Crop Planting Structure Research Articles

Effects of Crop Planting Structure Adjustment on Water Use Efficiency in the Irrigation Area of Hei River Basin

The adjustment of crop planting structure can change the process of water and material circulation, and thus affect the total amount of water and evapotranspiration in the irrigation district. To guide the allocation of water resources in the region, it is beneficial to ascertain the effects of changing the crop planting structure on water saving and farmland water productivity in the irrigation district. This paper takes Yingke Irrigation District as the background. According to the continuous observation data from 2012 to 2013, Based on the modified Soil and Water Assessment Tool (SWAT) model and taking advantage of monthly scale remote sensing EvapoTranspiration (ET) and crop growth parameters (leaf area index and shoot dry matter), we tested the simulation accuracy of the model, proposed irrigation efficiency calculation methods considering water drainage, and established the scenario analysis method for the spatial distribution of crop planting structure. Finally, we evaluated the changes in water savings in irrigation district projects and resources, the irrigation water productivity and the net income water productivity under different planting structure scenarios. The results indicate that the efficiency of irrigation has increased by 15~20%, while considering drainage, as compared with conventional irrigation efficiency. Additionally, the adjustment of crop planting structure can reduce regional evapotranspiration by 14.9%, reduce the regional irrigation volume by 30%, and increase the net income of each regional water area by 16%.

Understanding Farmers’ Perceptions and Behaviors towards Farmland Quality Change in Northeast China: A Structural Equation Modeling Approach

Farmland protection is the most important land science research issue in developing countries, especially in China, due to serious land degradation. This paper aimed to reveal the causal chain among driving factors, farmers’ land protection perceptions, behavioral responses, and land quality change by applying a structural equation model (SEM), based on a cross-sectional dataset of 238 households surveyed, and matched plot soil sample results in the Sujiatun District, in Liaoning province, China. The results show that, compared to internal factors, external factors play more important roles in shaping farmers’ land protection awareness which subsequently transfer into land protection behaviors. Various land use behaviors lead to different impacts on land quality, in which the crop planting structure and land input density have dominant effects on changes in the soil nutrient content. The results imply that a stable and reasonable price mechanism for agricultural inputs and outputs is meaningful to land protection. Moderate land circulation would help reduce land fragmentation, develop agricultural modernization, improve production efficiency, and achieve economies of scale. In addition, knowledge, training and environmental policy information on farmland protection play key roles in land conservation activities. These main results have important implications for policymakers with regard to promoting land protection activities, alleviating land resource and environmental pressures, and thus achieving the goal of sustainable land use.

Impact of Social Factors in Agricultural Production on the Crop Water Footprint in Xinjiang, China

Irrigation plays an important role in China’s agricultural production, and a reasonable assessment of water resources consumption in agricultural production will contribute to improved agricultural water management practices. The objectives of this study were to analyze variations in the magnitude of the crop water footprint (CWF) in Xinjiang and determine the major factors that influence variation in order to provide proposals for water resources management. The CWF of Xinjiang from 1988 to 2015 was calculated, and the impacts of crop-planting structures, agricultural inputs, and water conservancy projects on agricultural water use were analyzed to evaluate the suitable amount of agricultural water utilization and area of farmland in Xinjiang. Results show that the magnitude of the CWF in Xinjiang significantly increased during the study period. Construction of water conservancy projects greatly facilitated water diversion and had the closest relationship with the growth of CWF. The appropriate water volume and planting area for agriculture in Xinjiang is calculated to be 39.4 billion m3 and 4.3 million ha, respectively, which are 73% and 65% of the current water consumption and cultivated area, respectively. These results can be used as a reference for reducing agricultural water consumption and the farmland area in Xinjiang.

