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Spatial Variability of Bt Cotton On-farm Situation: A Survey

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The survey was carried out during November 2015 in selected cotton fields of seven villages viz., Kalmala, Jagir Venkatapur and Ijapur of Raichur district and Gogi, Ulalkal, Hothpet and Maddarki villages of Yadgir districts covering part of TBP and UKP irrigation commands, respectively. The villages were selected based on the predominance of cotton area. Farmers plots were visited and location were  recorded using GPS and observations were made on management practices, leaf reddening incidence and per cent leaf reddening, NDVI values, chlorophyll content, anthocyanin content and seed cotton yield. The spatial variability maps were generated using “krigging”, and interpolation method under GIS environment using observations on spatial spectral variability in NDVI, SPAD (chlorophyll content), anthocyanin content, leaf reddening index, reddening percentage and seed cotton as influenced by irrigation ecosystem, soil type and foliar spray of 19:19:19, date of sowing and cultivars. The data was further subjected for correlation studies. There is a lot of variation in the seed cotton yields among Bt cotton farmers across the Upper Krishna project and Tunga Bhadra Project irrigation commands of the state. Soils cultivated and cultivars used often remain the same the difference in yield could be due to nutritional management, the occurrence of leaf reddening, other factors, or combination of many of these attributing characteristics. Since leaf health is indicative of plant health and yield in turn, leaf health could be assessed through leaf spectral reflectance viz, NDVI, SPAD, and LRI. Based on this a survey was undertaken in November 2015 at Raichur (in three taluks) and Yadgir (in four taluks) districts falling under TBP and UKP irrigation commands, respectively, taking in all 90 farmers. The spectral observations were made on standing field crops besides leaf samples were collected to estimate leaf anthocyanin in the laboratory and GIS mapping was done using ESRI-made ArcGIS version 10.4 from Sujala-III, Remote Sensing and GIS laboratory, College of Agriculture, Raichur, was used to import GPS data and field data attachment for spatial analysis of leaf reddening incidence in cotton.  The results on Spectral observations on NDVI, SPAD, leaf reddening index, reddening percentage in addition to leaf anthocyanin content varied due to locations, irrigation or otherwise, foliar spray, fertilization level, date of sowing, and cultivars.The leaf chlorophyll content is an important biometric character, the content quality, and duration (stability) indicate general crop health and ultimately yield directly if not influenced by the rate and efficiency of translocation to sink (kapas yield in case of cotton), therefore, it is often used to monitor real-timeN fertilization (LCC, SPAD, Green Seeker) as well as to forecast crop condition and yield. Periodic spectral observations on SPAD and NDVI are useful indicators of crop health and performance in commercial crop like cotton which could be extrapolated to field scale for crop management and production forecast.
Title: Spatial Variability of Bt Cotton On-farm Situation: A Survey
Description:
The survey was carried out during November 2015 in selected cotton fields of seven villages viz.
, Kalmala, Jagir Venkatapur and Ijapur of Raichur district and Gogi, Ulalkal, Hothpet and Maddarki villages of Yadgir districts covering part of TBP and UKP irrigation commands, respectively.
The villages were selected based on the predominance of cotton area.
Farmers plots were visited and location were  recorded using GPS and observations were made on management practices, leaf reddening incidence and per cent leaf reddening, NDVI values, chlorophyll content, anthocyanin content and seed cotton yield.
The spatial variability maps were generated using “krigging”, and interpolation method under GIS environment using observations on spatial spectral variability in NDVI, SPAD (chlorophyll content), anthocyanin content, leaf reddening index, reddening percentage and seed cotton as influenced by irrigation ecosystem, soil type and foliar spray of 19:19:19, date of sowing and cultivars.
The data was further subjected for correlation studies.
There is a lot of variation in the seed cotton yields among Bt cotton farmers across the Upper Krishna project and Tunga Bhadra Project irrigation commands of the state.
Soils cultivated and cultivars used often remain the same the difference in yield could be due to nutritional management, the occurrence of leaf reddening, other factors, or combination of many of these attributing characteristics.
Since leaf health is indicative of plant health and yield in turn, leaf health could be assessed through leaf spectral reflectance viz, NDVI, SPAD, and LRI.
Based on this a survey was undertaken in November 2015 at Raichur (in three taluks) and Yadgir (in four taluks) districts falling under TBP and UKP irrigation commands, respectively, taking in all 90 farmers.
The spectral observations were made on standing field crops besides leaf samples were collected to estimate leaf anthocyanin in the laboratory and GIS mapping was done using ESRI-made ArcGIS version 10.
4 from Sujala-III, Remote Sensing and GIS laboratory, College of Agriculture, Raichur, was used to import GPS data and field data attachment for spatial analysis of leaf reddening incidence in cotton.
  The results on Spectral observations on NDVI, SPAD, leaf reddening index, reddening percentage in addition to leaf anthocyanin content varied due to locations, irrigation or otherwise, foliar spray, fertilization level, date of sowing, and cultivars.
The leaf chlorophyll content is an important biometric character, the content quality, and duration (stability) indicate general crop health and ultimately yield directly if not influenced by the rate and efficiency of translocation to sink (kapas yield in case of cotton), therefore, it is often used to monitor real-timeN fertilization (LCC, SPAD, Green Seeker) as well as to forecast crop condition and yield.
Periodic spectral observations on SPAD and NDVI are useful indicators of crop health and performance in commercial crop like cotton which could be extrapolated to field scale for crop management and production forecast.

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