Designing a Proximal Sensing Camera Acquisition System for Vineyard Applications: Results and Feedback on 8 Years of Experiments.

Abstract

The potential of image proximal sensing for agricultural applications has been a prolific scientific subject in the recent literature. Its main appeal lies in the sensing of precise information about plant status, which is either harder or impossible to extract from lower-resolution downward-looking image sensors such as satellite or drone imagery. Yet, many theoretical and practical problems arise when dealing with proximal sensing, especially on perennial crops such as vineyards. Indeed, vineyards exhibit challenging physical obstacles and many degrees of variability in their layout. In this paper, we present the design of a mobile camera suited to vineyards and harsh experimental conditions, as well as the results and assessments of 8 years' worth of studies using that camera. These projects ranged from in-field yield estimation (berry counting) to disease detection, providing new insights on typical viticulture problems that could also be generalized to orchard crops. Different recommendations are then provided using small case studies, such as the difficulties related to framing plots with different structures or the mounting of the sensor on a moving vehicle. While results stress the obvious importance and strong benefits of a thorough experimental design, they also indicate some inescapable pitfalls, illustrating the need for more robust image analysis algorithms and better databases. We believe sharing that experience with the scientific community can only benefit the future development of these innovative approaches.

Plant phenotyping relevance

ブドウ園向け移動カメラシステムの設計と、収量推定・病害検出への8年間の適用および評価が中心であり、植物形質取得プラットフォームの方法開発・実証に該当する。

Code and data availability

The paper describes vineyard proximal-sensing image datasets from four projects (EARN, ADVANTAGE, ProxiMaVi, ProspectFD). Only ProxiMaVi is noted as available online via a published data article, but no repository, identifier, or authors' public URL is provided in the supplied text, and the only allowed URL is the CC-B

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