Multi-Trait Phenotypic Analysis and Biomass Estimation of Lettuce Cultivars Based on SFM-MVS
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| 发表在: | Agriculture vol. 15, no. 15 (2025), p. 1662-1690 |
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MDPI AG
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| 在线阅读: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 024 | 7 | |a 10.3390/agriculture15151662 |2 doi | |
| 035 | |a 3239016029 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231331 |2 nlm | ||
| 100 | 1 | |a Li, Tiezhu |u School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China; 2212316059@stmail.ujs.edu.cn (T.L.); 2112216012@stmail.ujs.edu.cn (Y.Z.); 2222216051@stmail.ujs.edu.cn (Z.C.); 2222216048@stmail.ujs.edu.cn (T.Y.) | |
| 245 | 1 | |a Multi-Trait Phenotypic Analysis and Biomass Estimation of Lettuce Cultivars Based on SFM-MVS | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a To address the problems of traditional methods that rely on destructive sampling, the poor adaptability of fixed equipment, and the susceptibility of single-view angle measurements to occlusions, a non-destructive and portable device for three-dimensional phenotyping and biomass detection in lettuce was developed. Based on the Structure-from-Motion Multi-View Stereo (SFM-MVS) algorithms, a high-precision three-dimensional point cloud model was reconstructed from multi-view RGB image sequences, and 12 phenotypic parameters, such as plant height, crown width, were accurately extracted. Through regression analyses of plant height, crown width, and crown height, and the R2 values were 0.98, 0.99, and 0.99, respectively, the RMSE values were 2.26 mm, 1.74 mm, and 1.69 mm, respectively. On this basis, four biomass prediction models were developed using Adaptive Boosting (AdaBoost), Support Vector Regression (SVR), Gradient Boosting Decision Tree (GBDT), and Random Forest Regression (RFR). The results indicated that the RFR model based on the projected convex hull area, point cloud convex hull surface area, and projected convex hull perimeter performed the best, with an R2 of 0.90, an RMSE of 2.63 g, and an RMSEn of 9.53%, indicating that the RFR was able to accurately simulate lettuce biomass. This research achieves three-dimensional reconstruction and accurate biomass prediction of facility lettuce, and provides a portable and lightweight solution for facility crop growth detection. | |
| 653 | |a Accuracy | ||
| 653 | |a Height | ||
| 653 | |a Agricultural production | ||
| 653 | |a Biomass | ||
| 653 | |a Corn | ||
| 653 | |a Area | ||
| 653 | |a Regression analysis | ||
| 653 | |a Crops | ||
| 653 | |a Cultivars | ||
| 653 | |a Machine learning | ||
| 653 | |a Lettuce | ||
| 653 | |a Prediction models | ||
| 653 | |a Decision trees | ||
| 653 | |a Efficiency | ||
| 653 | |a Crop growth | ||
| 653 | |a Image reconstruction | ||
| 653 | |a Support vector machines | ||
| 653 | |a Phenotyping | ||
| 653 | |a Convexity | ||
| 653 | |a Portable equipment | ||
| 653 | |a Three dimensional imaging | ||
| 653 | |a Algorithms | ||
| 653 | |a Plant growth | ||
| 653 | |a Light | ||
| 653 | |a Morphology | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Zhang Yixue |u Basic Engineering Training Center, Jiangsu University, Zhenjiang 212013, China | |
| 700 | 1 | |a Hu, Lian |u Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510640, China; lianhu@scau.edu.cn | |
| 700 | 1 | |a Zhao Yiqiu |u School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China; 2212316059@stmail.ujs.edu.cn (T.L.); 2112216012@stmail.ujs.edu.cn (Y.Z.); 2222216051@stmail.ujs.edu.cn (Z.C.); 2222216048@stmail.ujs.edu.cn (T.Y.) | |
| 700 | 1 | |a Cai Zongyao |u School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China; 2212316059@stmail.ujs.edu.cn (T.L.); 2112216012@stmail.ujs.edu.cn (Y.Z.); 2222216051@stmail.ujs.edu.cn (Z.C.); 2222216048@stmail.ujs.edu.cn (T.Y.) | |
| 700 | 1 | |a Yu, Tingting |u School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China; 2212316059@stmail.ujs.edu.cn (T.L.); 2112216012@stmail.ujs.edu.cn (Y.Z.); 2222216051@stmail.ujs.edu.cn (Z.C.); 2222216048@stmail.ujs.edu.cn (T.Y.) | |
| 700 | 1 | |a Zhang, Xiaodong |u School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China; 2212316059@stmail.ujs.edu.cn (T.L.); 2112216012@stmail.ujs.edu.cn (Y.Z.); 2222216051@stmail.ujs.edu.cn (Z.C.); 2222216048@stmail.ujs.edu.cn (T.Y.) | |
| 773 | 0 | |t Agriculture |g vol. 15, no. 15 (2025), p. 1662-1690 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3239016029/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3239016029/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3239016029/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |