang and Yang 2009).

2) DATA PROCESSING The original data of temperature, precipitation, and sunshine that were obtained from the weather stations had been recorded on a daily basis. The phenological phases (see Table 1) were matched by the averaged recorded values of the three climatic factors during the life cycle of the soybeans. The weather data were interpolated within 1 km 3 1 km grids using a kriging function in ArcGIS software. Subsequently, agro-climatic suitability in the different life cycle phases was calculated using Eqs. (1)–(3). However, the climatic observation sites in Xinjiang Province and Qinghai Province are relatively too few to be used for kriging interpolation. Thus, the authors applied the method ‘‘linear regression 1 spatial residual,’’ which was implemented to study especially in the two provinces mentioned above, to calculate temperature

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TABLE 2. Weighting values for early maturity, middle maturity, and late maturity. Climatic factor

Precipitation

Temperature

Weighting value Weighting value Weighting value Weighting value

1–10 May 0.108 11 May–2 Jun 0.058 3–22 Jun 0.027 23 Jun–4 Jul 0.01 5 Jul–3 Aug 0.132

Class

Description

Value

0.06

0.235

0.048

0.118

S1 S2 M U1 U2

Most suitable Suitable Middle level Unsuitable Most unsuitable

0.9 # S , 1 0.86 # S , 0.9 0.82 # S , 0.86 0.72 # S , 0.82 0 # S , 0.72

0.002

0.004

0.086

0.002

0.088

0.022

0.047

0.189

0.038

0.095

0.022

0.003

0.077

0.002

0.087

0.162

0.038

0.150

0.031

0.076

0.022

0.002

0.051

0

0.069

0.177

Middle maturity Weighting value Weighting value Weighting value Weighting value Weighting value

1–10 May 0.087 11 May–2 Jun 0.049 3 Jun–2 Jul 0.054 3–14 Jul 0.001 15 Jul–18 Aug 0.087 Late maturity

Weighting value Weighting value Weighting value Weighting value Weighting value

1–10 May 0.070 11 May–2 Jun 0.038 3 Jun–12 Jul 0.024 13–24 Jul 0.172 25 Jul–2 Sep 0.078

TABLE 3. Classes of agro-climatic suitability for spring soybean growth in north China.

Sunshine

Early maturity Weighting value

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values (Zhong 2007). The method first analyzed the correlation between the averaged annual temperature for the period 1971–2000 and longitude, latitude, and altitude. The R2 was excellent with a value of 0.897. The residue, which is the difference value of actual temperature value to the calculated value by linear regression, could be interpolated with 1 km 3 1 km grids. For each 1 km 3 1 km grid, the averaged annual temperature value was equal to the sum of the calculated value by linear regression and residue. The validation results indicated that the R2 was 0.994 and the average error was 1.53%, which means that the method was very suitable for temperature calculation in the region. For precipitation, the authors adopted a similar method of ‘‘linear regression 1 spatial regression.’’ The little difference between precipitation and temperature during the operation was that consideration of slope was present in the linear regression (Zhou et al. 2006).

The authors processed spring soybean yield (kg ha21) obtained in the counties where the 341 climatic stations were located to calculate the mean agro-climatic suitability within the boundaries of these counties. Ultimately, weighting values were calculated using Eq. (4) and the final results showing agro-climatic suitability of various regions of north China could be determined using Eqs. (5) and (6). The weighting values are shown in Table 2.

3. Results and discussion a. Agro-climatic suitability for spring soybean growth The grading for agro-climatic suitability is in Table 3. The calculated mean value of the agro-climatic suitability of spring soybean growth for the whole study area is 0.83. This value indicates that the whole study area is positioned in the M (middle level) of the agro-climatic suitability scale for spring soybean growth (see Table 3). The most suitable area (S1) with an area of nearly 1.14 3 106 km2, occupying 21.35% of the total area of north China, is situated in the eastern parts of Xinjiang; the western and eastern parts of Inner Mongolia; the small northern parts of Ningxia; the small eastern parts of Shaanxi; the southern parts of Shanxi, Hebei, Beijing, and Tianjin; and the western parts of Liaoning and Jilin (see Fig. 3). The most unsuitable area (U2) was found to be only in Qinghai and a very small patch in Gansu, with an area of nearly 12% of the total area of north China. The areas of S2, M, and U1 occupied 20.62%, 22.49%, and 23.54% of the total area, respectively. It is obvious that the spatial distribution of agro-climatic suitability classes of spring soybean growth generally does not match the administrative boundaries (see Fig. 3). The very suitable area (S1) and suitable area (S2) areas are mostly situated in the plains (e.g., the Songnen Plain in northeast China), whereas the very unsuitable areas are mainly located in high-elevation regions (e.g., the Qinghai Plateau in the boundary of Qinghai Province). Precipitation greatly affects spatial distribution of agro-climatic suitability for spring soybean growth. The reason that the eastern parts of Xinjiang Province were

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FIG. 3. Climatic suitability ranking for spring soybean growth.

