AIMC Topic: Agriculture

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Deep learning model BiFPN-YOLOv8m for tree counting in mango orchards using satellite remote sensing data​.

Scientific reports
Mango is a fruit of great economic importance in India. India is the top mango-producing nation in the world, accounting for over half of global mango output. In order to determine the production capability of the insured orchards, a complete invento...

Prediction of regional cropland soil organic carbon content and distribution using deep learning: a case study of the Northeast China Plain.

Environmental monitoring and assessment
Soil organic carbon (SOC) is a critical component of soil fertility and plays a significant role in global carbon sequestration. The decline in SOC content across global croplands poses significant challenges to both agricultural productivity and env...

Measurement model of credit risk for unlisted agricultural enterprises.

PloS one
This paper aims to measure credit risks of unlisted agricultural enterprises by using the KMV model integrating a CNN-BiLSTM neural network. Initially, the expected default frequencies (EDF) for each listed agricultural enterprise are computed using ...

Associations among weed communities, management practices, and environmental factors in U.S. snap bean (Phaseolus vulgaris) production.

PloS one
Weed species that escape control (hereafter called residual weeds) coupled with changing weather patterns are emerging challenges for snap bean processors and growers. Field surveys were conducted to identify associations among crop/weed management p...

A robust hydroponic system for horticulture farming using deep learning, IoT, and mobile application.

PloS one
Due to limited literacy among root-level farmers, hydroponic farming in Bangladesh faces significant challenges. Therefore, there is a demand for easy-to-use technical systems to help farmers to monitor and operate smart systems. To address the issue...

Digital soil mapping in support of voluntary carbon market programs in agricultural land.

PloS one
Voluntary carbon market (VCM) programs in agriculture depend on accurate measurements of soil organic carbon (SOC) that can be deployed at scale efficiently, but barriers are preventing widespread adoption. To overcome these challenges, we developed ...

Multiple model visual feature embedding and selection method for an efficient pest classification supporting precision agriculture.

Scientific reports
Agriculture 5.0 is a principal economic activity in the world with major workforce dependent crops cultivation. An automated system for crops field insect pest identification can help decrease labour, while also improving the speed and precision in c...

Ecological and carcinogenic risk assessment of potentially toxic elements in rangelands and croplands around Lake Junin (Peru): Integrating remote sensing, machine learning, and land cover segmentation.

The Science of the total environment
The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial dis...

Helmets Labeling Crops: Kenya Crop Type Dataset Created via Helmet-Mounted Cameras and Deep Learning.

Scientific data
Accurate, up-to-date agricultural monitoring is essential for assessing food production, particularly in countries like Kenya, where recurring climate extremes, including floods and droughts, exacerbate food insecurity challenges. In regions dominate...

An adaptive sliding mode controller with free-will arbitrary time convergence for three-phase rectifiers in autonomous agricultural vehicles.

PloS one
This study describes a novel adaptive free-will arbitrary time sliding mode controller (AFWATSMC) designed to improve the performance of a three-phase rectifier in an autonomous oil palm grabber vehicle (Robot Autonomous Mechanical Buffalo Grabber (M...