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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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Subject: Agricultural Meteorology × Start date: 1995 × Type: Thesis × Thesis Type: Ph.D ×
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Now showing 1 - 9 of 24
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    ThesisItemOpen Access
    EVALUATION OF CROPSYST MODEL FOR RAINFED GROUNDNUT UNDER MIDDLE GUJARAT AGRO-CLIMATIC
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B. A. COLLEGE OF AGRICULTURE ANAND AGRICULTURAL UNIVERSITY ANAND, 2021) Santosh Tukaram Yadav; Dr. M.M. Lunagaria
    Field experiments were carried out during the kharif seasons of the year 2019 and 2020 in a randomized block design (factorial) with four replications to study “Evaluation of CropSyst model for rainfed groundnut under middle Gujarat agro climatic zone”. The objectives were to calibrate CropSyst for groundnut cultivars under rainfed condition, to validate the CropSyst for rainfed groundnut in middle Gujarat agroclimatic zone and to study water productivity of kharif groundnut using CropSyst.
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    ThesisItemOpen Access
    STUDY OF ASTRO-METEOROLOGICAL TECHNIQUES FOR PREDICTING RAINFALL AND ITS DISTRIBUTION IN GUJARAT
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B. A. COLLEGE OF AGRICULTURE ANAND AGRICULTURAL UNIVERSITY ANAND, 2020) Vaidya Vidyadhar Bhaskar; Dr. Vyas Pandey
    The study on “Astro-meteorological techniques for predicting rainfall and its distribution in Gujarat” was conducted with an aim to conglomerate the ancient knowledge of astronomy with present day weather forecast and develop relationship between astrological/astronomical parameters with actual rainfall received over the period of time. The study was conducted with the objectives (i) finding out predominant planetary combinations, (ii) classifying and establishing relationship between planetary combinations and start of rainy season, wet spells, extreme rainfall and withdrawal of monsoon and (iii) forecasting and validation of Varahmihir’s Model of seasonal rainfall prediction for 16 locations of Gujarat. Validation of predominant planetary combination model using 35 years data for onset of monsoon, withdrawal of monsoon, wet spell and extreme rainfall at different locations of Gujarat was carried out in independent data (2015-2018).
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    ThesisItemOpen Access
    CALIBRATION OF INFOCROP MODEL (V 1.2) FOR SOYBEAN (Glycin max L.) CULTIVARS UNDER VARYING PLANT SPACING IN MIDDLE GUJARAT CONDITION
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B. A. COLLEGE OF AGRICULTURE ANAND AGRICULTURAL UNIVERSITY ANAND, 2019) VIBHA TAK; DR. M. M. LUNAGARIA
    Soybean (Glycin max L.) is one of the important oilseed crops of the world occupying 67.62 million hectares of land, with a production of 281.7 million tones (Anon, 2014). It is a unique two-in-one crop, having both high quality protein (43%) and oil (20%) content. It is raised in Kharif where supplemental irrigation facilities are available. The field experiment were carried out during the year 2015 and 2016, aimed to achieve the objectives set forth in laid out with split plot design with four replications to study “Calibration of InfoCrop (V 1.2) model for soybean (Glycin max L.) cultivars under varying plant spacing in middle Gujarat condition’’. The experiment involved three spacing viz., S1 – 45 x 10 cm, S2 – 45 x 5 cm and S3 – 30 x 10 cm as main plot treatments with three different cultivars viz., V1 – GS 2, V2 – GS 1 and V3 – NRC 37 as sub plot treatments.
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    ThesisItemOpen Access
    YIELD SIMULATION MODELING AND EVALUATION OF CLIMATE CHANGE IMPACT ON SUMMER MUNGBEAN (Vigna radiata L.) USING CROPGRO MODEL (DSSAT4.6) UNDER DIFFERENT IRRIGATION REGIMES AND ROW SPACINGS
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B. A. COLLEGE OF AGRICULTURE ANAND AGRICULTURAL UNIVERSITY ANAND, 2017) Karande Baban Ishwar; Dr. H. R. Patel
    The field experiment was conducted at B. A. College of Agriculture, Anand Agricultural University, Anand to study the “Yield simulation modeling and evaluation of climate change impact on summer mungbean (Vigna radiata L.) using CROPGRO model (DSSAT4.6) under different irrigation regimes and row spacings” during two consecutive years 2015 and 2016 with three irrigation regimes, two varieties and two row spacings. Twelve treatment combinations comprised of three levels of irrigation viz., I1 (0.8 IW: CPE ratio), I2 (0.6 IW: CPE ratio) and I3 (0.4 IW: CPE ratio) in main plot with two varieties viz., V1 (Meha) and V2 (GM-4) and two row spacing S1 (45 cm) and S2 (30 cm) in sub plot were tested in split plot design with three replications.
