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Recommended nitrogen rates and the verification of effects based on leaf SPAD readings of rice.

ABSTRACT: Modern rice production systems need a reliable, easy-to-use, efficient, and environmentally-friendly method to determine plant nitrogen (N) status , predict grain yield, and optimize N management. We conducted field experiments to determine the influence of different N rates on Soil Plant Analysis Development (SPAD) readings of rice leaves. We also performed field validations to evaluate the grain yield and N use efficiency under recommended N rates. Our results showed that leaf SPAD readings increased as N rates increased. We applied the recommended N based on the relationships between the N rates and leaf SPAD readings at the tillering and booting stages. The recommended N decreased N rates and improved N use efficiency without sacrificing grain yield. When compared to farmer practices (FP), the recommended N rates of optimization (OPT) decreased by 5.8% and 10.0%, respectively. In comparison with FP, the N agronomic efficiency of OPT increased by 5.8 and 10.0% while the partial factor productivity of N increased by 6.0 and 14.2%, respectively. The SPAD meter may be a reliable tool to analyze the N in rice, estimate real-time N fertilization, and improve N use efficiency.

SUBMITTER: Hou W

PROVIDER: S-EPMC8403476 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Recommended nitrogen rates and the verification of effects based on leaf SPAD readings of rice.

Hou Wenfeng W Shen Juan J Xu Weitao W Khan Muhammad Rizwan MR Wang Yin Y Zhou Xue X Gao Qiang Q Murtaza Behzad B Zhang Zhongqing Z

PeerJ 20210826

Modern rice production systems need a reliable, easy-to-use, efficient, and environmentally-friendly method to determine plant nitrogen (N) status , predict grain yield, and optimize N management. We conducted field experiments to determine the influence of different N rates on Soil Plant Analysis Development (SPAD) readings of rice leaves. We also performed field validations to evaluate the grain yield and N use efficiency under recommended N rates. Our results showed that leaf SPAD readings in ...[more]

PMID: 34527449

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Project description:Many fertilization models have been created to scientifically determine the amount of fertilization. With the same purpose, we constructed a nitrogen (N) application model, the leaf value model, which can make N fertilizer decisions in a timely, fast and nondestructive manner during rice planting. However, only one area (A1, Jiuzhou Town, Xixiu District, Guizhou Province) and one cultivar (Qyou6) were involved in the construction of the leaf value model. Its stability and applicability could not be well evaluated. Thus, we chose another area (A2, Jiuzhou Town, Huangping County, Guizhou Province) in Guizhou Province and carried out the experiment by using four cultivars (Nie5you5399, Qyou6, Yixiangyou2115 and Zhongzheyou8) for the leaf value model construction. Compared with the average value of apparent total N uptake (Nz) obtained in 2 years in the A1 area, that in the Qyou6 leaf value model in the A2 area increased by 12%, reaching 635.72 kg ha-1, whereas the corresponding target yield changed slightly, reaching 10,999.90 kg ha-1. Simultaneously, the linear relationship between several good SPAD value-derived indexes (Ys) and apparent N supply of the field (Nx) was still significant or extremely significant in the Qyou6 leaf value model. Compared with the A1 area, it slightly differed, and the R2 of SPADL1 was higher than that of SPADL3×L4/mean. In the leaf value model of the other three cultivars, the relationship between yield and Nx and that between Ys and Nx were significant or extremely significant. The Nz of Yixiangyou2115 and Zhongzheyou8 (618.33 and 617.76 kg ha-1) were close to that of Qyou6 and the corresponding target yields were 10313.36 and 10301.99 kg ha-1, respectively. The Nz and target yield of Nie5you5399 were lowest at 546.63 and 10680.24 kg ha-1, respectively. In general, this study showed that relationships used in the construction of leaf value model had certain stability and applicability to difference areas and cultivars. The leaf value model can be considered in N fertilizer decision-making of rice planting management.

