Summary of Machine Vision-based Assessment Of Fall Color Changes and Its Relationship with Leaf Nitrogen Concentration, by Achyut Paudel et al.
Machine Vision-Based Assessment of Fall Color Changes and its Relationship with Leaf Nitrogen Concentration
by Achyut Paudel, Jostan Brown, Priyanka Upadhyaya, Atif Bilal Asad, Safal Kshetri, Joseph R. Davidson, Cindy Grimm, Ashley Thompson, Bernardita Sallato, Matthew D. Whiting, Manoj Karkee
First submitted to arxiv on: 23 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The machine learning-based system developed in this study uses image datasets and computer vision techniques to quantify the change in apple tree leaf color and its correlation with leaf nitrogen content. The system, which utilizes a custom-defined metric called the yellowness index, was able to accurately estimate the proportion of yellow leaves per canopy and capture the gradual color transition from green to yellow over time. The gradient boosting method used in this study outperformed the K-means-based method in terms of computational time and accuracy, achieving an R-squared value of 0.72. This research has potential applications in precision agriculture and orchard management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study uses special cameras and computers to help farmers understand how healthy their apple trees are. Apple trees change color from green to yellow before shedding their leaves each year, and this study shows that the amount of nitrogen in the leaves can affect how quickly this happens. The researchers developed a new way to measure this leaf color change using computer vision techniques, which was better than an older method. This could help farmers use technology to take care of their trees more effectively. |
Keywords
» Artificial intelligence » Boosting » K means » Machine learning » Precision
