The measure of data aggregation bias for crop production risk assessment

2015 ◽  
pp. 53-60
Keyword(s):  
Risk Assessment ◽  
Data Aggregation ◽  
Crop Production ◽  
Aggregation Bias ◽  
Production Risk

scholarly journals Toward Methodology of Satellite Observation Utilization for Agricultural Production Risk Assessment

IERI Procedia ◽  
2013 ◽  
Vol 5 ◽  
pp. 21-27 ◽  
Author(s):  
Yuriy V. Kostyuchenko ◽  
Yulia Bilous ◽  
Dmytro Movchan ◽  
László Márton ◽  
Ivan Kopachevsky
Keyword(s):  
Risk Assessment ◽  
Agricultural Production ◽  
Satellite Observation ◽  
Production Risk

scholarly journals Risk Management Strategies in Humid Production Regions: A Comparison of Supplemental Irrigation and Crop Insurance

2004 ◽  
Vol 33 (2) ◽  
pp. 220-232 ◽  
Author(s):  
Timothy J. Dalton ◽  
Gregory A. Porter ◽  
Noah G. Winslow
Keyword(s):  
Risk Management ◽  
Crop Production ◽  
Crop Insurance ◽  
Management Strategies ◽  
Economic Feasibility ◽  
Supplemental Irrigation ◽  
Production Risk ◽  
Enterprise Risk ◽  
Risk Management Strategies ◽  
Management Responsibility

Recent federal agricultural programs have accelerated the devolution of enterprise risk management responsibility from the state to individual producers. Using a biophysical simulation model, the risk management benefits of federal crop insurance and supplemental irrigation are derived and compared to uninsured rainfed crop production in an expected utility framework. Federal crop insurance programs are inefficient at reducing producer exposure to weather-related production risk in humid regions, and the risk management benefits from supplemental irrigation are found to be scale and technology dependent. Environmental policies that regulate resource development will increase the investment cost of irrigation alternatives and reduce economic feasibility.

scholarly journals Diversified Crop Rotation: An Approach for Sustainable Agriculture Production

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Kabita Kumari Shah ◽  
Bindu Modi ◽  
Hari Prasad Pandey ◽  
Arjun Subedi ◽  
Geeta Aryal ◽  
...  
Keyword(s):  
Crop Rotation ◽  
Crop Production ◽  
Disease Incidence ◽  
Soil Health ◽  
Farming Systems ◽  
Soil Condition ◽  
Crop Rotations ◽  
Production Risk ◽  
System Productivity ◽  
Distinct Structure

Diversified crop rotation (DCR) improves the efficiency of farming systems all over the world. It has the potentiality to improve soil condition and boost system productivity. Improved soil attributes such as increased soil water uptake and storage, and a greater number of beneficial soil organisms, may improve yield tolerance to drought and other hard growing conditions in a variety of crop rotations. Crop rotations with a variety of crops benefit the farmers,reduce production risk and uncertainty, and enhance soil and ecological sustainability. Farmers may be able to diversify their sources of income by adopting diversified crop rotations. Furthermore, because of the distinct structure, function, and relationship of plant community with soil in DCR, it contributes to the long-term development of soil health by decreasing insect, weed, and disease incidence and increasing the physical and chemical structure of the soil. DCR is becoming more popular approach for maintaining sustainable crop production. This review provides the evidence of the significance of DCR, challenges to adapt it, and possible way out to overcome the challenges.

Validating the AquaCrop model for maize under different sowing dates

Water Policy ◽  
2018 ◽  
Vol 20 (4) ◽  
pp. 826-840 ◽  
Author(s):  
Waseem Raja ◽  
Raihana Habib Kanth ◽  
Purshotum Singh
Keyword(s):  
Crop Production ◽  
Canopy Cover ◽  
Climatic Conditions ◽  
Climatic Data ◽  
Production Risk ◽  
Sowing Dates ◽  
Aquacrop Model ◽  
Water Field ◽  
Using Data ◽  
Crop Growth Simulation

Abstract The crop growth simulation driven by daily climatic data can be used to predict the yield under varied climatic conditions. The simulation model can be exploited to reduce production risk and to evaluate the effect of soil, water, field management and climate on crop production. In this study, the FAO AquaCrop model was calibrated and validated for maize under varied sowing dates during 2012 and 2013. The experiment was conducted at Shalimar Campus of Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir during kharif seasons of 2012 and 2013. Calibration was done using data of 28 April sowing of 2012 and validation was done by using data of 10 May and 25 May sowing of 2012, and 28 April, 10 May and 25 May sowing of 2013. The simulated grain yield and crop water use was acceptable as root mean square error (RMSE) between simulated and measured observations was low (≤0.05 t ha−1 and ≤16.72 mm) with high coefficient of efficiency (0.99 and 0.71), respectively. The model also performed satisfactorily for the canopy cover and in-season biomass under varied sowing dates having RMSE ≤9.97% and ≤1.78 t ha−1, respectively.

scholarly journals Projection of Rice and Maize Productions in Northern Thailand under Climate Change Scenario RCP8.5

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 23
Author(s):  
Teerachai Amnuaylojaroen ◽  
Pavinee Chanvichit ◽  
Radshadaporn Janta ◽  
Vanisa Surapipith
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climate Model ◽  
Crop Yields ◽  
Regional Climate ◽  
Change Scenario ◽  
Northern Thailand ◽  
Maize Production ◽  
Production Risk ◽  
Rainfed Rice

Climate change has an effect human living in a variety of ways, such as health and food security. This study presents a prediction of crop yields and production risks during the years 2020–2029 in northern Thailand using the coupling of a 1 km resolution regional climate model, which is downscaled using a conservative remapping method, and the Decision Support System for the Transfer of Agrotechnology (DSSAT) modeling system. The accuracy of the climate and agricultural model was appropriate compared with the observations, with an Index of Agreement (IOA) in the range of 0.65–0.89. The results reveal the negative effects of climate change on rice and maize production in northern Thailand. We show that, in northern Thailand, rainfed rice and maize production may be reduced by 5% for rice and 4% for maize. Moreover, rice and maize production risk analysis showed that maize production is at a high risk of low production, while rice production is at a low risk. Additional irrigation, crop diversification, the selection of appropriate planting dates and methods of conservation are promising adaptation strategies in northern Thailand that may improve crop production.

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