مرجـع دانـش پارس

نوع فایل:PDF

تعداد صفحات:11

سال انتشار:1395

چکیده

Yield forecasting, has been used in many parts of the world to assess national food security and provide early food shortage warning. Early assessment of yield can help in strategic planning and decision-making. It is especially useful in countries where the economy depends on crop harvest. In Iran, it is important for determining import–export policies, government aid for farmers, and allocation of subsidies for regional agricultural programs. That there is a relationship or correlation between vegetation indices and estimation crop and we can estimate the amount of yield production by establishing this kind of correlation. There is a satisfactory match sLAI (from SAVI) and gLAI. The overall RMSE was reported to be 0.06 and 0.08 respectively. When sLAI was used instead of gLAI, mean simulation (absolute) error in terms of grain yield was increased to 0.01 Mgha-1. The results of the measurements and calculations showed that the estimation accuracy of product model is acceptable and can be used for estimating wheat dry-land in the study area. The rate of RMSE model under estimation was equal to 0.15 Mg ha-1 (n=120), and 0.19 (n=30), in addition to MSD of 0.02 Mg ha-1 (n=120) and that of 0.03 (n=30), which indicates good accuracy for farming year in the study area and indicates that model with both variables of sLAI & gLAI are accurate enough to estimate products

واژگان کلیدی

Wheat. Malayer,NDVI, SAVI.Iran