Integrating Hyperspectral Reflectance-Based Phenotyping and SSR Marker-Based Genotyping for Assessing the Salt Tolerance of Wheat Genotypes under Real Field Conditions DOI Creative Commons
Salah El-Hendawy, Muhammad Bilawal Junaid,

Nasser Al-Suhaibani

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(18), P. 2610 - 2610

Published: Sept. 19, 2024

Wheat breeding programs are currently focusing on using non-destructive and cost-effective hyperspectral sensing tools to expeditiously accurately phenotype large collections of genotypes. This approach is expected accelerate the development abiotic stress tolerance genotypes in programs. study aimed assess salt wheat canopy spectral reflectance measurements as an alternative direct laborious time-consuming phenological selection criteria. Eight sixteen F8 RILs were tested under 150 mM NaCl real field conditions for two years. Fourteen indices (SRIs) calculated from data, including vegetation SRIs water SRIs. The effectiveness these assessing was compared with four morpho-physiological traits genetic parameters, SSR markers, Mantel test, hierarchical clustering heatmaps, stepwise multiple linear regression, principal component analysis (PCA). results showed significant differences (p ≤ 0.001) among RILs/cultivars both heritability, gain, genotypic phenotypic coefficients variability most comparable those measured traits. effectively differentiated between salt-tolerant sensitive exhibited strong correlations markers (R2 = 0.56–0.89), similar allelic data 34 SSRs. A correlation (r 0.27, p < 0.0001) found similarity which higher than that 0.20, 0.0003) based test. PCA indicated all grouped a positive direction identified RILs/cultivars. PLSR models, SRIs, robustly estimated various individual suggests can be integrated tool phenotyping screening populations short time frame. replace need traditional

Language: Английский

Developing an IoT-driven delta robot to stimulate the growth of mulberry branch cuttings cultivated aeroponically using machine vision technology DOI
Osama Elsherbiny, Jianmin Gao, Ming Ma

et al.

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 232, P. 110111 - 110111

Published: Feb. 11, 2025

Language: Английский

Citations

1
What Is the Predictive Capacity of Sesamum indicum L. Bioparameters Using Machine Learning with Red–Green–Blue (RGB) Images? DOI Creative Commons
Edimir Xavier Leal Ferraz, Alan Cézar Bezerra, Raquele Mendes de Lira

et al.

AgriEngineering, Journal Year: 2025, Volume and Issue: 7(3), P. 64 - 64

Published: March 3, 2025

The application of machine learning techniques to determine bioparameters, such as the leaf area index (LAI) and chlorophyll content, has shown significant potential, particularly with use unmanned aerial vehicles (UAVs). This study evaluated RGB images obtained from UAVs estimate bioparameters in sesame crops, utilizing data selection methods. experiment was conducted at Federal Rural University Pernambuco involved using a portable AccuPAR ceptometer measure LAI spectrophotometry photosynthetic pigments. Field were captured DJI Mavic 2 Enterprise Dual remotely piloted aircraft equipped thermal cameras. To manage high dimensionality data, CRITIC Pearson correlation methods applied select most relevant indices for XGBoost model. divided into training, testing, validation sets ensure model generalization, performance assessed R2, MAE, RMSE metrics. effectively estimated LAI, a, total chlorophyll, carotenoids (R2 > 0.7) but had limited b. found be effective method algorithm.

Language: Английский

Citations

0
Adaptive meta-modeling of evapotranspiration in arid agricultural regions of Saudi Arabia using climatic factors, drought indices and MODIS data DOI
Osama Elsherbiny, Salah Elsayed, Obaid Aldosari

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 59, P. 102279 - 102279

Published: March 17, 2025

Language: Английский

Citations

0
A comprehensive review on rice responses and tolerance to salt stress DOI Creative Commons

Obed Kweku Sackey,

Naijie Feng, Y A Mohammed

et al.

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 16

Published: March 31, 2025

The challenge of salinity stress significantly impacts global rice production, especially in coastal and arid regions where the salinization agricultural soils is on rise. This review explores complex physiological, biochemical, genetic mechanisms contributing to tolerance (Oryza sativa L.) while examining agronomic multidisciplinary strategies bolster resilience. Essential adaptations encompass regulation ionic balance, management antioxidants, adjustments osmotic pressure, all driven by genes such as OsHKT1;5 transcription factors like OsbZIP73. evolution breeding strategies, encompassing traditional methods cutting-edge innovations, has produced remarkable salt-tolerant varieties FL478 BRRI dhan47. advancements this field are enhanced including integrated soil management, crop rotation, chemical treatments spermidine, which through antioxidant activity transcriptional mechanisms. Case studies from South Asia, Sub-Saharan Africa, Middle East and, Australia demonstrate transformative potential utilizing varieties; however, challenges persist, polygenic nature tolerance, environmental variability, socioeconomic barriers. highlights importance collaborative efforts across various disciplines, merging genomic technologies, sophisticated phenotyping, inclusive practices foster climate-resilient sustainable cultivation. work seeks navigate complexities its implications for food security, employing inventive cohesive confront posed climate change.

