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Performance of meteorological, remote sensing and dynamic simulation models in wheat under Hisar conditions

KrishiKosh

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Title Performance of meteorological, remote sensing and dynamic simulation models in wheat under Hisar conditions
 
Creator Biswas, Barun
 
Contributor Ram Niwas
 
Subject fungi, planting, enzymes, biological development, diseases, productivity, biological phenomena, inorganic acid salts, pathogens, biological control
 
Description Field experiment entitled “Performance of Meteorological, Remote Sensing and Dynamic Simulation Models in Wheat under Hisar Conditions” was conducted during Rabi season (2010-11 and 2011-12) at research farm of Department of Agricultural Meteorology, CCS HAU, Hisar (29° 10 N, 75° 46 E and altitude 215.2 m). The experiment was comprised of three sowing dates main plot treatments namely (D1)-Early sowing on 5 November, (D2)-Timely sowing on 25 November and (D3)- Late sowing on 15 December; two sub plot treatments comprising two different cultivars viz. (V1)- WH711 and (V2)- DBW17; three sun-sub plot treatments of nitrogen doses viz. (N1)- 75% of the recommended dose, (N2)- 100% of the recommended dose and (N3)- 125% of the recommended dose. The experiment was laid out in split-split plot design with four replications. Different agrometeorological indices viz. GDD, HTU and PAU accumulation was significantly higher under early sowing date at all the phenopases in comparison to the other dates of sowing. The requirement of heat units were more in higher level of nitrogen application. Canopy reflectance of wheat crop was greatly influenced by date of sowing in both visible and infra-red bands. Green and IR reflectance were highest in 5 November sowing and in N1 nitrogen application. Different spectral indices (NDVI, GNDVI, RNDVI, PRI, SR, GVI and RVI) showed significant difference among crop under different growing environments and nitrogen levels. Above indices also indicated better crop growth and biomass production in early sowing and higher nitrogen fertilization. Different growing environment environments had affected wheat grain yield significantly and it was highest in 5 November sown crop. Nitrogen levels had also influenced the grain yield and produced highest grain yield in 125% nitrogen dose. The meteorological, spectral and integrated models developed using principal component analysis explained maximum variability in grain yield up to 98%. The crop parameters estimated by DSSAT model were closer to observed values as compared to the estimations by WOFOST model. However, the prediction made by integrated model was also closer to the actual values observed in the field. But such result was due to the fact that same data was used for prediction.
 
Date 2016-03-03T11:49:49Z
2016-03-03T11:49:49Z
2013
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/64656
 
Language en
 
Format application/pdf
 
Publisher CCSHAU