Tomato Plant Leaf Disease Classification using Deep Learning: A Review

Abstract

Tomato plants frequently be afflicted by diseases that may damage plants and decrease farmers’ earnings. finding these illnesse s early could be very vital for coping with them that affect tomato plants, like Yellow Leaf Curl Virus, Leaf mildew , late Blight, Early Blight, Septorial Spot, Bacterial Spot, goal Spot, Mosaic Virus, healthful, spotted Spider Mite, Powdery mould .We use deep getting to know strategies, especially a combination of EfficientNet-B0 with VGG-16, EfficientNet-B0 with CNN and VGG-16 with CNN, to investigate images of tomato leaves and decide if they may be healthful or diseased. The model learns to spot the specific signs of each disease, ensuring accurate detection. The system also suggests the best pesticides for treatment. By providing both disease identification and pesticide recommendations, this system helps farmers make better decisions to protect their crops, improve plant health and increase yield. This helps farmers grow healthier crops and increase food production in a sustainable way.

Plant phenotyping relevance

トマト葉の画像から健全・罹病状態や病徴を分類する手法が中心であり、植物病害状態の画像ベース表現型計測に該当する。タイトル上はレビューで、手法の整理・評価を主題としている。

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