Classification of diseases and pests in agricultural crops: A systematic review

article

Francisco, Mauro
Ribeiro, Fernando Reinaldo
Metrôlho, José
Dionísio, Rogério

MDPI

Francisco, Mauro [et al.] (2023). Algorithms and models for automatic detection and classification of diseases and pests in agricultural crops: A systematic review. Applied Sciences, 13(8), 4720. MDPI AG. http://dx.doi.org/10.3390/app13084720

Classification of diseases and pests in agricultural crops: A systematic review

Crop disease detection
Classification
Plant diseases and pests
Smart farming

CENTRO-01- 0247-FEDER-113287

2023-05-16T12:49:45Z
2023-05-16T12:49:45Z
2023

Plant diseases and pests significantly influence food production and the productivity and economic profitability of agricultural crops. This has led to great interest in developing technological solutions to enable timely and accurate detection. This systematic review aimed to find studies on the automation of processes to detect, identify and classify diseases and pests in agricultural crops. The goal is to characterize the class of algorithms, models and their characteristics and understand the efficiency of the various approaches and their applicability. The literature search was conducted in two citation databases. The initial search returned 278 studies and, after removing duplicates and applying the inclusion and exclusion criteria, 48 articles were included in the review. As a result, seven research questions were answered that allowed a characterization of the most studied crops, diseases and pests, the datasets used, the algorithms, their inputs and the levels of accuracy that have been achieved in automatic identification and classification of diseases and pests. Some trends that have been most noticed are also highlighted.
info:eu-repo/semantics/publishedVersion

openAccess
http://creativecommons.org/licenses/by/4.0/

eng