[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under c...[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions,such as strong light exposure and weed interference.The aims are to develop an effective crop line extraction method by combining YOLOv8-G,Affinity Propagation,and the Least Squares method to enhance detection accuracy and performance in complex field environments.[Methods]The proposed method employs machine vision techniques to address common field challenges.YOLOv8-G,an improved object detection algorithm that combines YOLOv8 and Ghost‐NetV2 for lightweight,high-speed performance,was used to detect the central points of crops.These points were then clustered using the Affinity Propagation algorithm,followed by the application of the Least Squares method to extract the crop lines.Comparative tests were conducted to evaluate multiple backbone networks within the YOLOv8 framework,and ablation studies were performed to validate the enhancements made in YOLOv8-G.[Results and Discussions]The performance of the proposed method was compared with classical object detection and clustering algorithms.The YOLOv8-G algorithm achieved average precision(AP)values of 98.22%,98.15%,and 97.32%for corn detection at 7,14,and 21 days after emergence,respectively.Additionally,the crop line extraction accuracy across all stages was 96.52%.These results demonstrate the model's ability to maintain high detection accuracy despite challenging conditions in the field.[Conclusions]The proposed crop line extraction method effectively addresses field challenges such as lighting and weed interference,enabling rapid and accurate crop identification.This approach supports the automatic navigation of agricultural machinery,offering significant improvements in the precision and efficiency of field operations.展开更多
Tsavorite green colored by Cr3+/V3+ has been traditionally found and mined in Tanzania, Kenya and Madagascar in the Neoproterozoic Mozambique metamorphic belt (NMMB), and recently be found in Sanjiang, Litang, Sichuan...Tsavorite green colored by Cr3+/V3+ has been traditionally found and mined in Tanzania, Kenya and Madagascar in the Neoproterozoic Mozambique metamorphic belt (NMMB), and recently be found in Sanjiang, Litang, Sichuan, China. The differences of the chemical formula, spectroscopic features, as well as the concentrations of the V2O3 and Cr2O3 in the tsavorite crystals collected from major international deposits and Sanjiang, China have been investigated using EPMA, XRF, UV-VIS spectrometers, FTIR, Raman scattering microscopy, DiamondView TM techniques. It was found that the chemical formulas of African tsavorite and Chinese tsavorite are Ca3(Al,V)2[SiO4]3 and Ca3(Al,Cr)2[SiO4]3, respectively, indicating that tsavorite is a solid solution between dominant grossular and minor goldmanite and uvarovite. Two broad bands centered at 430 nm and 605 nm were the main absorption features in the tsavorite samples, which attribute to the absorption of Cr3+ and/or V3+ ions in the lattice. The green coloration is caused by Cr3+ and/or V3+ ions resulting in the absorption of purple and red components of the visible light. Absorptions caused of Fe3+ and Fe2+ ions could add the bluish color component in some of tsavorite samples. The intensity of green color is proportional to the concentrations of V2O3 and Cr2O3. The basic gemological properties, such as refractive index in the investigated samples were presented, and the definition and chemical and spectroscopic properties of tsavorite are discussed.展开更多
文摘[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions,such as strong light exposure and weed interference.The aims are to develop an effective crop line extraction method by combining YOLOv8-G,Affinity Propagation,and the Least Squares method to enhance detection accuracy and performance in complex field environments.[Methods]The proposed method employs machine vision techniques to address common field challenges.YOLOv8-G,an improved object detection algorithm that combines YOLOv8 and Ghost‐NetV2 for lightweight,high-speed performance,was used to detect the central points of crops.These points were then clustered using the Affinity Propagation algorithm,followed by the application of the Least Squares method to extract the crop lines.Comparative tests were conducted to evaluate multiple backbone networks within the YOLOv8 framework,and ablation studies were performed to validate the enhancements made in YOLOv8-G.[Results and Discussions]The performance of the proposed method was compared with classical object detection and clustering algorithms.The YOLOv8-G algorithm achieved average precision(AP)values of 98.22%,98.15%,and 97.32%for corn detection at 7,14,and 21 days after emergence,respectively.Additionally,the crop line extraction accuracy across all stages was 96.52%.These results demonstrate the model's ability to maintain high detection accuracy despite challenging conditions in the field.[Conclusions]The proposed crop line extraction method effectively addresses field challenges such as lighting and weed interference,enabling rapid and accurate crop identification.This approach supports the automatic navigation of agricultural machinery,offering significant improvements in the precision and efficiency of field operations.
文摘Tsavorite green colored by Cr3+/V3+ has been traditionally found and mined in Tanzania, Kenya and Madagascar in the Neoproterozoic Mozambique metamorphic belt (NMMB), and recently be found in Sanjiang, Litang, Sichuan, China. The differences of the chemical formula, spectroscopic features, as well as the concentrations of the V2O3 and Cr2O3 in the tsavorite crystals collected from major international deposits and Sanjiang, China have been investigated using EPMA, XRF, UV-VIS spectrometers, FTIR, Raman scattering microscopy, DiamondView TM techniques. It was found that the chemical formulas of African tsavorite and Chinese tsavorite are Ca3(Al,V)2[SiO4]3 and Ca3(Al,Cr)2[SiO4]3, respectively, indicating that tsavorite is a solid solution between dominant grossular and minor goldmanite and uvarovite. Two broad bands centered at 430 nm and 605 nm were the main absorption features in the tsavorite samples, which attribute to the absorption of Cr3+ and/or V3+ ions in the lattice. The green coloration is caused by Cr3+ and/or V3+ ions resulting in the absorption of purple and red components of the visible light. Absorptions caused of Fe3+ and Fe2+ ions could add the bluish color component in some of tsavorite samples. The intensity of green color is proportional to the concentrations of V2O3 and Cr2O3. The basic gemological properties, such as refractive index in the investigated samples were presented, and the definition and chemical and spectroscopic properties of tsavorite are discussed.
