ESTIMATION OF BIOMASS YIELD OF WHEAT USING CANOPY REFLECTANCE AT DIFFERENT GROWTH STAGE

R. BAGHEL¹*, S.K. PYASI², R. SHARMA^3
1Department of Soil and Water Engineering, College of Agricultural Engineering, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Adhartal, Jabalpur, 482004, India
²Professor of Soil and Water Engineering, College of Agricultural Engineering, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Adhartal, Jabalpur, 482004, India
³Principal Scientist Agriculture & Soil Division, RSAC, Madhya Pradesh Council of Science and Technology, Bhopal, 462003, Madhya Pradesh, India
* Corresponding Author : rachnabjnkvv@gmail.com

Received : 19-09-2023     Accepted : 28-10-2023     Published : 30-10-2023
Volume : 15     Issue : 10       Pages : 12674 - 12680
Int J Agr Sci 15.10 (2023):12674-12680

Keywords : LAI meter, Chlorophyll meter, Spectrometer
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to Director, Regional National Institute of Hydrology, Bhopal; Department of Soil and Water Engineering, College of Agricultural Engineering, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Adhartal, Jabalpur, 482004, Madhya Pradesh, India and Agriculture & Soil Division, RSAC, Madhya Pradesh Council of Science and Technology, Bhopal, 462003, Madhya Pradesh, India
Author Contribution : All authors equally contributed

The study was planned in village Halali of district Raisen to determine the vegetative canopy of wheat at different growth stages, to compare canopy reflectance/ radiance of wheat crop using radiometer observation, remote sensing data and recommendation of best method to examine the utility of hyperspectral remote sensing in predicting canopy characteristics such as LAI and canopy chlorophyll content in a crop. The study area belongs to eastern part of the fertile Vindyanchal Plateau. This study has been done for the data collected during humid subtropical climate with cool, dry winter’s a hot summer and a humid monsoon season. Reflectance observations available at very high (56m) spatial resplution from Advanced Wide- Field Sensore (AWiFS) sensore onboard Indian Remote Sensing, Resourcesat-2 satellite was used in this study. Forward simulation of canopy reflectance in four AWiFS band viz. GREEN (0.52um), RED(0.62-0.68um),NIR(0.77-0.86um),SWIR(1.55-1.70um)were carried out to generate the look up table using CRT model PROSIAL from all combinations of canopy intrinsic variable. An inversion technique based on minimization of cost function was used to retrieval LAI from LUT and observed AWiFS surface reflectance. The plant bio physical parameter of wheat was measured in different stage and reported as maximum plant height 79 cm, No. of leaf/plant 17, leaf length 42.68cm, leaf width 1.90cm, leaf area 64.20cm², chlorophyll content 73.25 micro gram /cm² LAI, 4.52, leaf water equivalent thickness 0.18 g/cm² and wheat yield 4300 kg ha-1. The plant bio physical parameters were taken from LAI meter, Chlorophyll meter and Spectroradiometer. These parameters were taken as input parameters for PROSIAL model. The simulated data & ground data were used to get R² by linear correlation. The linear correlation between simulated and ground data during the wheat growing season gave high coefficient of determination (R²= 0.99) in SWIR band. Relationships between wave length and spectral response were drawn by relative spectral response (RSR) for 2nm intervals using Lagrange’s interpolation scheme. The empirical regression models were developed for the study area by using in situ field observation and LAI was calculated during growing to harvesting crop season 2015-2016. A spatial yield maps of the study area were generated using LAI values and yield data, LAI values and NDVI values of crop season 2015-2016. The LAI Vs yield regression model showed positive correlation with equation (Y = 11.70x - 2.041) and (R² = 0.94). The LAI Vs NDVI regression model also gave higher coefficient of determination equation (Y = 643.3x + 1108.86) (R² = 0.93) as well as lowest standard error 0.02

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