most suitable for soybean growth in an agricultural climate is that precipitation has been significantly increasing since the 1980s. In summary, latitude, altitude, and elevation determine the distribution of temperature and moisture that are crucial for spring soybean growth. An interesting observation was made in the Sanjiang Plain, located in the easternmost part of north China. It is well known that soybean is sensitive to day length. Insufficient sunshine in three of the five phenological phases— namely the first, second, and fifth—greatly affected the

crop yield. In recent years, the total soybean production in this region had been decreasing and climatic factors were among the reasons leading to the result.

b. The contributions of early, middle, and late maturity to total production of soybeans According to Fig. 4, among the three types of spring soybean in the study area, the variety of middle maturity was the main component to the final output mentioned above; meanwhile it occupied nearly 1.133 3 106 km2,

FIG. 4. Climatic suitability for spring soybeans.

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accounting for 99.76% of the total area of S1. In fact, in the most important soybean production areas in north China such as northeast China, the most popular spring soybean variety is the middle maturity. In addition, the area suitable for early maturity is approximately 2865 km2, which only accounts for about 0.24% of the total area of S1. The area under late maturity is none. When autumn falls in north China, the possibility of low temperature and frost dramatically increases. The low temperature and frost have very significant unfavorable effects on the soybean late-maturity variety. In fact, the soybean cultivation suitability involves not only natural factors such as climate, soil, hydrology, and topography, but also socioeconomic ones such as irrigation, road accessibility, and farmers’ inclination. Climatic factors, which are key to crop cultivation—to some extent they are the most important factors that determine the spatial distribution of soybean—are usually simplified by only using annually averaged temperature or annually accumulated temperature for the whole life cycle of a crop. The method could not effectively and precisely measure the effects of climatic factors on soybean growth in the different phases of life cycle. Moreover, crops are usually divided into different varieties in terms of phenology, for instance, early maturity, middle maturity, and late maturity. When applying response function, if we do not consider varieties subject to growth date of soybeans, results were also not accurate. Thus, we integrated the response functions of single climatic factor to detect crop agro-climatic suitability, which mainly aimed to guide agro-climatic regionalization for soybean. The authors suggest that breeders pay more attention to middle-maturity cultivars in north China. This paper will provide a reference for cultivation suitability for soybean, even extending to other crops based on a comprehensive index system containing natural factors and socioeconomic factors.

4. Conclusions An integrated crop-response-function method used in this study has been able to demonstrate the agro-climatic suitability of north China for spring soybean cultivation. The findings of this study show that the Songnen Plain in northeast China; the eastern parts of Xinjiang Province; the eastern and western parts of Inner Mongolia; and the southern parts of Shanxi Province, Hebei Province, Beijing, and Tianjin are the most suitable for spring soybean growth, and that the middle-maturity types are most suitable cultivars in north China. The findings of this study are expected to be useful for policy makers in charge of planning agricultural production.

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Acknowledgments. The authors express sincere appreciation to Dr. George Srzednicki, scientist in land use, for his great help in revising and polishing this paper. This research was funded by the National Program on Key Basic Research Project (973 Program, 2010CB951501-2), the Key Program of National Natural Science Foundation of China (40930101), the National Basic Research Priorities Program of China (2007FY120100), the National Natural Science Foundation of China (41001049), the Key Laboratory of Resources Remote Sensing and Digital Agriculture of Chinese Ministry of Agriculture (RDA0910), the Major Program of National Natural Science Foundation of China, the Commonweal Foundation of China’s National Academy (2010002-2), the Key International Cooperation Program of China’s Ministry of Science and Technology (2010DFB10030), and the National Program on Key Basic Research Project (973 Program, 2007CB106806).

REFERENCES Bhatia, V. S., S. Piara, S. P. Wani, G. S. Chauhan, A. V. R. Kesava Rao, A. K. Mishra, and K. Srinivas, 2008: Analysis of potential yields and yield gaps of rainfed soybean in India using CROPGRO-Soybean model. Agric. For. Meteor., 148, 1252– 1265. Brown, D. M., and L. J. Chapman, 1960a: Soybean ecology. I. Development–temperature relationships from controlled environment studies 1. Agron. J., 52, 493–496. ——, and ——, 1960b: Soybean ecology. II. Development– temperature–moisture relationships from field studies. Agron. J., 52, 496–499. ——, and ——, 1961: Soybean ecology. III. Soybean development units for zones and varieties in the Great Lakes region 1. Agron. J., 53, 306–308. Cao, X., and X. H. Zhang, 2000: Correlation analysis between climate factors and major characters of different types of soybean growth period (in Chinese). J. Shanxi Agric. Sci., 28, 31–34. Collins, M. G., F. R. Steiner, and M. J. Rushman, 2001: Land-use suitability analysis in the United States: Historical development and promising technological achievements. Environ. Manage., 28, 611–621. Cutforth, H. W., and C. F. Shaykewich, 1990: A temperature response functions for corn development. Agric. For. Meteor., 50, 159–171. Ding, Z. L., 1959: Studies on the bioclimatic adaptation of soybean in China (in Chinese). Acta Agric. Zhejiangensis, 4, 39–53. Hanks, J., and J. T. Ritchie, Eds., 1991: Modeling Plant and Soil Systems. American Society of Agronomy, 545 pp. Huang, H., 1996: Climatic ecological adaptability of the crop production in the red and yellow soil region of China (in Chinese). J. Nat. Res., 11, 341–346. Kou, J. P., and K. S. Feng, 2008: High-Quality Special Soybean Variety and High-Productive Cultivar Technology (in Chinese). China Agriculture Press, 298 pp. Lal, M., K. K. Singh, G. Srinivasan, L. S. Rathore, D. Naidu, and C. N. Tripathi, 1999: Growth and yield response of soybean in

