Yield Prediction in Maize (Zea Mays) using Weather Parameters under Subtropical and Intermediate Regions of North-Western Himalayas Singh Mahender, Banotra Monika*, Sharma B.C., Sharma Charu, Sharma Rohit1 Division of Agronomy, Sher-e-Kashmir University of Agricultural Sciences & Technology of Jammu, Chatha, Jammu-180 009, India 1Regional Agricultural Research Stations, Rajouri, SKUAST-Jammu-185 131, India *E-mail: monikabanotra6@gmail.com
Online Published on 20 February, 2024. Abstract For prediction of maize yield in the north western Himalayas two districts Jammu and Udhampur belonging to different agro climatic conditions i.e. subtropical and intermediate regions were selected. For running yield prediction model at F2stage (Flowering) and F3 stage (Pre harvest) of maize crop long term weekly climatic data of Jammu and Udhampur districts from 1997 to 2021 (24 years) was collected from different departments related to Agriculture and Meteorology. For validation yield prediction model field experiments on maize crop were conducted during kharif season 2020 and 2021 at SKUAST-J main campus Chatha. Pre harvest yield prediction model for maize crop has been prepared by using this data. For prediction of maize yield at F2 and F3 stage the long-term data from 26th to 36th and 26th to 40th standard meteorological week (SMW) from 1997 to 2021 was used. Further composite weather variables were studied for developing yield forecast model. Simple and weighted weather indices have been prepared for individual weather variable and for their interaction with time. The yield forecast model were able to explain the variation in the grain yield of maize crop in subtropical Jammu region which was to the tune of 2.57 and -14.70 at F2 Stage and -3.00 and 9.70 during F3 stage where as in intermediate Udhampur district variation in F2 was 9.15 and 2.15 whereas during F3 stage -1.37 and 0.20 percent during kharif 2020 and kharif 2021.The predicted yield of maize crop for most of the stages are within acceptable error limit (+10 percent) in both the years of validation. Top Keywords Agro climatic, Maize, Forecast, Model, Prediction, Weather, Yield. Top |