Protecting Superfood Olive Crop from Pests and Pathogens Using Image Processing Techniques: A Review

Abstract

Background: Olive (Oleo europaea L.) cultivars are widely cultivated all over the world. However, they are often attacked by pests and pathogens. This deteriorates the quality of the crop, leading to less yield of olive oil. The different infections that cause comparable disease symptoms on olive leaves can be classified using image processing techniques. Objective: The olive has established itself as a superfood and a possible source of medicine, owing to the rapid increase in the availability of data in the field of nutrigenomics. The goal of this review is to underline the importance of applying image processing techniques to detect and classify diseases early. Method: PubMed, ScienceDirect, and Google Scholar were used to conduct a systematic literature search using the keywords olive oil, pest and pathogen of olives, and metabolic profiling. Results: Infections caused by infectious diseases frequently result in significant losses and lowquality olive oil yields. Early detection of disease infestations can safeguard the olive plant and its yield. Results: This strategy can help protect the crop from disease spread, and early detection and classification of the disease can aid in prompt prophylaxis of diseased olive plants before the disease worsens. Protecting olive plants from pests and pathogens can help keep the yield and quality of olive oil consistent.

Plant phenotyping relevance

オリーブ葉の病害を画像処理で早期検出・分類する方法を扱うレビューであり、植物の病徴という状態の取得・推定が中心です。

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