Development of Chlorophyll-Meter-Index-Based Dynamic Models for Evaluation of High-Yield Japonica Rice Production in Yangtze River Reaches
| Autor: | Xiaojun Liu, Ke Zhang, Weixing Cao, Qiang Cao, Syed Tahir Ata-Ul-Karim, Yongchao Tian, Yan Zhu, Jingshan Lu, Songyang Li, Brian Krienke |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
Index (economics) Oryza sativa nitrogen nutrition index grain yield leaf nitrogen concentration lcsh:S food and beverages Ripening 04 agricultural and veterinary sciences Spatial distribution dynamic model 01 natural sciences Japonica rice lcsh:Agriculture Horticulture SPAD Human fertilization Yield (chemistry) 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Cultivar Agronomy and Crop Science 010606 plant biology & botany Mathematics |
| Zdroj: | Agronomy, Vol 9, Iss 2, p 106 (2019) Agronomy Volume 9 Issue 2 |
| ISSN: | 2073-4395 |
| Popis: | Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analysis development (SPAD) index (the normalized difference SPAD indexes, NDSIs) between the upper (the first and second leaves from the top), and lower (the third and fourth leaves from the top) leaves of Japonica rice. Four multi-location, multi-N rate (0&ndash 390 kg ha&minus 1) field experiments were conducted using seven Japonica rice cultivars (9915, 27123, Wuxiangjing14, Wunyunjing19, Wunyunjing24, Liangyou9, and Yongyou8). Growth analyses were performed at different growth stages ranging from tillering (TI) to the ripening period (RP). We measured leaf N concentration (LNC), the N nutrition index (NNI), the NDSI, and rice grain yield at maturity. The relationships among the NDSI, LNC, and NNI at different growth stages showed that the NDSI values of the third and fourth fully expanded leaves more reliably reflected the N nutritional status than those of the first and second fully expanded leaves (LNC: NDSIL3,4, R2 > 0.81 NDSIothers, 0.77 > R2 > 0.06 NNI: NDSIL3,4, R2 > 0.83 NDSIothers, 0.76 > 0.07 all p < 0.01). Two new diagnostic models based on the NDSIL3,4 (from the tillering to the ripening period) can be used for effective diagnosis of the LNC and NNI, which exhibited reasonable distributions of residuals (LNC: relative root mean square error (RRMSE) = 0.0683 NNI: RRMSE = 0.0688 p < 0.01). The relationship between grain yield, predicted yield, and NDSIL3,4 were established during critical growth stages (from the stem elongation to the heading stages R2 = 0.53, p < 0.01, RRMSE = 0.106). An NDSIL3,4 high-yield change curve was drawn to describe critical NDSIL3,4 values for a high-yield target (10.28 t ha&minus 1). Furthermore, dynamic-critical curve models based on the NDSIL3,4 allowed a precise description of rice N status, facilitating the timing of fertilization decisions to optimize yields in the intensive rice cropping systems of eastern China. |
| Databáze: | OpenAIRE |
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