Assessing Drought Stress of Sugarcane Cultivars Using Unmanned Vehicle System (UAS)-Based Vegetation Indices and Physiological Parameters

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(8), P. 1433 - 1433

Published: April 18, 2024

Sugarcane breeding for drought tolerance is a sustainable strategy to cope with drought. In addition biotechnology, high-throughput phenotyping has become an emerging tool plant breeders. The objectives of the present study were (1) identify drought-tolerant cultivars using vegetation indices (VIs), compared traditional method and (2) assess accuracy VIs-based prediction model estimating stomatal conductance (Gs) chlorophyll content (Chl). A field trial was arranged in randomized complete block design, consisting seven sugarcane. At tillering elongation stages, irrigation withheld, then furrow applied relieve sugarcane from stress. physiological assessment measuring Gs Chl handheld device VIs recorded under stress recovery periods. results showed that same identified as when methods used identification. Likewise, derived genotype by trait biplot heatmap comparable, which TCP93-4245 CP72-1210 classified tolerant cultivars, while sensitive CP06-2400 CP89-2143 both parameters model, random forest outperformed linear models predicting performance untested crops/environments Chl. contrast, it underperformed tested crops/environments. identification through revealed at least two out three had consistent rankings measured predicted outcomes traits. This shows possibility UAS mounted sensors assist breeders their decision-making.

Language: Английский

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Stability and adaptability of grain yield in quinoa genotypes in four locations of Iran

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 29, 2024

The genotype × environment interaction is one of the effective factors in identifying and introducing cultivars with stable grain yield different environments. There are many statistical methods for estimating interaction, among which AMMI GGE-biplot analyses provide better more interpretable results. objective this study was to assess as well adaptability stability 40 quinoa genotypes. experiment carried out a randomized complete block design three replications eight environments (four locations Iran two years). analysis variance showed that main effects environment, effect were significant on yield. Separation based principal component method first six components accounted 47.6%, 22.5%, 9%, 7%, 6% 4.3% variance, respectively. Based model, genotypes G16, G19, G35, G30, G39, G24, G18 identified high-yielding high general adaptability. In contrast, G36, G27, G38, G9, G28, G29, G23, G34, G13, G12 most unstable studied analysis, mega-environments identified, G25, G17 also these Also, biplot diagram ideal genotype, G17, G35 nearest genotype. total, results various G16 G19 superior terms stability. These can be introduced climatic conditions areas.

Language: Английский

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GLCM-1DCNN-based hyperspectral inversion of organic matter in improved saline soils

2022 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML), Journal Year: 2023, Volume and Issue: unknown, P. 441 - 446

Published: Nov. 3, 2023

The organic matter content of saline soils is an important biochemical indicator for evaluating the effectiveness land improvement. Therefore, monitoring soil rapidly and accurately key to realizing accurate degree Hyperspectral image technology allows rapid inversion content.Using measured hyperspectral data saline-amended as raw extraction spatial information by GLCM form texture features fused with reflectance mapping. Construction a convolutional network model in comparison processing. results show that compared other processing methods, best prediction inverted using extracted maps, method spectrum fusion, 0.9869, which 9.85% enhancement method, 9.7192, decrease 65.9210 method.

Language: Английский

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