Unverified paper record
Evaluating SAM3 and Conventional Image Processing Method for Potato Canopy Cover Estimation as an Indicator of Crop Health
Copernicus GmbH · 13 Mar 2026 · 10.5194/egusphere-egu26-1681
Abstract
Precise monitoring of crop canopy cover (CC) is crucial for evaluating growth and health under diverse water and nutrient conditions. Although nano liquid urea has been promoted in India as an eco-friendly alternative to conventional nitrogen (N) fertilizers. Its effectiveness in potato cultivation, particularly for canopy development and yield, remains unclear. To address this gap, a field experiment was conducted during the 2024–25 winter season using three N treatments under a micro-irrigation system: T1-recommended granular urea (46% N), T2-without N, and T3-IFFCO nano liquid urea (4% w/v). Images were captured using a downward-looking smartphone camera positioned 2.5 meters above the crop near each treatment, serving as the primary input for estimating canopy cover. The images were processed using both a prompt-based segmentation model (SAM3) and an image-processing pipeline (Modified Excess Green Index + Otsu thresholding) to estimate CC. The SAM3 occasionally overestimated or failed to detect the potato canopy with the prompt “Green plants, leaves, vegetations, canopy cover”, whereas the image-processing approach consistently provided accurate CC estimates and was therefore used for subsequent analysis. The result revealed that the CC clearly showed differentiation among the treatments after 25 days after sowing (DAS). With this most of the treatment comparisons depict the CC peaking after 45 DAS, where the T1 recorded the highest canopy cover (~71%), indicating a healthy crop, while the pairwise comparisons showed CC values of ~55% (T1–T2), ~66% (T1–T3), ~33% (T2–T2), ~36% (T3–T3), and ~36% (T2–T3), depicting the nitrogen deficit. Similarly, the yield followed the same trend, with T1 producing the highest yield (26.78 t/ha), compared to 10.89 t/ha in T2 and 11.90 t/ha in T3. The results indicate that nano liquid urea does not supply sufficient nitrogen to support optimal potato canopy growth and productivity, resulting almost similar response to the no nitrogen application treatment. Increasing the nitrogen concentration in nano liquid urea formulations may improve their effectiveness. This study provides evidence to guide farmers in selecting appropriate nitrogen fertilizers for potato cultivation. In the future, such fertilizers should be evaluated across different crops to ensure their efficacy and to prevent farmers from adopting products that may not meet crop nutrient requirements.
Plant phenotyping relevance
ジャガイモのキャノピー被覆率という植物形質を、SAM3と画像処理パイプラインで推定し、両手法の性能を比較・評価しているため、施肥試験を含むがフェノタイピング手法が中心的です。
titleEvaluating SAM3 and Conventional Image Processing Method for Potato Canopy Cover Estimation as an Indicator of Crop Health
abstractThe images were processed using both a prompt-based segmentation model (SAM3) and an image-processing pipeline (Modified Excess Green Index + Otsu thresholding) to estimate CC.
abstractThe SAM3 occasionally overestimated or failed to detect the potato canopy with the prompt “Green plants, leaves, vegetations, canopy cover”, whereas the image-processing approach consistently provided accurate CC estimates
Code and data availability
公開論文であることは確認できましたが、現在の公式API・許可済み取得経路では本文を自動取得できませんでした。
No evidence-backed public reproduction asset is currently recorded.
This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.