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Related papers: PROSPECT-PRO for estimating content of nitrogen-co…

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Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past,…

Quantitative Methods · Quantitative Biology 2020-12-10 Katja Berger , Jochem Verrelst , Jean-Baptiste Féret , Tobias Hank , Matthias Wocher , Wolfram Mauser , Gustau Camps-Valls

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus…

Modern day studies show a high degree of correlation between high yielding crop varieties and plants with upright leaf angles. It is observed that plants with upright leaf angles intercept more light than those without upright leaf angles,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Venkat Margapuri , Prapti Thapaliya , Trevor Rife

Plant traits such as leaf carbon content and leaf mass are essential variables in the study of biodiversity and climate change. However, conventional field sampling cannot feasibly cover trait variation at ecologically meaningful spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Eya Cherif , Arthur Ouaknine , Luke A. Brown , Phuong D. Dao , Kyle R. Kovach , Bing Lu , Daniel Mederer , Hannes Feilhauer , Teja Kattenborn , David Rolnick

Plants in their natural habitats endure an array of interacting stresses, both biotic and abiotic, that rarely occur in isolation. Nutrient stress-particularly nitrogen deficiency-becomes even more critical when compounded with drought and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Aswini Kumar Patra , Lingaraj Sahoo

In this work, we propose the novel Prototypical Graph Regression Self-explainable Trees (ProGReST) model, which combines prototype learning, soft decision trees, and Graph Neural Networks. In contrast to other works, our model can be used…

Quantitative Methods · Quantitative Biology 2022-12-29 Dawid Rymarczyk , Daniel Dobrowolski , Tomasz Danel

The investigation of plant transcriptional regulation constitutes a fundamental basis for crop breeding, where cis-regulatory elements (CREs), as the key factor determining gene expression, have become the focus of crop genetic improvement…

Genomics · Quantitative Biology 2025-05-16 Yingjun Wu , Jingyun Huang , Liang Ming , Pengcheng Deng , Maojun Wang , Zeyu Zhang

Clover fixates nitrogen from the atmosphere to the ground, making grass-clover mixtures highly desirable to reduce external nitrogen fertilization. Herbage containing clover additionally promotes higher food intake, resulting in higher milk…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Muhammad Zawish , Paul Albert , Flavio Esposito , Steven Davy , Lizy Abraham

Soil organic carbon (SOC) plays a major role in the global carbon budget. It can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Improving the tools that model the spatial…

Protein structures are important for understanding their functions and interactions. Currently, many protein structure prediction methods are enriching the structure database. Discriminating the origin of structures is crucial for…

Biomolecules · Quantitative Biology 2024-10-24 Wenrui Gou , Wenhui Ge , Yang Tan , Mingchen Li , Guisheng Fan , Huiqun Yu

Environmental variables are increasingly affecting agricultural decision-making, yet accessible and scalable tools for soil assessment remain limited. This study presents a robust and scalable modeling system for estimating soil properties…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 David Seu , Nicolas Longepe , Gabriel Cioltea , Erik Maidik , Calin Andrei

Protein language models (pLMs) produce per-residue representations that capture evolutionary and structural information, yet their mean-pooled sequence embeddings are not explicitly trained to reflect functional, evolutionary or structural…

Machine Learning · Computer Science 2026-05-11 Dan Ofer , Oriel Perets , Michal Linial , Nadav Rappoport

Rising global food demand and growing climate pressure increase the need for sustainable, precise agricultural practices. Automated, individualized plant treatment relies on fine-grained visual analysis, yet leaf-level segmentation remains…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Robert Martinko , Daniel Steininger , Julia Simon , Andreas Trondl , Matthias Blaickner

In response to climate change, assessing crop productivity under extreme weather conditions is essential to enhance food security. Crop simulation models, which align with physical processes, offer explainability but often perform poorly.…

Machine Learning · Computer Science 2025-01-03 Miro Miranda , Marcela Charfuelan , Andreas Dengel

Automation in agriculture plays a vital role in addressing challenges related to crop monitoring and disease management, particularly through early detection systems. This study investigates the effectiveness of combining multimodal Large…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Konstantinos I. Roumeliotis , Ranjan Sapkota , Manoj Karkee , Nikolaos D. Tselikas , Dimitrios K. Nasiopoulos

The accurate semantic segmentation of tree crowns within remotely sensed data is crucial for scientific endeavours such as forest management, biodiversity studies, and carbon sequestration quantification. However, precise segmentation…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Georgios Voulgaris

Accurately measuring protein-RNA binding affinity is crucial in many biological processes and drug design. Previous computational methods for protein-RNA binding affinity prediction rely on either sequence or structure features, unable to…

Biomolecules · Quantitative Biology 2025-01-06 Rong Han , Xiaohong Liu , Tong Pan , Jing Xu , Xiaoyu Wang , Wuyang Lan , Zhenyu Li , Zixuan Wang , Jiangning Song , Guangyu Wang , Ting Chen

Efficient nutrient management is critical for crop growth and sustainable resource consumption (e.g., nitrogen, energy). Current approaches require lengthy analyses, preventing real-time optimization; similarly, imaging facilitates rapid…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Abigail R. Cohen , Yuming Sun , Zhihao Qin , Harsh S. Muriki , Zihao Xiao , Yeonju Lee , Matthew Housley , Andrew F. Sharkey , Rhuanito S. Ferrarezi , Jing Li , Lu Gan , Yongsheng Chen

Drought stress is a major threat to global crop productivity, making its early and precise detection essential for sustainable agricultural management. Traditional approaches, though useful, are often time-consuming and labor-intensive,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Aswini Kumar Patra , Lingaraj Sahoo

Plant phenotyping (Guo et al. 2021; Pieruschka et al. 2019) focuses on studying the diverse traits of plants related to the plants' growth. To be more specific, by accurately measuring the plant's anatomical, ontogenetical, physiological…

Machine Learning · Computer Science 2022-01-17 Jun Wu , Elizabeth A. Ainsworth , Sheng Wang , Kaiyu Guan , Jingrui He
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