Project description:Nitrogen (N) is the most essential element for growth, development, and grain yield determination in crops. However, excessive nitrogen application can result in environmental pollution and greenhouse gas emissions that contribute to climate change. In this study, we used 158 rice genetic resources to evaluate the relationships between the soil and plant analysis development (SPAD) value and grain yield (GY) and its components. The SPAD value ranged between 30.5 and 55.8, with a mean of 41.7 ± 5.3, under normal nitrogen conditions (NN, 9 kg/10a), and between 27.5 and 52.3, with a mean of 38.6 ± 4.8, under low nitrogen conditions (LN, 4.5 kg/10a). Under NN conditions, the SPAD values were in the following order: japonica (43.5 ± 5.8), Tongil-type (41.7 ± 2.5), others (41.7 ± 5.2), and indica (38.3 ± 3.8). By contrast, under LN conditions, the SPAD values were in the following order: Tongil-type (40.4 ± 2.1), others (40.1 ± 4.5), japonica (39.6 ± 5.2), and indica (35.6 ± 3.9). The 158 genetic resources showed no correlation between SPAD and yield. Therefore, the low-decrease rate (LDR) and high-decrease rate (HDR) SPAD groups were selected to reanalyze the relationships between the surveyed traits. The SPAD values were positively correlated with 1000-grain weight (TGW) for both LDR and HDR groups (NN: 0.63, LN: 0.53), However, SPAD and GY were positively correlated only in the LDR group. For TGW, the coefficient of determination (R 2) was 20% and 13% under NN and LN conditions, respectively. For GY, R 2 values of 32% and 52% were observed under NN and LN conditions, respectively. Genetic resources with higher SPAD values in the LDR group exhibited the highest yield (NN: 1.19 kg/m2, LN: 1.04 kg/m2) under both NN and LN conditions. In conclusion, we selected 10 genetic resources that exhibited higher GY under both NN and LN conditions with minimal yield reductions. These genetic resources represent valuable breeding materials for nitrogen deficiency adaptation.

Project description:Accurate estimations of the vertical leaf nitrogen (N) distribution within a rice canopy is helpful for understanding the nutrient supply and demand of various functional leaf layers of rice and for improving the predictions of rice productivity. A two-year field experiment using different rice varieties, N rates, and planting densities was performed to investigate the vertical distribution of the leaf nitrogen concentration (LNC, %) within the rice canopy, the relationship between the LNC in different leaf layers (LNCLi, i = 1, 2, 3, 4), and the relationship between the LNCLi and the LNC at the canopy level (LNCCanopy). A vertical distribution model of the LNC was constructed based on the relative canopy height. Furthermore, the relationship between different vegetation indices (VIs) and the LNCCanopy, the LNCLi, and the LNC vertical distribution model parameters were studied. We also compared the following three methods for estimating the LNC in different leaf layers in rice canopy: (1) estimating the LNCCanopy by VIs and then estimating the LNCLi based on the relationship between the LNCLi and LNCCanopy; (2) estimating the LNC in any leaf layer of the rice canopy by VIs, inputting the result into the LNC vertical distribution model to obtain the parameters of the model, and then estimating the LNCLi using the LNC vertical distribution model; (3) estimating the model parameters by using VIs directly and then estimating the LNCLi by the LNC vertical distribution model. The results showed that the LNC in the bottom of rice canopy was more susceptible to different N rates, and changes in the LNC with the relative canopy height could be simulated by an exponential model. Vegetation indices could estimate the LNC at the top of rice canopy. R705/(R717+R491) (R2 = 0.763) and the renormalized difference vegetation index (RDVI) (1340, 730) (R2 = 0.747) were able to estimate the parameter "a" of the LNC vertical distribution model in indica rice and japonica rice, respectively. In addition, method (2) was the best choice for estimating the LNCLi (R2 = 0.768, 0.700, 0.623, and 0.549 for LNCL1, LNCL2, LNCL3, and LNCL4, respectively). These results provide technical support for the rapid, accurate, and non-destructive identification of the vertical distribution of nitrogen in rice canopies.

