000			03749nab|a22004577a|4500
001			64539
003			MX-TxCIM
005			20240919020918.0
008			202201s2022||||ne |||p|op||||00||0|eng|d
022			_a03784290
024	8		_ahttps://doi.org/10.1016/j.fcr.2021.108328
040			_aMX-TxCIM
041			_aeng
100	0		_aHari S. Nayak _98233
245	1	0	_aRice yield gaps and nitrogen-use efficiency in the Northwestern Indo-Gangetic Plains of India : _bevidence based insights from heterogeneous farmers’ practices
260			_aAmsterdam (Netherlands) : _bElsevier, _c2022.
500			_aPeer review
500			_aOpen Access
520			_aA large database of individual farmer field data (n = 4,107) for rice production in the Northwestern Indo-Gangetic Plains of India was used to decompose rice yield gaps and to investigate the scope to reduce nitrogen (N) inputs without compromising yields. Stochastic frontier analysis was used to disentangle efficiency and resource yield gaps, whereas data on rice yield potential in the region were retrieved from the Global Yield Gap Atlas to estimate the technology yield gap. Rice yield gaps were small (ca. 2.7 t ha−1, or 20% of potential yield, Yp) and mostly attributed to the technology yield gap (ca. 1.8 t ha−1, or ca. 15% of Yp). Efficiency and resource yield gaps were negligible (less than 5% of Yp in most districts). Small yield gaps were associated with high input use, particularly irrigation water and N, for which small yield responses were observed. N partial factor productivity (PFP-N) was 45–50 kg grain kg−1 N for fields with efficient N management and approximately 20% lower for the fields with inefficient N management. Improving PFP-N appears to be best achieved through better matching of N rates to the variety types cultivated and by adjusting the amount of urea applied in the 3rd split in correspondance with the amount of diammonium-phosphate applied earlier in the season. Future studies should assess the potential to reduce irrigation water without compromising rice yield and to broaden the assessment presented here to other indicators and at the cropping systems level.
546			_aText in English
591			_aKakraliya Suresh Kumar : Not in IRS Staff list but CIMMYT Affiliation
597			_aNutrition, health & food security _bTransforming Agrifood Systems in South Asia _cResilient Agrifood Systems _dUnited States Agency for International Development _dCGIAR Trust Fund _dBill & Melinda Gates Foundation _uhttps://hdl.handle.net/10568/126860
650		7	_aData _2AGROVOC _99002
650		7	_aStochastic models _2AGROVOC _96445
650		7	_aYield gap _2AGROVOC _91356
650		7	_aFertilizers _2AGROVOC _91111
650		7	_aSustainability _2AGROVOC _91283
700	1		_aSilva, J.V. _8001712458 _gSustainable Intensification Program _gSustainable Agrifood Systems _99320
700	1		_aParihar, C.M. _91486
700	0		_aKakraliya Suresh Kumar _96321
700	1		_aKrupnik, T.J. _gSustainable Intensification Program _gSustainable Agrifood Systems _8INT3222 _9906
700	1		_aBijarniya, D. _94727
700	1		_aJat, M.L. _gFormerly Sustainable Intensification Program _gFormerly Sustainable Agrifood Systems _8INT3072 _9889
700	1		_aSharma, P.C. _92439
700	1		_aJat, H.S. _95697
700	1		_aSidhu, H.S. _gFormerly Borlaug Institute for South Asia _8INT3482 _9961
700	1		_aSapkota, T.B. _gSustainable Intensification Program _gSustainable Agrifood Systems _8INT3361 _9940
773	0		_tField Crops Research _gv. 275, art. 108328 _dAmsterdam (Netherlands) : Elsevier, 2022. _x0378-4290 _wG444314
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/21736
942			_cJA _n0 _2ddc
999			_c64539 _d64531