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    ThesisItemOpen Access
    CALIBRATION AND VALIDATION OF CROPGRO-peanut (DSSAT v.4.6) MODEL FOR SUMMER GROUNDNUT AND SENSITIVITY ANALYSIS TO CLIMATE CHANGE IN MIDDLE GUJARAT
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B. A. COLLEGE OF AGRICULTURE ANAND AGRICULTURAL UNIVERSITY ANAND, 2017) Mote Balaji Mohan; Dr. Vyas Pandey
    Field experiments were carried out during the summer season of the year 2015 and 2016 was laid out in a split plot design with three date of sowing i.e., (D1- 31st January, D2-15th February, D3- 02nd March) as main plot treatments and four cultivars viz., (V1-GG 2, V2-GG 20, V3-GJG 31 and V4-TG 26) as sub-plot treatment with four replications. The results obtained during the course of study revealed that the weather had played a significant role in deciding the yield of groundnut. The result showed that During 2015 the maximum pod yield (2093 kg ha-1) was recorded under second date of sowing (15th February) and it was statistically at par with first date of sowing (31st January) (1927 kg ha-1) and the lowest pod yield (1724 kg ha-1) was recorded under third date of sowing (02nd March). Similar trends were observed during 2016 also, with slightly higher value of pod yield in comparison to 2015. Similarly in pooled analysis, also the highest pod yield (2107 kg ha-1) was recorded under second date of sowing which was significantly higher than the pod yield recorded under first date of sowing (1939 kg ha-1) and third date of sowing (1767 kg ha-1). During both years and in pooled data highest pod yield was recorded under second date of sowing, It might be due to the late sown crop encountered higher temperature during reproductive period, resulting in shortening the duration and accumulation of higher heat units, resulting lowest pod yield.
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    ThesisItemOpen Access
    CALIBRATION AND VALIDATION OF CROPGRO (DSSAT 4.6) MODEL FOR CHICKPEA (Cicer arietinumL.) UNDER DIFFERENT HYDRO-THERMAL REGIMES OF MIDDLE GUJARAT REGION
    (DEPARTMENT OF AGRICULTURAL METEOROLOGY B.A. COLLEGE OF AGRICULTURE ANAND AGRICULTURALUNIVERSITY ANAND, 2017) Patil Deepak Devidasrao; Dr. H.R.Patel
    A field experiment was conducted for two consecutive years 2014-15 and 2015-16 with three dates of sowing and four irrigation levels. The experiment was laid out in strip plot design. The sowing dates D1-15th October, D2- 30th October and D3- 15th November as main plot treatments with irrigation levels as sub plot treatments namelyI1-Irrigation at critical growth stages, I2- 0.4 IW: CPE, I3- 0.6 IW: CPE and I4- 0.8 IW: CPE to calibrate and validate the CROPGRO (DSSAT 4.6) model for chickpea (Cicer arietinum L.) under different hydro-thermal regimes of middle Gujarat region.
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    ThesisItemOpen Access
    ESTIMATING WHEAT YIELDS IN GUJARAT USING WTGROWS AND INFOCROP MODELS
    (AAU, Anand, 2003) AKULA, BABY; Shekh, A. M.
