Crop yield is mainly affected by weather condition, inputs, and agriculture policies. In the crop yield estimation, farmers＇ perception on weather conditions lead to the assessment of how well yield would be compared...Crop yield is mainly affected by weather condition, inputs, and agriculture policies. In the crop yield estimation, farmers＇ perception on weather conditions lead to the assessment of how well yield would be compared to the previous seasons. This paper applies Bayesian estimation method to estimate crop yield with farmers＇ appraisal on weather condition. The paper shows that crop yield estimation with farmers＇ appraisal on weather condition takes into account risk proportionally to climate change. In light of the United Nations efforts aimed to build a consolidated agriculture statistical system across countries, the statistical model developed here should provide an important tool both for the crop yield estimation and food price analysis.展开更多
Three-year investigation was conducted to demonstrate the mechanism of reduction of soybean yield aroused by continuous and every second year cropping. Compared to normal cropping, there are many unfavorable changes i...Three-year investigation was conducted to demonstrate the mechanism of reduction of soybean yield aroused by continuous and every second year cropping. Compared to normal cropping, there are many unfavorable changes in some major elements of soybean plant and soil environment. Chloropyll content was lower. Phosphorous content of soybean plant was decreased seriously. Potassium content was lower while calcium content was higher. Magnesium content was wot affected and decreased in susceptive varieties. Some deseases and insects of soybean under continuous and wery second year cropping conditions became serious as continuous years prolonged. Organic matter content tended to go down from normal rotation to continuous cropping. Amount of bacteria and antinomyces decreased while amount of fungi increased. The development of symbiotic nitrogen fixation system wsa deteriorated.展开更多
The formation of rice distribution is based on certain natural ecological conditions and social economic environments. In China, rice cropping is distributed in a vast area extending across 5 tempera ture belts, the n...The formation of rice distribution is based on certain natural ecological conditions and social economic environments. In China, rice cropping is distributed in a vast area extending across 5 tempera ture belts, the northernmost of rice growing area in the world being in China. Distribution of rice cropping is characterized by a gradual decrease from south to north, from large and concentrated regions in Southeast to small and separated areas in Northwest. Natural conditions in rice regions differ in China with a varied topography, high in the west and low in the east. Rice fields in the west are mostly distributed on flatlands on plains, valleys among mountains, tablelands in river valleys, yellow-soil plains and basins in low valleys, alluvial plains, plains in river valleys, while those in the east are mainly distributed on alluvial plains, hilly areas among low mountains, coastal plains, along rivers and lakes and in basins among mountains.展开更多
Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and ...Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in ag- ricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers＇ loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation （EO） data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration （NASA） Earth Observing System Data and Information System （EOSDIS）, for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment, the near-real-time availability of EO data, the service-oriented architecture, geospatial interoperability standards, and the standard-based geospatial web service technology. The prototypical system has automatically generated the flood crop loss products and demonstrated the feasibility of using such products to improve the agricultural decision-making. Evaluation of system by the end-user agencies indicates that significant improvement on flood-related crop decision-making has been achieved with the system.展开更多
文摘Crop yield is mainly affected by weather condition, inputs, and agriculture policies. In the crop yield estimation, farmers＇ perception on weather conditions lead to the assessment of how well yield would be compared to the previous seasons. This paper applies Bayesian estimation method to estimate crop yield with farmers＇ appraisal on weather condition. The paper shows that crop yield estimation with farmers＇ appraisal on weather condition takes into account risk proportionally to climate change. In light of the United Nations efforts aimed to build a consolidated agriculture statistical system across countries, the statistical model developed here should provide an important tool both for the crop yield estimation and food price analysis.
文摘Three-year investigation was conducted to demonstrate the mechanism of reduction of soybean yield aroused by continuous and every second year cropping. Compared to normal cropping, there are many unfavorable changes in some major elements of soybean plant and soil environment. Chloropyll content was lower. Phosphorous content of soybean plant was decreased seriously. Potassium content was lower while calcium content was higher. Magnesium content was wot affected and decreased in susceptive varieties. Some deseases and insects of soybean under continuous and wery second year cropping conditions became serious as continuous years prolonged. Organic matter content tended to go down from normal rotation to continuous cropping. Amount of bacteria and antinomyces decreased while amount of fungi increased. The development of symbiotic nitrogen fixation system wsa deteriorated.
文摘The formation of rice distribution is based on certain natural ecological conditions and social economic environments. In China, rice cropping is distributed in a vast area extending across 5 tempera ture belts, the northernmost of rice growing area in the world being in China. Distribution of rice cropping is characterized by a gradual decrease from south to north, from large and concentrated regions in Southeast to small and separated areas in Northwest. Natural conditions in rice regions differ in China with a varied topography, high in the west and low in the east. Rice fields in the west are mostly distributed on flatlands on plains, valleys among mountains, tablelands in river valleys, yellow-soil plains and basins in low valleys, alluvial plains, plains in river valleys, while those in the east are mainly distributed on alluvial plains, hilly areas among low mountains, coastal plains, along rivers and lakes and in basins among mountains.
基金supported by grants from the National Aeronautics and Space Administration Applied Science Program,USA (NNX12AQ31G,NNX14AP91G,PI:Dr.Liping Di)
文摘Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in ag- ricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers＇ loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation （EO） data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration （NASA） Earth Observing System Data and Information System （EOSDIS）, for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment, the near-real-time availability of EO data, the service-oriented architecture, geospatial interoperability standards, and the standard-based geospatial web service technology. The prototypical system has automatically generated the flood crop loss products and demonstrated the feasibility of using such products to improve the agricultural decision-making. Evaluation of system by the end-user agencies indicates that significant improvement on flood-related crop decision-making has been achieved with the system.
