AIMC Topic: Crops, Agricultural
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Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.
Nature plants
Jun 24, 2021
Climate change, increasing populations, competing demands on land for production of biofuels and declining soil quality are challenging global food security. Finding sustainable solutions requires bold new approaches and integration of knowledge from...
Crop yield prediction integrating genotype and weather variables using deep learning.
PloS one
Jun 17, 2021
Accurate prediction of crop yield supported by scientific and domain-relevant insights, is useful to improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop producti...
The Concept of the Constructional Solution of the Working Section of a Robot for Harvesting Strawberries.
Sensors (Basel, Switzerland)
Jun 7, 2021
Strawberry fruits are products of high commercial and consumption value, and, at the same time, they are difficult to harvest due to their very low mechanical strength and difficulties in identifying them within the bush. Therefore, robots collecting...
A novel semi-supervised framework for UAV based crop/weed classification.
PloS one
May 10, 2021
Excessive use of agrochemicals for weed controlling infestation has serious agronomic and environmental repercussions associated. An appropriate amount of pesticide/ chemicals is essential for achieving the desired smart farming and precision agricul...
Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields.
PloS one
Mar 25, 2021
Crop yield monitoring demonstrated the potential to improve agricultural productivity through improved crop breeding, farm management and commodity planning. Remote and proximal sensing offer the possibility to cut crop monitoring costs traditionally...
AgriPest: A Large-Scale Domain-Specific Benchmark Dataset for Practical Agricultural Pest Detection in the Wild.
Sensors (Basel, Switzerland)
Feb 25, 2021
The recent explosion of large volume of standard dataset of annotated images has offered promising opportunities for deep learning techniques in effective and efficient object detection applications. However, due to a huge difference of quality betwe...
sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks.
Plant molecular biology
Jan 1, 2021
We proposed an ensemble convolutional neural network model to identify sgRNA high on-target activity in four crops and we used one-hot encoding and k-mers for sequence encoding. As an important component of the CRISPR/Cas9 system, single-guide RNA (s...
Weed and Corn Seedling Detection in Field Based on Multi Feature Fusion and Support Vector Machine.
Sensors (Basel, Switzerland)
Dec 31, 2020
Detection of weeds and crops is the key step for precision spraying using the spraying herbicide robot and precise fertilization for the agriculture machine in the field. On the basis of k-mean clustering image segmentation using color information an...
Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data.
Journal of plant physiology
Dec 29, 2020
Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of the breeding cycle in major crops relevant for sustaining present demands for food, feed, and fuel. In contrast to classical approaches that emphasize the n...
Active and Passive Electro-Optical Sensors for Health Assessment in Food Crops.
Sensors (Basel, Switzerland)
Dec 29, 2020
In agriculture, early detection of plant stresses is advantageous in preventing crop yield losses. Remote sensors are increasingly being utilized for crop health monitoring, offering non-destructive, spatialized detection and the quantification of pl...
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