AN EMPIRICAL MODEL TO PREDICT YIELD OF RAINFED DRY BEAN WITH MULTI-YEAR DATA

Abstract

The prediction of crop yield and harvest volume of about 700 thousand ha planted to dry bean in Zacatecas State will enable the implementation of strategies to decrease the degree of uncertainty of decisions pertaining to agriculture. The purpose of the present study was to predict bean yield under rainfed conditions using leaf area index (LAI), light interception (LI) by the canopy, and rainfall. LAI and LI of both black-grain and light-colored grain beans were determined at the beginning of flowering, at pod formation, at the beginning of pod filling, and at intermediate pod filling. The relationship yield: LAI/LI/rainfall as well as the verification of a model were examined by linear least-square regression. Maximal LI and its LAI for the various years were 70 % and 1.6 for 2002 and 75 % and 2.5 in 2003. For these years, LI as a function of LAI could be described by an exponential model. LAI and LI at pod formation and the beginning of pod filling were the phenological stages that better explained bean yield for all varieties. The empirical model relating bean yield: LAI/LI/rainfall accounted for 71 % of the variability of light-colored grain bean yield. The corresponding percentages of the variability in measured yields for black-grain beans were 68 % for Emiliano Zapata and Progreso and 74 % for Zaragoza and Miguel Auza. Even though the relationship LAI/LI/rainfall was affected due to the low plant population density, the many varieties employed, and the agroecological sites, the information from this kind of studies will be useful to decision makers and farmers to make decisions.