Relation between soil temperature and biophysical parameters in Indian mustard seeds

Temporal changes in surface soil temperature were studied in winter crop. Significant changes in bare and cropped soil temperature were revealed. Air temperature showed a statistically positive and strong relationship (R2 = 0.79** to 0.92**) with the soil temperature both at morning and afternoon hours. Linear regression analysis indicated that each unit increase in ambient temperature would lead to increase in minimum and maximum soil temperatures by 1.04 and 1.02 degree, respectively. Statistically positive correlation was revealed among biophysical variables with the cumulative surface soil temperature. Linear and non-linear regression analysis indicated 62-69, 72-86 and 72-80% variation in Leaf area index, dry matter production and heat use efficiency in Indian mustard crop as a function of soil degree days. Below 60% variation in yield in Indian mustard was revealed as a function of soil temperature. In contrast, non-significant relationship between oil content and soil temperature was found, which suggests that oil accumulation in oilseed crops was not affected significantly by the soil temperature as an independent variable

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Not AvailableA study was carried out to develop useful. quantitative relationships between spectral indices (lR/R and NDVI) and leaf area index (LAl) in chickpea crop under irrigated and unirrigated conditions under field conditions. Six varieties differing in their growth habits and plant types were grown on sandy clay loam soils of Indian Agricultural Research Institute research farm during two rabi seasons of 2000-01 and 2001-02 under irrigated and unirrigated conditions following the recommended agronomic practices. The coefficients of determination (r2) values were obtained for the relations between LAI and spectral indices (lR/R and NDVI). Various types of regressions were tried and finally it was inferred that LAI can be best estimated by both lR/R and NDVI derived from the spectral reflectance data using linear or polynomial equations.Not Availabl

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Not AvailableQuantification of plants biophysical variable, economic yield and oil content of oilseed Brassica is important to know the potential impact of in-season weather variability. Agroclimatic models may be used to predict the plants' response and adaptability in the soil-plants-atmospheric systems and thereby screening various mitigation options to combat impinging climate change. In this study, some important biophysical indicators viz., leaf area index (LAI), dry biomass, economic seed yield and oil content of Indian mustard have been predicted using thermal unit based regression models following field experimentations carried out in two consecutive winter seasons of 2005-06 and 2006-07 on a sandy clay loam soil of IARI research farm, New Delhi. Linear and non-linear regression models were developed in which thermal indices viz., Growing Degree Days (GDD), Heliothermal Unit (HTU) and Photothermal Unit (PTU) have been used as independent variables. These thermal units were cumulated up to maximum leaf area index and dry biomass and 50% physiological maturity. Models developed from pooled data showed statistically significant and positive correlations existed between biophysical variables with thermal units.GDDand PTU based regression models may be recommended for predicting leaf area index (LAI = 0.008 ×GDD- 3.54; R = 0.78 * * and LAI = 0.0007 × PTU - 3.31; R = 0.75 * *) and dry biomass production (Dry biomass = 1.89 × GDD - 1060.3; R = 0.87 * * and Dry biomass = 0.15 ×PTU- 794.02;R = 0.85 * *).HTUbased regression models were found to be better predictor only when accumulated values of the index exceeded 1000 Cd hours (LAI = 0.0005 × HTU + 0.69; R = 0.31 and Dry biomass = 0.11 × HTU + 202.81; R = 0.51). The generated agroclimatic models may be complementary to decision support systems for predicting biophysical parameters under semi-arid subtropical environment using daily information on critical weather parameters.Not Availabl

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Not AvailableField experiments were conducted for two years (2005-06 and 2006-7) at IARI New Delhi, India research farm to assess the variations of micrometeorological parameters under differential hydrothermal regimes in mustard crop. Changes in sowing time and branch removal/defoliation treatments were imposed in order to create variations by hydrothermal regimes under phenology based irrigation scheduling. It was inferred that near ground surfaces in the debranched plot where microenvironment was modified, air temperatures were higher(2 to 3 degree celcius) as compared to control plots, decreased at 35 cm and remained almost similar with further increase in height at 1130 hrs while at 1430 hrs the magnitude of temperature variations was relatively higher. In contrast to air temperature, the relative humidity in debranched plot was less than that of control plot. At near ground, even at higher canopy height about 10% higher RH variations were observed in control plot as compared to debranched plot both in morning and afternoon hours. Furthermore, leaf area index could explain variations in temperature and RH to the tune of 45-50% radiation penetration and soil moisture depletion pattern also indicated significant impact of microclimatic variations near the ground.Not Availabl

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Not AvailableBiomass production in arid and semi-arid regions requires a special attention owing to spatiotemporal scarcity of irrigation water wherein improved water use efficiency (WUE) of the crop is targeted. Under field conditions, the crop undergoes dynamic changes in near ground or within-canopy microenvironments. This changed microclimatic condition may have an impact on phenological response of the oilseed crop which in turn would affect biomass productivity, economic seed yield and water use efficiency of the crop. Henceforth, quantification of biomass production and its WUE of oilseed Brassica crop is essentially required owing to have better understanding of the crop water requirement under the era of climate change. Following a 2 years field experiment, it was revealed that the changes in leaf area index were explained by about 68e74%. The best fit polynomial third order regression analysis indicated >93% prediction in biomass production as a function of time factor. Improved biomass partitioning into economic sinks was also observed. Small scale change in near ground microenvironment may reduce the prediction of biomass variability to the extent of 3%. The mean ET variations were observed as 2.4, 1.5 and 3.2 mm day_1 during the critical phenological stages. Mean seed yield, biomass WUE and seed yield WUE ranged between 2.71 and 2.87 Mg ha_1, 11.4 and 13.1 g m_2 mm_1 and 19.3 and 22.9 kg ha_1 mm_1 respectively. Variations in both biomass and seed yield water use efficiencies due to small scale change in near ground microclimates were revealed.Not Availabl