    Crop simulation models are valuable tools to researchers to help them to understand the influence of climatic variables on crop productivity. The model estimated yields are handy to the agencies in government, trade and industry for planning about distribution, storage, processing, export or import of crop produce. Yield estimates by the models are also useful in taking timely policy decisions on fixing levy prices, because the estimates of the yield are available well in advance of the actual harvesting of the crop. Hence, a two-pronged approach was followed to estimate wheat yields in Gujarat, with the help of WTGROWS and InfoCrop simulation models. Initially both the models were calibrated and validated under Anand conditions through field experiment laid out in a strip plot design with three replications during rabi season of the years 2000 and 2001. Tliree dates of sowing were assigned as a main plot treatment with four irrigation regimes as sub plot treatments. Consistently higher yields were realised in case of the second date of sowing (15* Nov) during both the years although the yield differences were not statistically significant. Relatively more yields were realised in 2000 than those realised in 2001 and this was due to prevalence of favourable low temperatures during 50-90 DAS - a period that corresponded with anthesis to dough stage in conjunction with intermittent cold spells from 70-75 DAS corresponding with soft dough phase in the former year. In contrast to what was observed in case of yields in relation to the dates of sowing, yield data due to different irrigation treatments showed significant differences among them. Three irrigations gave significantly the lowest yield as compared with yields realised through any other irrigation treatment. The lowest yields realised in the treatment involving three irrigations were due to prevalence of moisture stress during tillering and flowering. Paradoxically, six irrigations despite not missing any important physiological stage, did not record significantly higher yield in comparison with yield in response to five irrigations. This was on account of the fact that, luxurious vegetative growth in the former case had caused lodging, as the prevailing wind speed was high. Different test criteria were followed to validate the performance of the models. Besides, error per cent was also calculated in all the different treatments to express the deviation in simulated values from those observed. Close scatter of simulated yield and total dry matter and respective measured values around the regression line and 1:1 line in case of both the models indicated good agreement between them. Both the models exhibited their robustness in predicting yields by explaining more than 90 per cent of variation in yield and total dry matter on an overall basis. However, there still remains some scope for improvement of the models in accounting for the loss due to lodging. The estimated RMSE for yield by WTGROWS was 318 kg ha-1, while that for yield by InfoCrop was 360 kg ha-1. Among the different dates of sowing, error per cent was relatively low in the treatments of the second date of sowing when compared with that for other dates. Both the models displayed decrease in error per cent with increase in irrigation levels. Underestimation of the simulated yield was more when the number of irrigations was less [three (I1) and four (I2)] when compared with that for more irrigations [five (I3) and six (I4)]. The underestimation was relatively more in case of InfoCrop, than that in case of WTGROWS. The performance of the models could be adjudged with the index of agreement (D), which was relatively high for WTGROWS (D= 0.97) than that for InfoCrop (D=0.95) in terms of yield. The models were also observed to perform in a similar way in terms of their response to the treatments in case of total dry matter, phenology and LAI also. The days to anthesis and maturity were simulated with less accuracy by both the models as compared to that of yield. Anthesis by WTGROWS explained more variance (R2=0.82) than that explained by InfoCrop (R2=0.75). The performance of these models in explaining the variance due to days to maturity was reverse of what was observed in case of anthesis. The highest and the .lowest ET were observed in case of the treatments of D2I4 and Dili, respectively. WTGROWS also showed similar pattern. Relatively higher proportion of MBE as compared to that of MAE during both the years in terms of ET as simulated by WTGROWS revealed under- prediction of ET by the model. Nonetheless, the error per cent did not cross the limit of -15 per cent during both the seasons except in case of Dill (-15.77%). Both the models expressed sensitivity to weather parameters viz., temperature, radiation and CO2 levels under both potential and stressed test conditions. But, the magnitude of change from the respective base yields in case of both the models was more to temperature under stressed conditions. However, the magnitude of response was more in case of WTGROWS than that in case of InfoCrop on overall basis except in case of radiation under stressed conditions where InfoCrop exhibited relatively more sensitivity. Linear response to TTVG, POTGWT, GNODMA, NSOILI, WLSTI was observed in case of both the models. The sensitivity was relatively more in case of WTGROWS than in case of InfoCrop. Moreover, InfoCrop exhibited linear response to RGRPOT and SLAVAR also. Statistical analysis of the historical actual wheat yield data of the state revealed that the average actual yield for the state as a whole was 2.5 t ha-1. Out of the ten districts selected to understand the temporal and spatial variability in wheat production levels and further to estimate yield gap through linking the model results with GIS, only Junagadh, Banaskantha and Bhavnagar exhibited significant positive linear trend at an average increase rate of 66, 31 and 25 kg ha-1 yr-1, respectively. Majority of the other districts failed to exhibit any discernible linear trend. However, Mehsana was found to be the second potential wheat producer of the state after Junagadh. The estimated average district potential yield by the models was 5.9 t ha-1 on overall bases. This is 2.36 times higher than the average actual state yield and is due to favourable thermal regimes as it was evident under Anand conditions where the estimated TTVG explained 87 per cent of variation in the potential yield and indicated significant linear positive trend. Similar reasoning holds good for higher potential yields in other districts. The attainable yields were estimated by imposing the management constraint of delayed sowing by twenty days from the optimum time (15thNov). The attainable wheat yields were found to decrease in all the districts irrespective of the agro climatic zone. The estimated attainable yield for the state as whole was 4.8 t ha-1 on the basis of the ten districts considered in the study. The average sowing yield gap between potential and attainable yield varied from 863 to 1205 kg ha-1 Reduction in yield due to delayed sowing was highest in the districts of Saurashtra which was followed in this respect by middle Gujarat, north Gujarat and south Saurashtra in sequence. The quantity of reduction in succession in these agro climatic zones was to the tune of 60, 59, 49 and 44 kg ha-1 per day delay in sowing, respectively.