Language: Английский

Citations

0
Potential of RGB Spectral Information in the Selection of Wheat (Triticum aestivum L.) Genotypes Adapted to Early Drought and Salinity Stresses DOI Creative Commons
Alan Mário Zuffo, Francisco Charles dos Santos Silva, Ricardo Mezzomo

et al.

Journal of Agronomy and Crop Science, Journal Year: 2025, Volume and Issue: 211(3)

Published: April 11, 2025

ABSTRACT Wheat ( Triticum aestivum L.) is one of the world's main cereals, with considerable potential for expansion in tropical regions such as Brazilian Cerrado. However, abiotic stresses, drought and salinity, present significant challenges cultivation this species region. This challenge can be overcome by selecting cultivars that are tolerant to these stresses. study investigated using RGB spectral information from wheat seedlings a rapid nondestructive tool identify genotypes adapted salinity stress conditions. Seeds 11 were sown under nonstressful (control) stressful (drought salinity) The evaluated germination morphological traits, images obtained via low‐cost platform analysis. data subjected analysis variance, correlation, calculation WAASB multitrait stability index greatest adaptation stability. (ExGR, ExR, VEG, RED, GREEN BLUE) proved efficient selection conditions during initial seedling growth stage. ORS FEROZ BRS 404 have high both Additionally, used parents crossing blocks obtain better

Language: Английский

Citations

0
RGB Indices Can Be Used to Estimate NDVI, PRI, and Fv/Fm in Wheat and Pea Plants Under Soil Drought and Salinization DOI Creative Commons

Yuriy Zolin,

Alyona Popova, Lyubov Yudina

et al.

Plants, Journal Year: 2025, Volume and Issue: 14(9), P. 1284 - 1284

Published: April 23, 2025

Soil drought and salinization are key abiotic stressors for agricultural plants; the development of methods their early detection is an important applied task. Measurement red-green-blue (RGB) indices, which calculated on basis color images, a simple method proximal remote sensing plant health under action stressors. Potentially, RGB indices can be used to estimate narrow-band reflectance and/or photosynthetic parameters in plants. Analysis this problem was main task current work. We investigated relationships six (r, g, b, ExG, VEG, VARI) widely (the normalized difference vegetation index, NDVI, photochemical PRI) potential quantum yield photosystem II (Fv/Fm) wheat pea plants soil salinization. It shown that PRI, Fv/Fm were significantly changed both stressors; changes some (e.g., ExG) initiated stage or Correlation analysis showed (especially, VARY, g) strongly related Fv/Fm; linear regressions between these values calculated. means measured by low-cost cameras (NDVI, Fv/Fm) requiring sophisticated equipment measure.

Language: Английский

Citations

0
Assessment of salt tolerance in peas using machine learning and multi-sensor data DOI Creative Commons
Zehao Liu, Qiyan Jiang, Yishan Ji

et al.

Plant Stress, Journal Year: 2025, Volume and Issue: unknown, P. 100902 - 100902

Published: May 1, 2025

Language: Английский

Citations

0
Integrating Hyperspectral Reflectance-Based Phenotyping and SSR Marker-Based Genotyping for Assessing the Salt Tolerance of Wheat Genotypes under Real Field Conditions DOI Creative Commons
Salah El-Hendawy, Muhammad Bilawal Junaid,

Nasser Al-Suhaibani

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(18), P. 2610 - 2610

Published: Sept. 19, 2024

Wheat breeding programs are currently focusing on using non-destructive and cost-effective hyperspectral sensing tools to expeditiously accurately phenotype large collections of genotypes. This approach is expected accelerate the development abiotic stress tolerance genotypes in programs. study aimed assess salt wheat canopy spectral reflectance measurements as an alternative direct laborious time-consuming phenological selection criteria. Eight sixteen F8 RILs were tested under 150 mM NaCl real field conditions for two years. Fourteen indices (SRIs) calculated from data, including vegetation SRIs water SRIs. The effectiveness these assessing was compared with four morpho-physiological traits genetic parameters, SSR markers, Mantel test, hierarchical clustering heatmaps, stepwise multiple linear regression, principal component analysis (PCA). results showed significant differences (p ≤ 0.001) among RILs/cultivars both heritability, gain, genotypic phenotypic coefficients variability most comparable those measured traits. effectively differentiated between salt-tolerant sensitive exhibited strong correlations markers (R2 = 0.56–0.89), similar allelic data 34 SSRs. A correlation (r 0.27, p < 0.0001) found similarity which higher than that 0.20, 0.0003) based test. PCA indicated all grouped a positive direction identified RILs/cultivars. PLSR models, SRIs, robustly estimated various individual suggests can be integrated tool phenotyping screening populations short time frame. replace need traditional

Language: Английский

Citations

1