Detecting Sensitive Spectral Bands and Vegetation Indices for Potato Yield Using Handheld Spectroradiometer Data.

Abstract

Remote sensing is a valuable tool in precision agriculture due to its spatial and temporal coverage, non-destructive method of data collection, and cost-effectiveness. In this study, we measured the canopy reflectance of potato ( Solanum tuberosum L.) crops on a plant-by-plant basis with a handheld spectrometer instrument. Our study pursues two primary objectives: (1) determining the optimal temporal aggregation for measuring canopy signals related to potato yield and (2) identifying the best spectral bands in the 350-2500 nm domain and vegetation indices. The study was conducted over two consecutive years (2020 and 2021) with 60 plants per plot, encompassing six potato varieties and three replicates annually throughout the growth season. Employing correlation analysis and dimensionality reduction, we identified 23 independent features significantly correlated with tuber yield. We used multiple linear regression analysis to model the relationship between the selected features and yield and to compare their influence in the fitted model. We used the Leave-One-Out Cross-Validation (LOOCV) method to assess the validity of the model (RMSE = 702 g and %RMSE = 29.2%). The most significant features included the Gitelson2 and Vogelmann indices. The optimal time period for measurements was determined to be from 56 to 100 days after planting. These findings may contribute to the advancement of precision farming by proposing tailored sensor applications, paving the way for improved agricultural practices and enhanced food security.

Plant phenotyping relevance

携帯型分光計による植物体ごとのキャノピー反射測定、感度波長・植生指数の選定、収量推定モデルの検証が研究の中心であり、ジャガイモ収量という植物形質を推定する方法研究である。

Code and data availability

The paper's plant-level ASD spectroradiometer reflectance measurements and tuber yield data are not publicly deposited; the Data Availability Statement states no new data were created or analyzed, and no author code or model availability is declared. The only supplement (Figure S1, a correlation matrix) does not expose

No evidence-backed public reproduction asset is currently recorded.