Dataset Information

CCMT: Dataset for crop pest and disease detection.

ABSTRACT: Artificial Intelligence (AI) has been evident in the agricultural sector recently. The objective of AI in agriculture is to control crop pests/diseases, reduce cost, and improve crop yield. In developing countries, the agriculture sector faces numerous challenges in the form of knowledge gap between farmers and technology, disease and pest infestation, lack of storage facilities, among others. In order to resolve some of these challenges, this paper presents crop pests/disease datasets sourced from local farms in Ghana. The dataset is presented in two folds; the raw images which consists of 24,881 images (6,549-Cashew, 7,508-Cassava, 5,389-Maize, and 5,435-Tomato) and augmented images which is further split into train and test sets. The latter consists of 102,976 images (25,811-Cashew, 26,330-Cassava, 23,657-Maize, and 27,178-Tomato), categorized into 22 classes. All images are de-identified, validated by expert plant virologists, and freely available for use by the research community.

SUBMITTER: Mensah PK

PROVIDER: S-EPMC10285554 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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CCMT: Dataset for crop pest and disease detection.

Mensah Patrick Kwabena PK Akoto-Adjepong Vivian V Adu Kwabena K Ayidzoe Mighty Abra MA Bediako Elvis Asare EA Nyarko-Boateng Owusu O Boateng Samuel S Donkor Esther Fobi EF Bawah Faiza Umar FU Awarayi Nicodemus Songose NS Nimbe Peter P Nti Isaac Kofi IK Abdulai Muntala M Adjei Remember Roger RR Opoku Michael M Abdulai Suweidu S Amu-Mensah Fred F

Data in brief 20230612

Artificial Intelligence (AI) has been evident in the agricultural sector recently. The objective of AI in agriculture is to control crop pests/diseases, reduce cost, and improve crop yield. In developing countries, the agriculture sector faces numerous challenges in the form of knowledge gap between farmers and technology, disease and pest infestation, lack of storage facilities, among others. In order to resolve some of these challenges, this paper presents crop pests/disease datasets sourced f ...[more]

PMID: 37360671

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Project description:Spotted wing drosophila, Drosophila suzukii Matsumura, is a major pest of small fruit worldwide in temperate and subtropical growing regions. In Northern climates, D. suzukii likely overwinters locally under leaf litter and snow pack, but our understanding of the factors affecting thermal susceptibility is limited. While previous investigations of thermal susceptibility in this species have employed conventional static acclimation protocols, we aimed to determine whether gradual cooling, or dynamic acclimation, may extend the limits of known thermal tolerance by more closely approximating naturally occurring shifts in temperature. First, we assessed survival among adult and pupal D. suzukii using static acclimation. Then, we re-assessed survival using a novel dynamic acclimation method. We found that while static acclimation was sufficient to induce cold tolerance, dynamic acclimation significantly improved survival at temperatures as low as -7.5 °C. Following static acclimation, the lower lethal limit of adult D. suzukii was -1.1 °C in winter morphotype (WM) adults compared to 1.7 °C in non-acclimated summer morphotype (SM) adults. Dynamic acclimation reduced the lower limit to -5 °C in SM flies. At the end of our study 50% of WM flies survived 72 h at -7.5 °C. Below 0 °C pupal survival declined significantly regardless of acclimation procedure. However, pupal acclimation improved survival outcomes significantly compared to non-acclimated pupae, suggesting that while juvenile diapause is unlikely, cold hardening likely benefits those flies which may develop into the overwintering WM population. These data suggest that the degree of cold hardening is proportional to the thermal environment, a finding previously unrecognized in this species. Given the economic impact of this pest, these data may have important implications for offseason population monitoring and management. We discuss how phenotypic plasticity may drive geographical range expansion, and the impact of climate change on the spread of this species.

Dataset Information

CCMT: Dataset for crop pest and disease detection.

Publications

CCMT: Dataset for crop pest and disease detection.

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