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Anand Agricultural University, Anand

Anand Agricultural University (AAU) was established in 2004 at Anand with the support of the Government of Gujarat, Act No.(Guj 5 of 2004) dated April 29, 2004. Caved out of the erstwhile Gujarat Agricultural University (GAU), the dream institution of Sardar Vallabhbhai Patel and Dr. K. M. Munshi, the AAU was set up to provide support to the farming community in three facets namely education, research and extension activities in Agriculture, Horticulture Engineering, product Processing and Home Science. At present there seven Colleges, seventeen Research Centers and six Extension Education Institute working in nine districts of Gujarat namely Ahmedabad, Anand, Dahod, Kheda, Panchmahal, Vadodara, Mahisagar, Botad and Chhotaudepur AAU's activities have expanded to span newer commodity sectors such as soil health card, bio-diesel, medicinal plants apart from the mandatory ones like rice, maize, tobacco, vegetable crops, fruit crops, forage crops, animal breeding, nutrition and dairy products etc. the core of AAU's operating philosophy however, continues to create the partnership between the rural people and committed academic as the basic for sustainable rural development. In pursuing its various programmes AAU's overall mission is to promote sustainable growth and economic independence in rural society. AAU aims to do this through education, research and extension education. Thus, AAU works towards the empowerment of the farmers.

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  • ThesisItemOpen Access
    SIMULATION MODELING OF WHEAT YIELD USING WOFOST MODEL UNDER MIDDLE GUJARAT AGRO CLIMATIC REGION
    (AAU, Anand, 2013) MISHRA, SUDHIR KUMAR; Shekh, A. M.
    Crop growth simulation models are useful tools for considering and exploring the complex interactions between a range of factors that affecting crop performance, including weather, soil properties and management. To sustain crop production and to reduce the detrimental effects of varied environmental conditions on crop production, the understanding of crop growth in relation to varying resource input and agro-environments is required for management options. Improved production technology at the farm level is the most crucial starting point for future improvement of productivity of wheat by employing and adapting suitable crop growth simulation models. In addition to this, the use of crop growth simulation models comes handy to the government agencies, trade and industry and for planning about the distribution, storage, processing, and export/import of crop produce besides taking timely policy decisions on fixing levy prices as they provide accurate advance estimation of yields. Crop simulation models are recent tools that have facilitated identification of production constraints and for assisting in agro-technology transfer. In the present investigation, WOFOST (WOrld FOod STudy) v.7.1 model was used to develop genetic coefficients and validate it under Anand conditions by conducting a field experiment on Sandy loam soil during two consecutive Rabi seasons of 2009- 2010 and 2010-2011. The study was carried out for simulation of phenology. growth and yield of four different wheat cultivars (cv. GW 322, GW 496, GW 366 and GW 1139), vahdation of four dates of sowing viz., D1 (1st November), D2 (15th November), D3 30th November and D4 (15th December), cahbration of genetic coefficients of all four different cultivars, carry out the sensitivity analysis of WOFOST model with respect to middle Gujarat agro-climatic region. The cultivar GW 322 performed best during 2009-2010, 2010-2011 and in pooled analysis in producing the grain yield by 3611 kg/ha, 4384 kg/ha and 3998 kg/ha. Among all cultivars, GW 322 performed best (3611 kg/ha in 2009-2010 and 4384 kg/ha in 2010-2011) followed by cultivar GW 496, GW 366 and GW 1139. Although the durum type wheat cultivar GW 1139 yielded least among all cultivars. The yield reduction is more under delayed sowing. Although this cultivar (GW 1139) is cultivated under rainfed conditions in Bhal zone but, under irrigated conditions in Anand its performance was better in terms of duration as well as in yield. The mean maximum temperature of wheat growing season during first year ranged between 30.4 to 31.4 °C while, during second year it was between 28.9 to 31.3 °C under different dates of sowing. Higher maximum temperature caused the reduction in wheat yield. With an increase of 1°C in maximum temperature the wheat yield reduced by 412 kg/ha. Among different stages, the flowering stage was most vulnerable with increase temperature. At this stage, every 1°C increase in the maximum, minimum and mean temperatures respective reduction in yield was 213 kg/ha, 177 kg/ha and 231 kg/ha. Minimum temperature less than 11.5 °C at flowering stage was found more favourable for wheat production. This lower minimum temperature corresponds with the wheat sown on the normal dates (15th November) hence, it is recommended. The association between simulated and observed grain yields of GW 496, GW 366 and GW 1139 cultivars were found satisfactory. Consistently higher grain yields were realized in case of the second date of sowing (15th November) during both the years and the yields were statistically significant for the pooled data over the years. Average minimum temperature in D2 sowing around 11.5°C around 70 DAS and 8.4°C at 60 DAS in 2009-2010 and 2010-2011, respectively seemed to have contributed to yields under D2 being higher than those under D1, D3 and D4. The average minimum temperature in D2 sowing was found the lowest and prevalence of lower mean temperature during flowering and milking stage during both the years were found favourable for higher grain yield. The WOFOST model was superior to InfoCrop and DSSAT crop simulation models in simulation of days to anthesis and maturity of wheat crop. Various test criteria were applied to validate the performance of the model. The simulation performance of grain yield was found better in 2009- 2010 than in 2010-2011. The calibrated WOFOST model performed well for simulating phenological stages (viz., anthesis and physiological maturity) with error percent less than 4.03%. Similarly, the error percent was less than 8.48 for simulation of grain and biomass production. Hence, this model can be used for simulating the phenology and yield of wheat cultivars. Highest error 9.34% was noticed in simulation of leaf area index by InfoCrop and 9.21% by DSSAT model. The comparison of WOFOST with DSSAT and InfoCrop models suggested the superiority of WOFOST over others as it was evident from least percent error in simulating phenology, yield and yield attributes of wheat. The DSSAT models also simulated the phenology, yield and yield attributes of wheat close to the observed. This model estimated the yield, biomass and harvest index with percent error less than 7.83, -5.5 and 11.47, respectively. Index of agreement from all three models was more than 0.95 in simulations of various growth and yield components of wheat cultivars under varied environmental conditions reveal the accuracy of models.