Project description:Farmers in low-elevation coastal zones in South Asia face numerous food security and environmental sustainability challenges. This study evaluated the effects of nitrogen (N) rate and source on the agronomic, economic, and environmental performance of transplanted and rainfed 'aman' (monsoon-season) rice in Bangladesh's non-saline coastal areas. Fifty-one farmers participated in trials distributed across two landscape positions described as 'highlands' (on which field water inundation depth typically remains <30 cm) and 'medium-highlands' (inundation depths 30-90 cm) planted singly with varieties appropriate to each position (BRRI dhan 39 for highlands and the traditional variety Bhushiara for medium-highlands). Researcher designed but farmer-managed dispersed plots were located across three district sub-units (Barisal Sadar, Hizla, Mehendigonj) and compared N source (broadcast prilled urea or deep-placed urea super granules (USG)) at four N rates. Rice grown on medium-highlands did not respond to increasing N rates beyond 28 kg N ha-1, indicating that little fertilization is required to maintain yields and profitability while limiting environmental externalities. In highland locations, clear trade-offs between agronomic and environmental goals were observed. To increase yields and profits for BRRI dhan 39, 50 or 75 kg N ha-1 was often needed, although these rates were associated with declining energy and increasing greenhouse gas (GHG) efficiencies. Compared to prilled urea, USG had no impact on yield, economic, energy and GHG efficiencies in medium-highland locations. USG conversely led to 4.2-5.8% yield improvements at higher N rates on highlands, while also increasing energy efficiency. Given the observed yield, agronomic and economic benefit of USG, our preliminary results that farmers can consider use of USG at 50 kg N ha-1 to produce yields equivalent to 75 kg N ha-1 of prilled urea in highland landscapes, while also reducing environmental externalities. These results suggest that when assessing sustainable intensification (SI) strategies for rice in South Asia's coastal zones, N requirements should be evaluated within specific production contexts (e.g. cultivar type within landscape position) to identify options for increasing yields without negatively influencing environmental and economic indicators. Similar studies in other parts of coastal South Asia could help policy-makers prioritize investments in agriculture with the aim of improving rice productivity while also considering income generation and environmental outcomes.

Project description:Rapid and non-destructive diagnostic tools to accurately assess crop nitrogen nutrition index (NNI) are imperative for improving crop nitrogen (N) diagnosis and sustaining crop production. This study was aimed to develop the relationships among NNI, leaf N gradient, chlorophyll meter (CM) readings gradient, and positional differences chlorophyll meter index [PDCMI, the ratio of CM readings between different leaf layers (LLs) of crop canopy] and to validate the accuracy and stability of these relationships across the different LLs, years, sites, and cultivars. Six multi-N rates (0-320 kg ha-1) field experiments were conducted with four summer maize cultivars (Zhengdan958, Denghai605, Xundan20, and Denghai661) at two different sites located in China. Six summer maize plants per plot were harvested at each sampling stage to assess NNI, leaf N concentration and CM readings of different LLs during the vegetative growth period. The results showed that the leaf N gradient, CM readings gradient and PDCMI of different LLs decreased, while the NNI values increased with increasing N supply. The leaf N gradient and CM readings gradient increased gradually from top to bottom of the canopy and CM readings of the bottom LL were more sensitive to changes in plant N concentration. The significantly positive relationship between NNI and CM readings of different LLs (LL1 to LL3) was observed, yet these relationships varied across the years. In contrast, the relationships between NNI and PDCMI of different LLs (LL1 to LL3) were significantly negative. The strongest relationship between PDCMI and NNI which was stable across the cultivars and years was observed for PDCMI1-3 (NNI = -5.74 × PDCMI1-3+1.5, R2 = 0.76**). Additionally, the models developed in this study were validated with the data acquired from two independent experiments to assess their accuracy of prediction. The root mean square error value of 0.1 indicated that the most accurate and robust relationship was observed between PDCMI1-3 and NNI. The projected results would help to develop a simple, non-destructive and reliable approach to accurately assess the crop N status for precisely managing N application during the growth period of summer maize crop.

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Recommended nitrogen rates and the verification of effects based on leaf SPAD readings of rice.

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Recommended nitrogen rates and the verification of effects based on leaf SPAD readings of rice.

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