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Nagarjuna Kumar, R.
- Assessing Unrealized Yield Potential of Maize Producing Districts in India
Abstract Views :282 |
PDF Views:78
Authors
B. M. K. Raju
1,
C. A. Rama Rao
1,
K. V. Rao
1,
Srinivasarao
1,
Josily Samuel
1,
A. V. M. Subba Rao
1,
M. Osman
1,
M. Srinivasa Rao
1,
N. Ravi Kumar
1,
R. Nagarjuna Kumar
1,
V. V. Sumanth Kumar
2,
K. A. Gopinath
1,
N. Swapna
1
Affiliations
1 ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad 500 059, IN
2 International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Hyderabad 502 324, IN
1 ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad 500 059, IN
2 International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Hyderabad 502 324, IN
Source
Current Science, Vol 114, No 09 (2018), Pagination: 1885-1893Abstract
The projected demand of maize production in India in 2050 is 4–5 times of current production. With the scope for area expansion being limited, there is need for enhancement of yield. This calls for identifying areas where huge unrealized yield potential exists. With a view to address the issue, the present study delineates homogeneous agro-climatic zones for maize production system in India taking district as a unit and using the factors production, viz. climate, soil, season and irrigated area under the crop. There are 146 districts in India that grow maize as a major crop. They were divided into 26 zones using multivariate cluster analysis. Study of variation in yield between districts within a zone vis-a-vis crop management practices adopted in those districts was found useful in targeting the yield gaps. These findings can have direct relevance to the maize farmers and district level administrators.Keywords
Agro-Climatic Zone, Climate, Cluster, Irrigation, Potential Yield, Yield Gap.Full Text
References
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- Spatial Rice Decision Support System for Effective Rice Crop Management
Abstract Views :253 |
PDF Views:84
Authors
B. Sailaja
1,
S. R. Voleti
1,
D. Subrahmanyam
1,
P. Raghuveer Rao
1,
S. Gayatri
1,
R. Nagarjuna Kumar
2,
Shaik N. Meera
1
Affiliations
1 Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, IN
2 Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad - 500 059, IN
1 Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, IN
2 Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad - 500 059, IN
Source
Current Science, Vol 116, No 3 (2019), Pagination: 412-421Abstract
Rice, a widely grown crop all over the world provides food security to millions of people. The average productivity of rice in India is still low due to diversified environments under which it is being cultivated. Prediction and assessment of rice yields needs simplified precision models. A spatial rice decision support system (SRDSS) was designed by integrating ClimGen climate model and Oryza2000 crop model with soil and weather layers. This DSS facilitates input model parameters and geo-referenced maps to predict rice yield at polygon/pixel level. SRDSS is useful to researchers and planners not only in estimating rice yield but also to estimate optimum crop sowing dates and management practices to achieve target yield for the selected location. Further, SRDSS will be integrated with weather sensors to generate real time advisories to farmers at each level of decision making and to plan and achieve the targets of doubling the farmer’s income by 2022.Keywords
ARCGIS, ClimGen, Oryza2000, Rice Yield, SRDSS.Full Text
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