Performance of Site‐Specific Nutrient Management for Irrigated Rice in Southeast China
Rice (Oryza sativa L.) yield increases in Zhejiang, China have slowed since 1985 despite the increasing use of hybrids and fertilizers. On‐farm experiments at 21 sites were conducted to evaluate a new approach for site‐specific nutrient management (SSNM). Field‐ and season‐specific N–P–K application...
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Veröffentlicht in: | Agronomy journal 2001-07, Vol.93 (4), p.869-878 |
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Sprache: | eng |
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Zusammenfassung: | Rice (Oryza sativa L.) yield increases in Zhejiang, China have slowed since 1985 despite the increasing use of hybrids and fertilizers. On‐farm experiments at 21 sites were conducted to evaluate a new approach for site‐specific nutrient management (SSNM). Field‐ and season‐specific N–P–K applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine‐tuned based on season‐specific rules and field‐specific monitoring of crop N status. The performance of SSNM was tested for four successive rice crops. Compared with the current farmers' fertilizer practice (FFP), average grain yield increased from 5.9 to 6.4 Mg ha−1 while plant N, P, and K uptake increased by 8 to 14%. The gross return over fertilizer cost was about 10% greater with SSNM than with FFP. Yields were about 20% greater in late rice (hybrid cultivars) than in early rice (inbred cultivars), but SSNM performed equally better than FFP in both seasons. Improved timing and splitting of fertilizer N increased N recovery efficiency from 0.18 kg kg−1 in FFP plots to 0.29 kg kg−1 in SSNM plots. The agronomic N use efficiency (grain yield increase per kilogram fertilizer applied) was 80% greater with SSNM than with FFP. As defined in our study, SSNM has potential for improving yields and nutrient efficiency in irrigated rice. Future research needs to develop a practical approach for achieving similar benefits across large areas without field‐specific modeling and with minimum crop monitoring. |
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ISSN: | 0002-1962 1435-0645 |
DOI: | 10.2134/agronj2001.934869x |