JUNE 2011

HE ET AL.

Madhya Pradesh, India, to climate variability and change. Agric. For. Meteor., 93, 53–70. Li, S. K., 1987: Agro-climatic regionalization of China (in Chinese). J. Nat. Res., 2, 71–83. Li, X. H., and R. Z. Chang, 1998: Cluster and principal component analysis of the spring soybean varieties in China. Acta Agron. Sin., 24, 325–332. Ma, S. Q., 1996: A simulating study on the influences of climate change on grain yield and the countermeasures in the northeast China (in Chinese). Acta Meteor. Sin., 54, 484–492. Mall, R. K., M. Lal, V. S. Bhatia, L. S. Rathore, and S. Ranjeet, 2004: Mitigating climate change impact on soybean productivity in India: A simulation study. Agric. For. Meteor., 112, 113–125. Nuttonson, M. Y., 1965: Rice Culture and Rice-Climate Relationships: With Special Reference to the United States Rice Areas and Their Latitudinal and Thermal Analogues in Other Countries. American Institute of Crop Ecology, 555 pp. Ogunkun, L. A., 1993: Soil and land suitability evaluation an example with oil palm in Nigeria. Soil Use Manage., 9, 35–40. Pan, T. F., D. R. Zhang, W. G. Zhang, and Z. R. Li, 1982: Study on climatic biology of soybean in northeast China (in Chinese). Soybean Sci., 1, 17–28. Peart, R. M., J. W. Jones, R. B. Curry, K. Boote, and L. H. Allen, 1989: The potential effects of global climatic change on the United States. Report to Congress. U.S. EPA, 401 pp. Qian, H. S., S. X. Jiao, and F. Zhao, 2004: Influence of global climate change on climatic suitability of crop: a case of crop in Henan Province (in Chinese). Res. Agric. Mod., 25, 106–110. Qiu, L. J., and S. M. Wang, 2007: Soybean Variety in China (in Chinese). China Agriculture Science and Technology Press, 525 pp. Qiu, Q., X. Y. Yan, W. Zhang, M. H. Zhang, X. J. Yan, S. Q. Gao, and L. C. Dong, 2009: Studies on adaptability of spring soybean

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varieties in middle-late-maturity soybean area of north China (in Chinese). Jilin Agric. Sci., 34, 4–6. Satyavathi, P. L. A., and M. S. Reddy, 2004: Soil site suitability for six major crops in Telangana Region of Andhra Pradesh. J. Indian Soc. Soil Sci., 52, 220–225. Sinclair, T. R., and S. L. Rawlins, 1993: Interseasonal variation in soybean and maize yields under global environmental change. Agron. J., 85, 406–409. Wei, R. J., W. Z. Zhang, X. Y. Kang, and Z. Q. Dong, 2007: Application and establishment of climatic suitability dynamic model of crop in Hebei Province (in Chinese). Agric. Res., 25, 5–15. Xu, X. X., P. Gao, and D. S. Jiang, 2000: Fuzzy analysis on the suitability of precipitation to the agro2crop growing in Yanan City (in Chinese). Res. Soil Water Conserv., 7, 73–76. Yan, Q., J. H. Xu, and G. D. Chen, 2008: A study on the spatial relationship between agricultural land use intensity and agroclimatic suitability in China (in Chinese). Ecol. Sci., 27, 107–113. Yang, X. F., and D. G. Yang, 2009: Establish climatic adaptability index system for spring soybean (in Chinese). Acad. Field, 11, 36–38. ——, ——, Y. H. Tang, and Z. H. Wang, 2010: Changes of effective accumulated temperature and ecological suitability of soybean in Heilongjiang Province (in Chinese). Crops, 2, 62–65. Zhao, F., H. S. Qian, and S. X. Jiao, 2003: The climatic suitability model of crop: A case study of winter wheat in Henan Province (in Chinese). Res. Sci., 25, 77–82. Zhong, J. L., 2007: Method of spatial interpolation of air temperature based on GIS and RS in Xinjiang (in Chinese). Des. Oas. Meteor., 1, 33–35. Zhou, S. Q., G. Y. Xue, L. F. Zhou, Q. Sun, and N. Kang, 2006: The interpolation approach of precipitation for spatial analysis based on GIS (in Chinese). Acta Meteor. Sin., 64, 101–111.