Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial
In recent years, global agriculture has encountered several challenges exacerbated by the effects of changes in climate, such as extreme water shortages for irrigation and heat waves. Water-deficit stress adversely affects the morpho-physiology of numerous crops, including soybean (<i>Glycine...
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| author | Md. Raihanul Islam Hasan Muhammad Abdullah Md Farhadur Rahman Mahfuzul Islam Abdul Kaium Tuhin Md Ashiquzzaman Kh Shakibul Islam Daniel Geisseler |
| author_facet | Md. Raihanul Islam Hasan Muhammad Abdullah Md Farhadur Rahman Mahfuzul Islam Abdul Kaium Tuhin Md Ashiquzzaman Kh Shakibul Islam Daniel Geisseler |
| author_sort | Md. Raihanul Islam |
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| description | In recent years, global agriculture has encountered several challenges exacerbated by the effects of changes in climate, such as extreme water shortages for irrigation and heat waves. Water-deficit stress adversely affects the morpho-physiology of numerous crops, including soybean (<i>Glycine max</i> L.), which is considered as promising crop in Bangladesh. Seaweed extract (SWE) has the potential to improve crop yield and alleviate the adverse effects of water-deficit stress. Remote and proximal sensing are also extensively utilized in estimating morpho-physiological traits owing to their cost-efficiency and non-destructive characteristics. The study was carried out to evaluate soybean morpho-physiological traits under the application of water extracts of <i>Gracilaria tenuistipitata</i> var. <i>liui</i> (red seaweed) with two varying irrigation water conditions (100% of total crop water requirement (TCWR) and 70% of TCWR). Principal component analysis (PCA) revealed that among the four treatments, the 70% irrigation + 5% (<i>v</i>/<i>v</i>) SWE and the 100% irrigation treatments overlapped, indicating that the application of SWE effectively mitigated water-deficit stress in soybeans. This result demonstrates that the foliar application of 5% SWE enabled soybeans to achieve morpho-physiological performance comparable to that of fully irrigated plants while reducing irrigation water use by 30%. Based on Pearson’s correlation matrix, a simple linear regression model was used to ascertain the relationship between unmanned aerial vehicle (UAV)-derived vegetation indices and the field-measured physiological characteristics of soybean. The Normalized Difference Red Edge (NDRE) strongly correlated with stomatal conductance (R<sup>2</sup> = 0.76), photosystem II efficiency (R<sup>2</sup> = 0.78), maximum fluorescence (R<sup>2</sup> = 0.64), and apparent transpiration rate (R<sup>2</sup> = 0.69). The Soil Adjusted Vegetation Index (SAVI) had the highest correlation with leaf relative water content (R<sup>2</sup> = 0.87), the Blue Normalized Difference Vegetation Index (bNDVI) with steady-state fluorescence (R<sup>2</sup> = 0.56) and vapor pressure deficit (R<sup>2</sup> = 0.74), and the Green Normalized Difference Vegetation Index (gNDVI) with chlorophyll content (R<sup>2</sup> = 0.73). Our results demonstrate how UAV and physiological data can be integrated to improve precision soybean farming and support sustainable soybean production under water-deficit stress. |
| format | Article |
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| spelling | doaj-art-87d2b6351ecc42e2974baa70bcbbdc112025-08-20T03:35:27ZengMDPI AGDrones2504-446X2025-07-019748710.3390/drones9070487Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field TrialMd. Raihanul Islam0Hasan Muhammad Abdullah1Md Farhadur Rahman2Mahfuzul Islam3Abdul Kaium Tuhin4Md Ashiquzzaman5Kh Shakibul Islam6Daniel Geisseler7GIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshGIS and Proximal Sensing Lab, Department of Agroforestry and Environment, Gazipur Agricultural University, Gazipur 1706, BangladeshDepartment of Land, Air and Water Resources, University of California, OneShields Avenue, Davis, CA 95616, USAIn recent years, global agriculture has encountered several challenges exacerbated by the effects of changes in climate, such as extreme water shortages for irrigation and heat waves. Water-deficit stress adversely affects the morpho-physiology of numerous crops, including soybean (<i>Glycine max</i> L.), which is considered as promising crop in Bangladesh. Seaweed extract (SWE) has the potential to improve crop yield and alleviate the adverse effects of water-deficit stress. Remote and proximal sensing are also extensively utilized in estimating morpho-physiological traits owing to their cost-efficiency and non-destructive characteristics. The study was carried out to evaluate soybean morpho-physiological traits under the application of water extracts of <i>Gracilaria tenuistipitata</i> var. <i>liui</i> (red seaweed) with two varying irrigation water conditions (100% of total crop water requirement (TCWR) and 70% of TCWR). Principal component analysis (PCA) revealed that among the four treatments, the 70% irrigation + 5% (<i>v</i>/<i>v</i>) SWE and the 100% irrigation treatments overlapped, indicating that the application of SWE effectively mitigated water-deficit stress in soybeans. This result demonstrates that the foliar application of 5% SWE enabled soybeans to achieve morpho-physiological performance comparable to that of fully irrigated plants while reducing irrigation water use by 30%. Based on Pearson’s correlation matrix, a simple linear regression model was used to ascertain the relationship between unmanned aerial vehicle (UAV)-derived vegetation indices and the field-measured physiological characteristics of soybean. The Normalized Difference Red Edge (NDRE) strongly correlated with stomatal conductance (R<sup>2</sup> = 0.76), photosystem II efficiency (R<sup>2</sup> = 0.78), maximum fluorescence (R<sup>2</sup> = 0.64), and apparent transpiration rate (R<sup>2</sup> = 0.69). The Soil Adjusted Vegetation Index (SAVI) had the highest correlation with leaf relative water content (R<sup>2</sup> = 0.87), the Blue Normalized Difference Vegetation Index (bNDVI) with steady-state fluorescence (R<sup>2</sup> = 0.56) and vapor pressure deficit (R<sup>2</sup> = 0.74), and the Green Normalized Difference Vegetation Index (gNDVI) with chlorophyll content (R<sup>2</sup> = 0.73). Our results demonstrate how UAV and physiological data can be integrated to improve precision soybean farming and support sustainable soybean production under water-deficit stress.https://www.mdpi.com/2504-446X/9/7/487soybeanirrigation water-deficit stressbiostimulantremote sensingmultispectral imagerysimple linear regression model |
| spellingShingle | Md. Raihanul Islam Hasan Muhammad Abdullah Md Farhadur Rahman Mahfuzul Islam Abdul Kaium Tuhin Md Ashiquzzaman Kh Shakibul Islam Daniel Geisseler Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial Drones soybean irrigation water-deficit stress biostimulant remote sensing multispectral imagery simple linear regression model |
| title | Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial |
| title_full | Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial |
| title_fullStr | Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial |
| title_full_unstemmed | Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial |
| title_short | Mitigation of Water-Deficit Stress in Soybean by Seaweed Extract: The Integrated Approaches of UAV-Based Remote Sensing and a Field Trial |
| title_sort | mitigation of water deficit stress in soybean by seaweed extract the integrated approaches of uav based remote sensing and a field trial |
| topic | soybean irrigation water-deficit stress biostimulant remote sensing multispectral imagery simple linear regression model |
| url | https://www.mdpi.com/2504-446X/9/7/487 |
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