Evidence map›Paper›PMID 35531188›Full record

ArticleSaudi journal of biological sciences2022

Utilizing spectral vegetation indices for yield assessment of tomato genotypes grown in arid conditions.

Abdulhakim A Aldubai, Abdullah A Alsadon, Khalid A Al-Gaadi, ElKamil Tola, Abdullah A Ibrahim

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Article in Saudi journal of biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Abdulhakim A AldubaiPlant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Abdullah A AlsadonPlant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Khalid A Al-GaadiPrecision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia.
ElKamil TolaPrecision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia.
Abdullah A IbrahimPlant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tomato is among important vegetable crops cultivated in different climates; however, heat stress can greatly affect fruit quality and overall yield. Crop reflectance measurements based on ground reflectance sensor data are reliable indicators of crop tolerance to abiotic stresses. Here, we report on using non-destructive spectral vegetation indices to monitor yield traits of 10 tomato genotypes transplanted on three different dates (Aug. 2, Sept. 3 and Oct. 1) during 2019 growing season in the Riyadh region. The ten genotypes comprised six commercial cultivars-(Pearson Improved, Strain B, Valentine, Marmande VF, Super Strain B, and Pearson early) --and four local Saudi cultivars (Al-Ahsa, Al-Qatif, Hail and Najran). Spectral reflectance data were utilized using a FieldSpec 3 spectroradiometer in the range of 350-2500 nm to calculate nine vegetation indices (VIs): Normalized Water Band Index (NWBI), Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Red Edge Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index (SAVI), Red Edge Normalized Difference Vegetation Index (RENDVI), Renormalized Difference Vegetation Index (RDVI), and Normalized Difference Nitrogen Index (NDNI). VIs and yield parameters (total fruit yield, harvest index) revealed that second transplanting date was optimal for all the genotypes. Valentine showed the best growth performance followed by Najran, Hail, Super Strain B and finally Pearson early. For all the three transplanting dates, Valentine recorded the highest total fruit yield. Additionally, some genotypes had no significant differences in the VIs values or the total fruit yield between the second and third transplanting dates. This study indicated that yield parameters could be linked to rapid, non-destructive hyperspectral reflectance data to predict tomato production under heat stress.

Indexed as

Heat stressSolanum lycopersicum L.Spectral reflectanceVegetation indices

Identifiers

PMID35531188
PMCPMC9073031

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.