The virtual Water flow of crops between intraregional and interregional in mainland China

Agriculture is the main consumer of freshwater in the world. The paper described the process of virtual water content and flow in crops. Differences in climatic conditions of different regions in China result in large differences in water consumption during crop growth. The virtual water trade in crops connects water flows within and between regions, linking the actual water consumption with the invisible water trade as a whole. The objective of the paper was supplying the agricultural products virtual water trade evaluation system, determining quantitatively the virtual water flow within the region & regional. Using meteorological and agricultural data from 2003 to 2010, a comprehensive analysis of China's domestic & international virtual water trade of agricultural products has been undertaken. The virtual water for the three primary crops and virtual water trade are discussed. The virtual water content of grain crops in northern & southern China was 1293 m3/t & 942 m3/t, respectively; the national average value was 1117 m3/t; and the regional differences in virtual water content for each crop were significant. China's inter-regional agricultural products virtual water trade was not consistent with water resource endowment expectations. The transfer of crops from northern to southern regions would have a significant impact on the sustainable utilization of water resources and would exacerbate water resources shortages in northern regions. China had a trade surplus in global virtual water trade of agricultural products. The exported agricultural products virtual water amounted to 31.5 billion m3/yr., and the imported amount was 145 billion m3/yr. The net import of virtual water embedded in agricultural products increased from 44 billion m3/yr. in 2003 to 178 billion m3/yr. in 2010. It is further concluded that the trend for agricultural products total virtual water, green water, and blue water is that China is increasing its imports year on year. A large increase in imports of agricultural products has led to a decline in the rate of self-sufficiency in domestic agricultural production. The paper provided the basis for the comprehensive evaluation of crop planting structure adjustment, grain import & export, and the potential of regional water resources development and utilization.

Study on the ecological potential of Chinese straw resources available for bioenergy producing based on soil protection functions

Straw return has positive effect on improving soil ecological environment, and now there are serious ecological problems of arable land in China. Therefore, the concept of basic straw returning amount (BSRA) was put forward based on soil protection functions, and literature review and scenario analysis method were adapted to design BSRA. Based on this, a bottom up dynamic accounting model was built, which considering the changes of sown area, unit crop yield, planting structure and crop straw utilization. Then, the model was applied to assess the potentials of straw resources for bioenergy production. Usable straw resources in low, middle and high BSRA scenario (Table 1) are 265.70, 180.25 and 117.51 Tg respectively in 2030, mainly composed of paddy rice (Oryza sativa L.) stalk, maize (Zea mays L.) stalk and potato (Solanum tuberosum L.) stalk in low and middle scenario, and maize stalk, potato stalk and sugarcane (Saccharum officinarum) stalk in high scenario. Available crop residues mainly distribute in Sichuan, Henan, Heilongjiang and Shandong Province under the three scenarios. There will be interzone spatial transfer of usable straw resources, over time, mainly transferring to Northeast China, North China and Northwest China. The usable straw amount will have shape decrease in August and September as the increase of BSRA.

EXTRACTION AND ANALYSIS OF MAJOR AUTUMN CROPS IN JINGXIAN COUNTY BASED ON MULTI - TEMPORAL GF - 1 REMOTE SENSING IMAGE AND OBJECT-ORIENTED

Abstract. The purpose of this paper is to provide decision support for the adjustment and optimization of crop planting structure in Jingxian County. The object-oriented information extraction method is used to extract corn and cotton from Jingxian County of Hengshui City in Hebei Province, based on multi-period GF-1 16-meter images. The best time of data extraction was screened by analyzing the spectral characteristics of corn and cotton at different growth stages based on multi-period GF-116-meter images, phenological data, and field survey data. The results showed that the total classification accuracy of corn and cotton was up to 95.7 %, the producer accuracy was 96 % and 94 % respectively, and the user precision was 95.05 % and 95.9 % respectively, which satisfied the demand of crop monitoring application. Therefore, combined with multi-period high-resolution images and object-oriented classification can be a good extraction of large-scale distribution of crop information for crop monitoring to provide convenient and effective technical means.

THE RESEARCH ON DRYLAND CROP CLASSIFICATION BASED ON THE FUSION OF SENTINEL-1A SAR AND OPTICAL IMAGES

Abstract. In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.

