Most Downloaded Articles

Open access

ISSN: 2589-7217
CN: 10-1795/S
p-ISSN: 2097-2113

Application of artificial intelligence in insect pest identification - A review

The increasing danger of insect pests to agriculture and ecosystems calls for quick, and precise diagnosis. Conventional techniques that depend on human observation and taxonomic knowledge are frequently...

Computer vision in smart agriculture and precision farming: Techniques and applications

The transformation of age-old farming practices through the integration of digitization and automation has sparked a revolution in agriculture that is driven by cutting-edge computer vision and artificial...

Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides

Agriculture plays a significant role in the economic sector. The automation in agriculture is the main concern and the emerging subject across the world. The population is increasing tremendously and...

AI-driven aquaculture: A review of technological innovations and their sustainable impacts

The integration of artificial intelligence (AI) in aquaculture has been identified as a transformative force, enhancing various operational aspects from water quality management to genetic optimization....

Automatic body temperature detection of group-housed piglets based on infrared and visible image fusion

Rapid and accurate measurement of body temperature is essential for early disease detection, as it is a key indicator of piglet health. Infrared thermography (IRT) is a widely used, convenient, non-intrusive,...

Review of agricultural IoT technology

Agricultural Internet of Things (IoT) has brought new changes to agricultural production. It not only increases agricultural output but can also effectively improve the quality of agricultural products,...

Fruit ripeness classification: A survey

Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, most of all, safety....

A comprehensive review of obstacle avoidance for autonomous agricultural machinery in multi-operational environment

As automation becomes increasingly adopted to mitigate labor shortages and boost productivity, autonomous technologies such as tractors, drones, and robotic devices are being utilized for various tasks...

Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments

Instance segmentation, an important image processing operation for automation in agriculture, is used to precisely delineate individual objects of interest within images, which provides foundational...

Development of an enhanced hybrid attention YOLOv8s small object detection method for phenotypic analysis of root nodules

Nodule formation and their involvement in biological nitrogen fixation are critical features of leguminous plants, with phenotypic characteristics closely linked to plant growth and nitrogen fixation...

A comprehensive review on automation in agriculture using artificial intelligence

Agriculture automation is the main concern and emerging subject for every country. The world population is increasing at a very fast rate and with increase in population the need for food increases...

Deep learning-based classification, detection, and segmentation of tomato leaf diseases: A state-of-the-art review

The early identification and treatment of tomato leaf diseases are crucial for optimizing plant productivity, efficiency and quality. Misdiagnosis by the farmers poses the risk of inadequate treatments,...

Automation and digitization of agriculture using artificial intelligence and internet of things

The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity. In most of the countries where the expansion...

Application of navigation technology in agricultural machinery: A review and prospects

With the rapid advancement of information technology, the intelligent and unmanned applications of agricultural machinery and equipment have become a central focus of current research. Navigation technology...

A review on enhancing agricultural intelligence with large language models

This paper systematically explores the application potential of large language models (LLMs) in the field of agricultural intelligence, focusing on key technologies and practical pathways. The study...

Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review

An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue. Both e-nose and e-tongue have shown great promise and utility in improving assessments...

Towards sustainable agriculture: Harnessing AI for global food security

The issue of food security continues to be a prominent global concern, affecting a significant number of individuals who experience the adverse effects of hunger and malnutrition. The finding of a solution...

A review of imaging techniques for plant disease detection

Agriculture is the basis of every economy worldwide. Crop production is one of the major factors affecting domestic market condition in any country. Agricultural production is also a major prerequisite...

Transfer learning-based soybean LAI estimations by integrating PROSAIL, UAV, and PlanetScope imagery

Accurate Leaf Area Index (LAI) estimations at the soybean plot scale is achievable using high-resolution Unmanned Aerial Vehicle (UAV) imagery and field measurement samples. However, the limited coverage...

Deep learning based computer vision approaches for smart agricultural applications

The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core...

Two-year remote sensing and ground verification: Estimating chlorophyll content in winter wheat using UAV multi-spectral imagery

Leaf chlorophyll content serves as a critical biophysical indicator for characterizing wheat growth status. Traditional measurement using a SPAD meter, while convenient, is hampered by its localized...

Comprehensive review on 3D point cloud segmentation in plants

Segmentation of three-dimensional (3D) point clouds is fundamental in comprehending unstructured structural and morphological data. It plays a critical role in research related to plant phenomics, 3D...

DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

Rice stands as a crucial staple food globally, with its enduring sustainability hinging on the prompt detection of rice leaf diseases. Hence, efficiently detecting diseases when they have already occurred...

Comparison of CNN-based deep learning architectures for rice diseases classification

Although convolutional neural network (CNN) paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures, few studies have focused on the performance comparison...

YOLO-light-pruned: A lightweight model for monitoring maize seedling count and leaf age using near-ground and UAV RGB images

Maize seedling count and leaf age are critical indicators of early growth status, essential for effective field management and breeding variety selection. Traditional field monitoring methods are time-consuming,...

Stay Informed

Register your interest and receive email alerts tailored to your needs. Sign up below.