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    ThesisItemOpen Access
    CROP-PEST-WEATHER INTERACTION AND POPULATION DYNAMICS OF (Heliothis armigera (Hubner) IN TWO DIVERSE PIGEONPEA (Cajanus cajan (L.) Millsp.) GENOTYPES (BDN-2 and GT-100) AT ANAND
    (AAU, Anand, 1998) Chaudhari, G. B.; Shekh, A. M.
    The results obtained in this investigation revealed that the air temperature and photoperiod had profound influence on growth and development of the pigeonpea crop. The variation in air temperatures during different phenophases resulted in differential attainment of physiological maturity in both the genotypes. Whereas, the differential availability of bright hours of sunshine (BSS) during reproductive phase resulted in higher seed yield. Low vapour pressure (VP) and relative humidity (RH) during flower bud initiation to podding phase, were favourable for higher seed yield. The seed yield and other yield attributing characters of pigeonpea crop were significantly influenced by the different treatments. The seed yield of protected condition was observed 36% higher than that under unprotected condition. The short duration genotype, GT-100 was found significantly higher in seedyield than the long duration genotype BbN-2. The seed yield was found to decrease upto 35%, with delayed sowing till 40 days after the onset of monsoon. Significant differences in total biomass were noticed in treatments like irrigation, genotypes and dates of sowing The results from correlation study revealed that there was a positive significant association between seed yield and different weather parameters like, maximum and minimum temperatures, bright hours of sunshine and different thermal indices like, growing degree days, phototherraal units and Heliothermal units and accumulated PAR. It has been observed that there was a difference in growing degree days requirement for the two genotypes to attain different phenological phases. To attain physiological maturity the GDD requirement for BDN-2 was 3105°Cd and it was 2894°Cd for GT-100 genotype
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    ThesisItemOpen Access
    DYNAMIC MODELING OF DAILY WATER USE BY SUMMER PEARL MILLET ' (Pennisetum americanum L.)
    (AAU, Anand, 1995) Bodapati, Papuji Rao; Savani, M. B.
    Crop water use is a complex function of the climatic conditions, stage of the crop development and the soil water content. Models have been developed earlier using various approaches and levels of details to improve the prediction of evapotranspiration. Functional models with some empiricism can be used for routine applications than the mechanistic models. Transpiration from the pearl millet was found to be strongly influenced by leaf area than by stomatal conductance. Field experiments during the summer season of the years 1994 and 1995 were conducted with pearl millet cv. GHB-30. The experiments were laid out in split-plot design, with three dates of sowing as the main plot and four irrigation levels as the sub-plot treatments which were replicated four times. The results obtained in this investigation revealed that, air temperature had a profound influence on the growth and development of summer pearl millet. The optimum date of sowing was found to be February 15th , which would provide optimum environmental conditions for the growth and development of the crop. Different dates of sowing did not show any significant effect on the grain yield. Irrigating the crop at 25% depletion of available soil moisture gave the highest grain and biomass yields but its WUE was lower than that for the other irrigation levels. Pearl millet required about 310 GDD in summer season to build considerable GLAI and about 800 GDD to attain the maximum GLAI. A second-order polynomial was developed for estimating GLAI using the accumulated GDD. The FAO Kc, values had over-estimated ET rates and a second-order polynomial was developed to estimate daily Kc values from the accumulated GDD for non-stressed pearl millet. The rate of ET in pearl millet was found to decrease with an increase in soil moisture deficit and approached zero at a soil moisture depletion of 65% of the available soil moisture. PLANTGRO and MCD models when evaluated against the field data collected through this experiment, predicted ET reasonably better for nonstressed treatments than for stressed treatments. Of the two models, the MCD model predicted better for stressed condition than the PLANTGRO model. The functional relations for the PET estimation and root water uptake in the MCD model needed substantial modification. The separation of the PET in the PLANTGRO model did not suit the summer pearl millet. A one-day time step model BAJRAWAT had been developed in the 'C' language during the course of the present study, and was made User-friendly. Irrigation amount and the PET being its main driving forces, the partitioning of PET into soil evaporation and transpiration had been accomplished in BAJRAWAT by GLAI. The actual evaporation and transpiration depended on the availability of water in the surface soil and in the root zone and also on the depth of root penetration. The evaporation was assumed to take place from the surface soil only and the soil was further divided into four layers, from which water was assumed to have been removed by transpiration and drainage. Infiltration was assumed to have been taking place depending on the amount and the location of water already in the soil layers. The transpiration was computed as a function of GLAI and the available moisture in the root zone. The development of GLAI was considered to be controlled by thermal time and a moisture stress factor. The BAJRAWAT model when validated along with PLANTGRO and MCD models predicted ET better than the latter two models. The relative transpiration of summer pearl millet was found to be more closely associated with relative dry matter yield than with the relative grain yield