Optimization strategies of fruit detection to overcome the challenge of unstructured background in field orchard environment: A review

Y Tang, J Qiu, Y Zhang, D Wu, Y Cao, K Zhao… - Precision Agriculture, 2023 - Springer
The demand for intelligent agriculture is increasing due to the continuous impact of world
food and environmental crises. Focusing on fruit detection, with the rapid development of …

Forecasting plant and crop disease: an explorative study on current algorithms

G Fenu, FM Malloci - Big Data and Cognitive Computing, 2021 - mdpi.com
Every year, plant diseases cause a significant loss of valuable food crops around the world.
The plant and crop disease management practice implemented in order to mitigate …

Machine learning in precision agriculture: a survey on trends, applications and evaluations over two decades

S Condran, M Bewong, MZ Islam, L Maphosa… - IEEE …, 2022 - ieeexplore.ieee.org
Precision agriculture represents the new age of conventional agriculture. This is made
possible by the advancement of various modern technologies such as the internet of things …

Hyperspectral imaging for early identification of strawberry leaves diseases with machine learning and spectral fingerprint features

Q Jiang, G Wu, C Tian, N Li, H Yang, Y Bai… - Infrared Physics & …, 2021 - Elsevier
Anthracnose and gray mold are two most devastating diseases of strawberries which can
spread to healthy plants in short time and can cause large-scale yield losses worldwide …

Early decay detection in fruit by hyperspectral imaging–Principles and application potential

D Min, J Zhao, G Bodner, M Ali, F Li, X Zhang… - Food Control, 2023 - Elsevier
Although fruits are rich in health-promoting properties and associated with several health
benefits to humans, they are highly susceptible to pathogen infection which results in the …

Enhancing mango disease diagnosis through eco-informatics: A deep learning approach

AA Salamai - Ecological Informatics, 2023 - Elsevier
The mango is one of the most popular and economically important fruits in the world, but it is
vulnerable to various diseases that can significantly reduce the quality and yield of the fruit …

[PDF][PDF] Comparison of Artificial Intelligence Algorithms in Plant Disease Prediction.

RR Patil, S Kumar, R Rani - Revue d'Intelligence Artificielle, 2022 - researchgate.net
Accepted: 12 April 2022 The оссurrenсe or сhаnge in the diseases in а specific аreа саn be
рrediсted in аdvаnсe with the help оf рlаnt disease fоreсаsting model. This helps to …

Investigation into maize seed disease identification based on deep learning and multi-source spectral information fusion techniques

P Xu, L Fu, K Xu, W Sun, Q Tan, Y Zhang, X Zha… - Journal of Food …, 2023 - Elsevier
Detection of diseases in maize seeds is crucial for their quality evaluation and disease
control. This study uses hyperspectral imaging (HSI) and deep learning methods for analysis …

Hyperspectral imaging coupled with machine learning for classification of anthracnose infection on mango fruit

U Siripatrawan, Y Makino - Spectrochimica Acta Part A: Molecular and …, 2024 - Elsevier
Anthracnose is the major plant disease causing an economic loss of mango fruit.
Anthracnose symptom is not visible at a quiescent stage and the infected fruit often enters …

Analysis of mango fruit surface temperature using thermal imaging and deep learning

P Pugazhendi, G Balakrishnan Kannaiyan… - International Journal of …, 2023 - degruyter.com
Thermal imaging has the potential to measure the object's surface temperature. This study
investigated the thermal behavior of mango fruit stored in a refrigerated environment …