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Chandel, N. S.
- Study on Tractor Implement Combination and Optimum Field Capacity for some Selected Farms
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Authors
Affiliations
1 Department of Farm Machinery and Power Engineering, Punjab University, Ludhiana Punjab, IN
2 Department of Farm Machinery and Power Engineering, Facul ty of Agicul tural Engineering, Indira Gandhi Krishi Vishwavidyalaya, Raipur C.G., IN
3 Department of Agriculture and Food Engineering, Indian Institute of Technology, Kharagpur W.B., IN
4 Agricultural Mechanization Division, Central Institute of Agricultural Engineering, Bhopal M.P., IN
1 Department of Farm Machinery and Power Engineering, Punjab University, Ludhiana Punjab, IN
2 Department of Farm Machinery and Power Engineering, Facul ty of Agicul tural Engineering, Indira Gandhi Krishi Vishwavidyalaya, Raipur C.G., IN
3 Department of Agriculture and Food Engineering, Indian Institute of Technology, Kharagpur W.B., IN
4 Agricultural Mechanization Division, Central Institute of Agricultural Engineering, Bhopal M.P., IN
Source
International Journal of Agricultural Engineering, Vol 6, No 1 (2013), Pagination: 32–38Abstract
In this study, the optimum size of tractor and optimum field capacity requirements of implements for three different farms i.e., Agricultural Engineering Farm (AEF), Adhartal Farm (AF), and Dusty Acre Farm (DAF) of Jawaharlal Nehru Krishi Vishwa Vidyalaya Jabalpur was analyzed. Primary data were obtained through log book, history book and field survey of the university farms. Results showed that an optimum hp requirement for AEF was maximum (138.59hp). For DAF and AF it was 101.19 and 124.92 hp, respectively. The optimum field capacity of plough for all the three farm varied between 0.23 - 0.46 ha/h, cultivator was between 0.82 - 1.40 ha/h, disk harrow was between 0.90 - 1.52 ha/h and for seed drill was 1.00 - 2.01 ha/h when the labour cost varies between Rs. 100 - 180. For the selected farms the size of plough ranged between 2bottom-30cm to 4 bottom-35cm, the size of the cultivator and seed drill varied 9 - 19 tynes and for disk harrow between 8 - 16 disk.Keywords
Farm Equipment, Optimum Size, Power, Tractor- Digital Map-Based Site-Specific Granular Fertilizer Application System
Abstract Views :340 |
PDF Views:92
Authors
Affiliations
1 ICAR-Central Institute of Agricultural Engineering, Bhopal 462 038, IN
2 Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, IN
3 ICAR-Central Potato Research Institute, Shimla 171 001, IN
1 ICAR-Central Institute of Agricultural Engineering, Bhopal 462 038, IN
2 Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, IN
3 ICAR-Central Potato Research Institute, Shimla 171 001, IN
Source
Current Science, Vol 111, No 7 (2016), Pagination: 1208-1213Abstract
Variable rate application is the process of applying different rates of crop inputs according to the variability within an agricultural field. Variable rate fertilizer application is a technology that regulates the fertilizer application rate based on site-specific needs within a field. A GPS-based variable rate fertilizer application (VRFA) system was developed, which consisted of a differential global positioning system (DGPS), micro-processor, micro-controller, DC motor actuator, power supply, threaded screw arrangement and fluted roller metering mechanism. The digital soil nutrient availability and application maps for targeted yield were also developed. DGPS was used for real-time identification of grids. Based on the microcontroller algorithm, application rates were varied by changing the feed roller exposure length. The observed fertilizer application rate was 5 and 300 kg/ha for exposure length of 0 and 44 mm respectively. The results indicate that the fertilizer application rate changes according to the prescribed application rate at the identified grid with coefficient of variation (CV) of 11.7-15%. The values of ischolar_main mean square error and relative difference of the system for different levels of application rates were 2.62 and 3.71 respectively. It can be concluded that the developed VRFA system closely meets the target fertilizer application rate at the selected grid point.Keywords
Differential Global Positioning System, Fertilizer Applicator, Interpolation, Micro-Controller, Soil Nutrient Map.References
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- Yield Prediction in Wheat (Triticum aestivum L.) using Spectral Reflectance Indices
Abstract Views :184 |
PDF Views:76
Authors
N. S. Chandel
1,
P. S. Tiwari
1,
K. P. Singh
1,
D. Jat
1,
B. B. Gaikwad
1,
H. Tripathi
1,
K. Golhani
1
Affiliations
1 ICAR-Central Institute of Agricultural Engineering, Bhopal - 462 038, IN
1 ICAR-Central Institute of Agricultural Engineering, Bhopal - 462 038, IN
Source
Current Science, Vol 116, No 2 (2019), Pagination: 272-278Abstract
Influence of nitrogen on vegetative growth of wheat is significant, and can be monitored and assessed using vegetation indices derived from canopy reflectance at different phenological growth stages. The aim of the present work was to establish a regression model for yield prediction of wheat using spectral reflectance indices (SRIs), normalized difference nitrogen index (NDNI), normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and soil adjusted vegetation index (SAVI) for selected phenological growth stages of wheat. The canopy spectral reflectance was recorded during three winter seasons (2014–2017) for irrigated wheat. A hyperspectral library of canopy reflectance was developed, which enables the study of spectra independent of different nitrogen management practices. It indicated that the precise level of nitrogen for irrigated wheat may be 90 kg ha-1 in vertisols under agro-climatic of central India. Coefficient of variation (CV) was determined based on significance test between eight levels of nitrogen and SRI values. On the basis of CV, NDVI and NDWI were selected among the four spectral indices for the study of correlation between grain and biomass yields and nitrogen levels for four growth stages, viz. tillering, booting, heading and milking. A regression model was developed to find the best representative stage for yield prediction among the four stages. The regression model indicated that the relations of NDVI with grain and biomass yields were stronger in the heading stage, and it resulted in 96% accurate estimation of grain and biomass yields in irrigated wheat.Keywords
Nitrogen Management, Spectral Reflectance, Vegetation Indices, Wheat, Yield Estimation.References
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