Research on farmland crop classification based on UAV multispectral remote sensing images

Abstract: UAV remote sensing technology is used to accurately and efficiently identify crops in farmland, providing technical support for obtaining crop category information in time and realizing precision agriculture. Obtain multi-spectral images of farmland peach trees, corn, weeds and other ground objects with quadrotor equipped with a multi-spectral camera, and use the method of principal component analysis to transform the multi-spectral image, retain the first 2 spectral bands with the most information content, and calculate 16 textures from 7 vegetation indices, 6 reflectances and 2 principal component bands, totaling 29 The item feature is used as the feature parameter of the classification sample. The ReliefF algorithm is used to screen the spectral features and texture features respectively. The 11 features obtained (blue reflectivity, green reflectivity, red edge reflectivity, normalized green band difference vegetation index, enhanced vegetation index, ratio vegetation index, first One principal component correlation, second principal component synergy, information entropy, second moment, correlation). from the screening form the A-group feature data set. All the spectral features extracted from the image form the B-group feature data set and all the extracted texture features form the C-group feature data Set, all 29 features form the D feature data set. SVM support vector machine is used to supervise and classify the 4 groups of feature data sets, and the accuracy of the classification results obtained is evaluated. The accuracy of the supervised classification model trained on the single category feature data sets of B and C is poor, and the SVM supervised classification model trained on the feature data set of the ReliefF algorithm has a better classification effect, with an overall accuracy of 90.09%, and the Kappa coefficient of 0.86. The SVM model trained on the feature data set D has the best classification effect, with an overall accuracy of 92.01%, and the Kappa coefficient of 0.89. The ground object classification based on UAV multi-spectral images is efficient and feasible, which provides a reference for timely acquisition of crop planting structure in farmland. Keywords: UAV, Ground object identification, Multispectral remote sensing, ReliefF algorithm DOI: 10.33440/j.ijpaa.20210401.153 Citation: Yang D J, Zhao J, Lan Y B, Wen Y T, Pan F J, Cao D L, Hu C X, Guo J K. Research on farmland crop classification based on UAV multispectral remote sensing images. Int J Precis Agric Aviat, 2021; 4(1): 29–35.

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

In-Season Crop Mapping with GF-1/WFV Data by Combining Object-Based Image Analysis and Random Forest

Producing accurate crop maps during the current growing season is essential for effective agricultural monitoring. Substantial efforts have been made to study regional crop distribution from year to year, but less attention is paid to the dynamics of composition and spatial extent of crops within a season. Understanding how crops are distributed at the early developing stages allows for the timely adjustment of crop planting structure as well as agricultural decision making and management. To address this knowledge gap, this study presents an approach integrating object-based image analysis with random forest (RF) for mapping in-season crop types based on multi-temporal GaoFen satellite data with a spatial resolution of 16 meters. A multiresolution local variance strategy was used to create crop objects, and then object-based spectral/textural features and vegetation indices were extracted from those objects. The RF classifier was employed to identify different crop types at four crop growth seasons by integrating available features. The crop classification performance of different seasons was assessed by calculating F-score values. Results show that crop maps derived using seasonal features achieved an overall accuracy of more than 87%. Compared to the use of spectral features, a feature combination of in-season textures and multi-temporal spectral and vegetation indices performs best when classifying crop types. Spectral and temporal information is more important than texture features for crop mapping. However, texture can be essential information when there is insufficient spectral and temporal information (e.g., crop identification in the early spring). These results indicate that an object-based image analysis combined with random forest has considerable potential for in-season crop mapping using high spatial resolution imagery.

