Cropping pattern optimization considering uncertainty of water availability and water saving potential

In arid and semi-arid areas,the profitability of irrigated agriculture mainly depends on the availability of water resources and optimal cropping patterns of irrigation districts.In this study,an integrated agricultural cropping pattern optimization model was developed with considering the uncertainty of water availability and water saving potential in the future,aiming to maximize agricultural net benefit per unit of irrigation water.The available water which was based on the uncertainty of runoff was divided into five scenarios.The irrigation water-saving potential in the future was quantified by assuming an increase in the rate irrigation water-saving of 10% and 20%.The model was applied to the middle reaches of Heihe River basin,in Gansu Province,China.Results showed that if the irrigation water-saving rate was assumed to increase by 10%,then the net water-saving quantity would increase by 21.5-22.5 million m3 and the gross water-saving quantity would increase by 275.7-303.0 million m3.Similarly,if the irrigation water-saving rate increased by 20%,then the net water-saving quantity would increase by 43.0-45.1 million m3 and the gross water-saving quantity would increase by 331.7-383.2 million m3.If the agricultural cropping pattern was optimized,the optimal water and cultivated area allocation for maize would be greater than those for other crops.Under the premise that similar volume of irrigation water quantity was available in different scenarios,results showed differences in system benefit and net benefit per unit of irrigation water,for the distribution of available irrigation water was diverse in different irrigation districts.

Empirical study on optimal reinsurance for crop insurance in China from an insurer's perspective

This study investigates the optimal reinsurance for crop insurance in China in an insurer＇s perspective using the data from Inner Mongolia, Jilin, and Liaoning, China. On the basis of the loss ratio distributions modeled by An Hua Crop Risk Evaluation System, we use the empirical model developed by Tan and Weng（2014） to study the optimal reinsurance design for crop insurance in China. We find that, when the primary insurer＇s loss function, the principle of the reinsurance premium calculation, and the risk measure are given, the level of risk tolerance of the primary insurer, the safety loading coefficient of the reinsurer, and the constraint on reinsurance premium budget affect the optimal reinsurance design. When a strict constraint on reinsurance premium budget is implemented, which often occurs in reality, the limited stop loss reinsurance is optimal, consistent with the common practice in reality. This study provides suggestions for decision making regarding the crop reinsurance in China. It also provides empirical evidence for the literature on optimal reinsurance from the insurance market of China. This evidence undoubtedly has an important practical significance for the development of China＇s crop insurance.

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

To improve the accuracy of runoff forecasting,an uncertain multiple linear regression(UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming(ITSP) model is used for crop planting structure optimization(CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.

Optimizing photorespiration for improved crop productivity

In C3 plants, photorespiration is an energyexpensive process, including the oxygenation of ribulose-1,5-bisphosphate(RuBP) by ribulose 1,5-bisphosphate carboxylase/oxygenase(Rubisco) and the ensuing multiorganellar photorespiratory pathway required to recycle the toxic byproducts and recapture a portion of the fixed carbon. Photorespiration significantly impacts crop productivity through reducing yields in C3 crops by as much as 50%under severe conditions. Thus, reducing the flux through, or weive R improving the efficiency of photorespiration has the potential of large improvements in C3 crop productivity.Here, we review an array of approaches intended to engineer photorespiration in a range of plant systems with the goal of increasing crop productivity. Approaches include optimizing flux through the native photorespiratory pathway, installing non-native alternative photorespiratory pathways, and lowering or even eliminating Rubiscocatalyzed oxygenation of RuBP to reduce substrate entrance into the photorespiratory cycle. Some proposed designs have been successful at the proof of concept level.A plant systems-engineering approach, based on new opportunities available from synthetic biology to implement in silico designs, holds promise for further progress toward delivering more productive crops to farmer’s fields.