in Agriculture: A Review
A survey of machine learning in farming finds it already predicts yields, spots diseases and weeds, and monitors livestock, soil and water from sensor data.
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The Combine0 comments1mo ago 3,287 citations
Machine Learning Applications for : A Comprehensive Review
Machine learning now underpins smart farming — predicting soil properties, crop yields, diseases, weeds, livestock health and automating irrigation and harvesting.
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The Combine0 comments1mo ago 1,090 citations
The Path to Smart Farming: Innovations and Opportunities in
Drones, sensors, IoT and machine learning can raise crop yields while cutting waste, but cost, data management and slow farmer adoption still hold precision agriculture back.
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The Combine0 comments1mo ago 756 citations
Crop Yield Prediction in
Combining farm sensor data with big-data and AI methods can make crop yield forecasts far more useful than traditional statistical models alone.
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The Combine0 comments1mo ago 54 citations
A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving with IoT-Driven Sensor Networks and Data Analytics
A network of field sensors feeding live soil and weather data into predictive algorithms helped farmers raise crop yields and cut wasted water and fertiliser.
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The Combine0 comments1mo ago 5 citations
Optimizing nitrogen fertilization in mustard through GreenSeeker-based precision agriculture: Impacts on productivity, economics, and environmental sustainability
Using a handheld GreenSeeker sensor to time and size nitrogen doses in mustard raised seed yield 22.75% while using 18.7% less fertilizer than standard practice.
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The Combine0 comments21d ago
Controlled-Release Fertilizers: Innovations, Challenges, and Practical Applications
Slow-release fertilizer coatings can cut nutrient waste and boost yields, but plastic coatings shed microplastics and release timing still fails under real field conditions.
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The Combine0 comments29d ago
Generation of spatially and temporally fine-resolution imagery using STF algorithms and post-processing
Fusing near-daily 3 m satellite images with sparse 0.05 m drone photos produced daily 0.5 m crop maps, with the ESTARFM algorithm plus CACAO smoothing performing best.
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The Combine0 comments1mo ago
A review: research progress on intelligent technologies for orchard yield monitoring
No single sensor or algorithm can estimate orchard yield alone — ground cameras count fruit best, while drones and spectral sensors map yield across regions.
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The Combine0 comments1mo ago
for yield prediction in staple crops: a review
Drone-based crop yield prediction works, but its accuracy is limited less by fancy models than by mismatched, poor-quality ground-truth yield data and untested transfer across years and regions.
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The Combine0 comments1mo ago
Dynamic Prediction of Maize Tasseling Stage Based on UAV Time-Series Plant Height Growth Curves: A Framework Coupling UAV-CHM-POI
Drone LiDAR tracking of maize height over time predicts tasseling within about 2.6 days, replacing subjective manual field scouting.
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The Combine0 comments1mo ago