Dhaliwal, L. K.Mehta, Purnima2021-01-182021-01-182020Mehta, Purnima (2020). Development of agroclimatic model for prediction of wheat phenophases and yield by using ICT tools (Unpublished Ph.D. Dissertation). Punjab Agricultural University, Ludhiana, Punjab, India.https://krishikosh.egranth.ac.in/handle/1/5810160286The field experiments were conducted at the Research Farm, Department of Climate Change and Agricultural Meteorology, Punjab Agricultural University, Ludhiana during rabi seasons of 2017-18 and 2018-19. The wheat varieties viz., PBW-725, PBW 677 and HD 3086 were sown on 25th October, 15th November and 5th December. Different agroclimatic indices viz., growing degree days, heliothermal units, photo-thermal units, pheno-thermal index, hygro-thermal units and relative temperature disparity were computed at different phenological stages. Heat use efficiency, helio-thermal use efficiency, photo-thermal use efficiency and radiation use efficiency were computed during both the years.The canopy temperature based different indices viz.,average canopy minus air temperature (TcTa) and summation stress degree days (SDD) were also calculated during both the crop seasons. The results indicated that growing degree days, hygro-thermal units and relative temperature disparity were higher in 25th October sown crop followed by 15th November and 5th December sown crop for variety PBW 677 during both the years. Whereas, helio-thermal units and photo-thermal units were higher in 5th December sown crop in comparison to 25th October sown crop for variety PBW 677 than PBW 725 and HD 3086. Heat use efficiency, helio-thermal use efficiency and photo-thermal use efficiency were higher in 25th October sown crop followed by 15th November and 5th December sown crop for biomass and grain yield during both the years. The results showed that crop sown on 5th December experienced higher canopy temperature at reproductive stages as compared to 25th October and 15th November sown crop. Higher negative stress degree days (SDDs) were observed under 25th October sowing as compared to 15th November and 5th December sowing reflects that canopy temperature was lower this means that the crop is healthy and without any stress.The grain yield was significantly higher in 25th October sowing (50.8 q/ha and 52.2 q/ha) as compared to 15th November (48.3 q/ ha and 49.9 q/ha) and 5th December sowing (42.1 q/ha and 43.3 q/ha) during both the crop seasons. Based on historical data, agroclimatic indices based regression models were developed for grain yield prediction at vegetative and reproductive stages under different dates of sowing. At the reproductive stage, accumulated growing degree days (AGDD) based model for 25th October sowing gave 16 per cent error followed by 15th November sowing with 5.7 per cent error. The AGDD based model for yield prediction is the best model with a minimum 5.7 per cent error under 15th November sowing.The Agromet wheat app is an android based app and android studio 3.5 is used for coding, backend core Java language is used and database is created through firebase. Agromet wheat mobile app was developed to give information to the users in English and regional language Punjabi. This app gives information about wheat management viz., varieties, sowing methods, irrigation, fertilizers, plant protection and recent advisories to the farmers about weather warning, insect and disease warning. Growing degree days calculator was developed to predict the phenological stages and yield of wheat crop.EnglishThesis