ArticlePlant methods2020
Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage.
Article in Plant methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Detection of Abiotic Stress in Potato and Sweet Potato Plants Using Hyperspectral Imaging and Machine Learning.Plants (Basel, Switzerland) · 2025Article
- Methodological evolution of potato yield prediction: a comprehensive review.Frontiers in plant science · 2023Review
- Cultivar-dependent differences in tuber growth cause increased soil resistance in potato fields.Frontiers in plant science · 2023Article
- Multispectral remote sensing for accurate acquisition of rice phenotypes: Impacts of radiometric calibration and unmanned aerial vehicle flying altitudes.Frontiers in plant science · 2022Article
- A review of remote sensing for potato traits characterization in precision agriculture.Frontiers in plant science · 2022Review
- Multi-dimensional variables and feature parameter selection for aboveground biomass estimation of potato based on UAV multispectral imagery.Frontiers in plant science · 2022Article
- Remotely sensed estimation of total iron content in soil with harmonic analysis and BP neural network.Plant methods · 2021Article
- Impacts of climate change on suitability zonation for potato cultivation in Jilin Province, Northeast China.Scientific reports · 2021Article
- Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging.Remote sensing · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe accurate estimation of potato yield at regional scales is crucial for food security, precision agriculture, and agricultural sustainable development.
methodsIn this study, we developed a new method using multi-period relative vegetation indices (rVIs) and relative leaf area index (rLAI) data to improve the accuracy of potato yield estimation based on the weighted growth stage. Two experiments of field and greenhouse (water and nitrogen fertilizer experiments) in 2018 were performed to obtain the spectra and LAI data of the whole growth stage of potato. Then the weighted growth stage was determined by three weighting methods (improved analytic hierarchy process method, IAHP; entropy weight method, EW; and optimal combination weighting method, OCW) and the Slogistic model. A comparison of the estimation performance of rVI-based and rLAI-based models with a single and weighted stage was completed.
resultsThe results showed that among the six test rVIs, the relative red edge chlorophyll index (rCI
conclusionThis study emphasizes the importance of inconsistent contributions of multi-period or different types of data to the results when they are used together, and the weights need to be considered.
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