Spatiotemporal Patterns of Crop Irrigation Water Requirements in the Heihe River Basin, China

Agricultural expansion, population growth, rapid urbanization, and climate change have all significantly impacted global water supply and demand and have led to a number of negative consequences including ecological degradation and decreases in biodiversity, especially in arid and semi-arid areas. The agricultural sector consumes the most water globally; crop irrigation alone uses up more than 80% of available agricultural water. Thus, to maintain sustainable development of the global economy and ecosystems, it is crucial to effectively manage crop irrigation water. We focus on the arid and semi-arid Heihe River Basin (HRB), China, as a case study in this paper, extracting spatiotemporal information on the distribution of crop planting using multi-temporal Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) remote sensing (RS) images. We estimate the spatiotemporal crop irrigation water requirements (IWRc) using the Food and Agriculture Organization of the United Nations (FAO) Penman-Monteith method and reveal variations in IWRc. We also analyze the impact of changes in crop planting structure on IWRc and discuss strategies for the rational allocation of irrigation water as well as policies to alleviate imbalance between water supply and demand. The results of this study show that effective rainfall (ER) decreases upstream-to-downstream within the HRB, while crop evapotranspiration under standard conditions (ETc) increases, leading to increasing spatial variation in IWRc from zero up to 150 mm and between 300 and 450 mm. Data show that between 2007 and 2012, annual mean ER decreased from 139.49 to 106.29 mm, while annual mean ETc increased from 483.87 to 500.38 mm, and annual mean IWRc increased from 339.95 to 370.11 mm. Data show that monthly mean IWRc initially increased before decreasing in concert with crop growth. The largest values for this index were recorded during the month of June; results show that IWRc for May and June decreased by 8.14 and 11.67 mm, respectively, while values for July increased by 5.75 mm between 2007 and 2012. These variations have helped to ease the temporal imbalance between water supply and demand. Mean IWRc values for oilseed rape, corn, barley, and other crops all increased over the study period, from 208.43, 349.35, 229.26, and 352.85 mm, respectively, in 2007, to 241.81, 393.10, 251.17, and 378.86 mm, respectively, in 2012. At the same time, the mean IWRc of wheat decreased from 281.53 mm in 2007 to 266.69 mm in 2012. Mainly because of changes in planting structure, the total IWRc for the HRB in 2012 reached 2692.58 × 106 m3, an increase of 332.16 × 106 m3 (14.07%) compared to 2007. Data show that 23.11% (76.77 × 106 m3) of this increase is due to crop transfers, while the remaining 76.89% (255.39 × 106 m3) is the result of the rapid expansion of cultivated land. Thus, to maintain both the sustainable development and ecological security of the HRB, it is crucial to efficiently manage and utilize agricultural water in light of spatiotemporal patterns in IWRc changes as well as IWRc variations between different crops. The cultivation of water-demanding crops and the further expansion of agricultural land should also be avoided.

Optimization of water use structure and plantation benefit of unit water consumption using fractional programming and conditional value-at-risk model

For optimizing the water-use structure and increasing plantation benefit of unit water consumption, a multi-objective model for water resources utilization was established based on fractional programming (FP). Meanwhile, considering the stochasticity of water availability in the study area, the impact of the risk factor (λ) from a quantitative and qualitative perspective was analyzed. The chance-constrained programming (CCP) and conditional value-at-risk (CVaR) models were introduced into five important major grain production areas in Sanjiang Plain, and the crop planting structure under this condition was optimized. The results showed that, after optimization, overall benefit of cultivation increased from 42.07 billion Yuan to 42.47 billion Yuan, water consumption decreased from 15.90 billion m3 to 11.95 billion m3, the plantation benefit of unit water consumption increased from 2.65 Yuan/m3 to 3.55 Yuan/m3. Furthermore, the index of water consumption, benefit of cultivation and plantation benefit of unit water consumption showed an increasing trend with the increase of violation likelihood. However, through the quantification of λ from an economic perspective, the increasing of λ could not enhance plantation benefit of unit water consumption significantly. Keywords: agricultural water-use structure, plantation benefit of unit water consumption, the Sanjiang Plain, fractional programming (FP), chance-constrained programming (CCP), conditional value-at-risk (CVaR) DOI: 10.3965/j.ijabe.20171002.2961 Citation: Fu Q, Xiao Y Y, Cui S, Liu D, Li T X. Optimization of water use structure and plantation benefit of unit water consumption using fractional programming and conditional value-at-risk model. Int J Agric & Biol Eng, 2017; 10(2): 151–161.

