Dataset Information

Applying spectral fractal dimension index to predict the SPAD value of rice leaves under bacterial blight disease stress.

ABSTRACT:

Background

The chlorophyll content is a vital indicator for reflecting the photosynthesis ability of plants and it plays a significant role in monitoring the general health of plants. Since the chlorophyll content and the soil-plant analysis development (SPAD) value are positively correlated, it is feasible to predict the SPAD value by calculating the vegetation indices (VIs) through hyperspectral images, thereby evaluating the severity of plant diseases. However, current indices simply adopt few wavelengths of the hyperspectral information, which may decrease the prediction accuracy. Besides, few researches explored the applicability of VIs over rice under the bacterial blight disease stress.

Methods

In this study, the SPAD value was predicted by calculating the spectral fractal dimension index (SFDI) from a hyperspectral curve (420 to 950 nm). The correlation between the SPAD value and hyperspectral information was further analyzed for determining the sensitive bands that correspond to different disease levels. In addition, a SPAD prediction model was built upon the combination of selected indices and four machine learning methods.

Results

The results suggested that the SPAD value of rice leaves under different disease levels are sensitive to different wavelengths. Compared with current VIs, a stronger positive correlation was detected between the SPAD value and the SFDI, reaching an average correlation coefficient of 0.8263. For the prediction model, the one built with support vector regression and SFDI achieved the best performance, reaching R², RMSE, and RE at 0.8752, 3.7715, and 7.8614%, respectively.

Conclusions

This work provides an in-depth insight for accurately and robustly predicting the SPAD value of rice leaves under the bacterial blight disease stress, and the SFDI is of great significance for monitoring the chlorophyll content in large-scale fields non-destructively.

SUBMITTER: Cao Y

PROVIDER: S-EPMC9118648 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Applying spectral fractal dimension index to predict the SPAD value of rice leaves under bacterial blight disease stress.

Cao YiFei Y Xu Huanliang H Song Jin J Yang Yao Y Hu Xiaohui X Wiyao Korohou Tchalla KT Zhai Zhaoyu Z

Plant methods 20220518 1

<h4>Background</h4>The chlorophyll content is a vital indicator for reflecting the photosynthesis ability of plants and it plays a significant role in monitoring the general health of plants. Since the chlorophyll content and the soil-plant analysis development (SPAD) value are positively correlated, it is feasible to predict the SPAD value by calculating the vegetation indices (VIs) through hyperspectral images, thereby evaluating the severity of plant diseases. However, current indices simply ...[more]

PMID: 35585547

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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.

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Dataset Information

Applying spectral fractal dimension index to predict the SPAD value of rice leaves under bacterial blight disease stress.

Background

Methods

Results

Conclusions

Publications

Applying spectral fractal dimension index to predict the SPAD value of rice leaves under bacterial blight disease stress.

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