Regression models for lentil seed and straw yields in Near East

Abstract

Lentil (Lens culinaris Medikus subsp. culinaris) is traditionally grown as a rainfed crop globally, except in Sudan and Egypt, where it is grown under supplemental irrigation. Its seed is a rich source of protein for human consumption, and the straw is a valued animal feed in Near East. In the Mediterranean environment, lentil productivity is limited primarily by the amount and distribution of rainfall and temperature extremes. This study aimed to develop simple models to predict lentil seed and straw yields as a function of seasonal weather data (rainfall and temperature). Historical weather and yield trial data over 39 environments from three contrasting locations in Syria and Lebanon were used. Best-fit models for seed and straw yields in terms of climatic variables based on stepwise regression were developed. These accounted for over 77% variance in yield for both models. The overall responses to total seasonal rainfall were 5.16 kg ha−1 mm−1 seed yield and 10.7 kg ha−1 mm−1 for straw yield. Although May (period of pod-filling) rain contributed substantially to seed yield, high May temperatures reduced yield drastically. For straw yield, absolute minimum temperature and February temperature are important factors, in addition to total seasonal rainfall. The simple regression models developed from historical data not only describe the variation in lentil yields but can also be used for yield prediction purposes in the Near East.