Global vulnerability to agricultural drought and its spatial characteristics

As an important part of agricultural drought risk, agricultural drought vulnerability helps effectively prevent and alleviate drought impacts by quantifying the vulnerability as well as identifying its spatial distribution characteristics. In this study, global agricultural cultivation regions were chosen as the study area; six main crops (wheat, maize, rice, barley, soybean, sorghum) were selected as the hazard-affected body of agricultural drought. Then, global vulnerability to agricultural drought was assessed at a 0.5° resolution and finally, its distribution characteristics were revealed. The results indicated that the area percentages of different grades of global vulnerability to agricultural drought from low to very high were 38.96%, 28.41%, 25.37%, and 7.26%, respectively. This means that the total area percentage of high and very high vulnerability zones exceeded 30% of the study area. Although high and very high vulnerability zones were mainly distributed in arid and semi-arid regions, approximately 40% of those above were distributed in humid and semi-humid regions. In addition, only about 15% of the population in this study was located in the high vulnerability regions. Among the vulnerability factors, water deficit during the growing season and the irrigation area ratio are the key factors affecting regional vulnerability. Therefore, the vulnerability could be reduced by adjusting crop planting dates and structures as well as by improving irrigation level and capacity.

Effects of meteorological droughts on agricultural water resources in southern China

With the global warming, frequencies of drought are rising in the humid area of southern China. In this study, the effects of meteorological drought on the agricultural water resource based on the agricultural water resource carrying capacity (AWRCC) in southern China were investigated. The entire study area was divided into three regions based on the distributions of climate and agriculture. The concept of the maximum available water resources for crops was used to calculate AWRCC. Meanwhile, an agricultural drought intensity index (ADI), which was suitable for rice planting areas, was proposed based on the difference between crop water requirements and precipitation. The actual drought area and crop yield in drought years from 1961 to 2010 were analyzed. The results showed that ADI and AWRCC were significantly correlated with the actual drought occurrence area and food yield in the study area, which indicated ADI and AWRCC could be used in drought-related studies. The effects of seasonal droughts on AWRCC strongly depended on both the crop growth season and planting structure. The influence of meteorological drought on agricultural water resources was pronounced in regions with abundant water resources, especially in Southwest China, which was the most vulnerable to droughts. In Southwest China, which has dry and wet seasons, reducing the planting area of dry season crops and rice could improve AWRCC during drought years. Likewise, reducing the planting area of double-season rice could improve AWRCC during drought years in regions with a double-season rice cropping system. Our findings highlight the importance of adjusting the proportions of crop planting to improve the utilization efficiency of agricultural water resources and alleviate drought hazards in some humid areas.

Changes in ecosystem services associated with planting structures of cropland: A case study in Minle County in China

The cropland ecosystem provides essential direct and indirect products and services to mankind such as food, fiber, biodiversity and soil conservation. A change of crop planting structure can change the ecosystem services of cropland by affecting land use type. In recent years, under the influence of regional comparative advantage and consumer demand changes, the crop planting structure in China has changed rapidly. However, there is still a lack of deep understanding on the effect of such a change in planting structure on the ecosystem services of cropland. Therefore, this research selected Minle County in the Heihe River Basin, which has small scattered croplands and a complex planting structure, as a study area. Based on the key time phase and optimal threshold of the normalized difference vegetation index (NDVI) data of the Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images, this study used the decision tree algorithm to classify and extract the crop planting structure in Minle County in 2007 and 2012 and to analyze the changes in its temporal and spatial patterns. Then, the market value method was adopted to estimate the effect of the change in crop planting structure on the ecosystem services of the cropland. From 2007 to 2012, the planting area of corn and rapeseed in Minle County increased by 5.86 × 103 ha and 5.10 × 103 ha, respectively. Conversely, the planting area of wheat and barley was reduced by 3.26 × 103 ha and 6.34 × 103 ha, respectively. These changes directly caused the increase of the ecosystem services value of corn and rapeseed by 1062.82 × 104 USD and 842.54 × 104 USD, respectively. The resulting reduction in the ecosystem services value of wheat and barley was 488.24 × 104 USD and 828.29 × 104 USD, respectively. Besides, the total ecosystem services value of cropland increased by 1564.98 × 104 USD. Further analysis found that the change in the crop planting structure caused an increase in the ecosystem services value of cropland of 359.44 × 104 USD, with a contribution rate of 22.97% to the total increase. The expansion of corn caused the increase of the ecosystem services value of cropland by 151.65 × 104 USD, with a contribution rate of 9.69% to the total increase. The change in crop planting structure in Minle County increased not only the economic benefits of crop planting, but also the ecosystem services of cropland.

China’s environmental strategy towards reducing deep groundwater exploitation

Long-term over-exploitation of deep groundwater has made the North China Plain the world’s largest zone of groundwater depression, resulting in massive damage to the environment. As a result, China launched a resolute endeavor to reduce deep groundwater exploitation in 2014 when the Middle Route of the South-to-North Water Diversion Project, the world’s largest inter-basin water diversion project so far, was put into operation. In this process, water-source substitution is combined with diverse water-saving measures, including the adjustment of crop planting structures, the substitution of agricultural crops, water-saving techniques, and efficient water conservation projects. These structural measures have proved remarkably effective; however, to achieve a fundamental reduction in deep groundwater exploitation, it is imperative to control shallow groundwater pollution radically and build an efficient groundwater administration system.

Agricultural water supply/demand changes under projected future climate change in the arid region of northwestern China

The water resources in the arid region of northwestern China, which are impacted by climate change, tend to be more unstable, and the environment and ecosystems will suffer from severe water shortage. In this paper, potential future climate trends were predicted based on CMIP5 simulations in this region. The water availability and agricultural water demand under future climate change scenarios were estimated. Impacted by increases in temperature, the irrigation water demand will increase by 4.27–6.15billionm3 in this region over the next 60years, compared to the demand of 32.75billionm3 during 1971–2000. However, the annual runoff will only increase by 4.8–8.5billionm3, which is equivalent to or even less than the increased irrigation water demand. In fact, the increased demand for industrial, domestic and ecological water were not considered here. Thus, the water supply/demand contradiction will result in more severe water shortages in the future. According to a comparison with simulated irrigation water demand under three adaptation strategy scenarios, we should take effective measures such as improving the efficiency of irrigation water utilization, reducing crop planting areas and adjusting crop planting structures to alleviate the impacts of future climate changes and human activities on the water supply and water use in this region.

Crop Planting Structure Optimization for Water Scarcity Alleviation in China

SummaryAlong with globalization, countries consume a large amount of goods and services from both domestic and international markets. As one of the world's largest agricultural countries, China is faced with serious water scarcity and has to reduce the water consumption from both domestic and global aspects, of which the crop planting structure optimization (CPSO) between regions based on the virtual water perspective could be a solution for efficient agricultural water consumption. In this article, three scenarios of Chinese agriculture, including agricultural water consumption restrictions relaxed scenario, agricultural water consumption limited scenario, and net utilization ratio of water resources limited scenario, were designed to minimize the national agricultural water consumption under various water, land, and crop planting constraints in individual provinces and analyze the impacts of the CPSO. The results showed that compared with the historical situation of crop planting in 2007, 53.3%, 51.4%, and 47.3% of the agricultural water consumption and more than 10% of the sown area of China was saved under the three scenarios, respectively. Because of the reduction of agricultural water consumption and land use, it brought about the expansion of crops production in China. CPSO is found to have notable effects on water saving and food security considering the dependence of the crops by international trade.

Uncertain and multi-objective programming models for crop planting structure optimization

Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP) model and an inexact fuzzy linear programming (IFLP) model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimizationtheory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multiobjective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods of each model are expounded. Detailed analysis of results of each model and their comparisons demonstrate the feasibility and applicability of the models developed, therefore decision makers can choose the appropriate model when making decisions.

An Optimization Model of Crop's Planting Structure Using Linear Programming

An Optimization Model of Crop's Planting Structure Using Linear Programming