Plant Phenomics
@plantphenomics.bsky.social
An open access journal indexed in: #DOAJ #EI #PMC #SCIE (#JIF 2023: 7.6) #Scopus (#CiteScore2023: 8.6) etc. #PlantPhenomics #PlantPhenotyping #openaccess
We've developed ILCD, a VQA model for crop diseases, integrating coattention, MUTAN, and BiBa. Our new CDwPK-VQA dataset includes multi-attribute info. ILCD achieves 86.06% accuracy on CDwPK-VQA, outperforming others.
Details: doi.org/10.34133/plant…
Details: doi.org/10.34133/plant…
May 22, 2025 at 3:08 AM
We've developed ILCD, a VQA model for crop diseases, integrating coattention, MUTAN, and BiBa. Our new CDwPK-VQA dataset includes multi-attribute info. ILCD achieves 86.06% accuracy on CDwPK-VQA, outperforming others.
Details: doi.org/10.34133/plant…
Details: doi.org/10.34133/plant…
We integrated hyperspectral & metabolomic data to identify salt-tolerant Medicago truncatula mutants. By combining data & using upper-level metabolomics, we achieved high efficiency & accuracy.
Details: doi.org/10.1016/j.plap…
Details: doi.org/10.1016/j.plap…
May 15, 2025 at 3:09 PM
We integrated hyperspectral & metabolomic data to identify salt-tolerant Medicago truncatula mutants. By combining data & using upper-level metabolomics, we achieved high efficiency & accuracy.
Details: doi.org/10.1016/j.plap…
Details: doi.org/10.1016/j.plap…
New study uses 3D RTM & LiDAR to analyze light in larch plantations. Crown volume key for APAR, while competition still impacts. Combining tech helps optimize forest structure & guide precise management. #forestry #ecology
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
April 7, 2025 at 2:59 PM
New study uses 3D RTM & LiDAR to analyze light in larch plantations. Crown volume key for APAR, while competition still impacts. Combining tech helps optimize forest structure & guide precise management. #forestry #ecology
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New study uses YOLO v5, ResNet50, and DeepSORT models to analyze rice panicle traits via time - series images. Results show high accuracy in panicle counting and heading date estimation.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
April 7, 2025 at 2:58 PM
New study uses YOLO v5, ResNet50, and DeepSORT models to analyze rice panicle traits via time - series images. Results show high accuracy in panicle counting and heading date estimation.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Boosting rice yield via enhanced photosynthesis! New study uses sun-induced chlorophyll fluorescence (SIF) to accurately estimate key traits like Vcmax and gs. 🌱📈 #agritech #photosynthesis #cropscience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
April 7, 2025 at 2:57 PM
Boosting rice yield via enhanced photosynthesis! New study uses sun-induced chlorophyll fluorescence (SIF) to accurately estimate key traits like Vcmax and gs. 🌱📈 #agritech #photosynthesis #cropscience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New study proposes ALAEM algorithm to measure maize leaf orientation via RGB images. It shows leaf orientation varies by sowing density, row spacing, and genotype, impacting light interception.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 31, 2025 at 2:49 PM
New study proposes ALAEM algorithm to measure maize leaf orientation via RGB images. It shows leaf orientation varies by sowing density, row spacing, and genotype, impacting light interception.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
We propose PLPNet for precise tomato leaf disease detection. It uses perceptual adaptive convolution, location reinforcement attention, and proximity feature aggregation to tackle challenges like soil interference. Details: spj.science.org/doi/10.34133/p…
March 31, 2025 at 2:48 PM
We propose PLPNet for precise tomato leaf disease detection. It uses perceptual adaptive convolution, location reinforcement attention, and proximity feature aggregation to tackle challenges like soil interference. Details: spj.science.org/doi/10.34133/p…
New study: DC2Net detects Asian soybean rust early using hyperspectral imaging & deep learning. It combines deformable & dilated convolutions, achieving 96.73% accuracy. #CropDisease
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 31, 2025 at 2:47 PM
New study: DC2Net detects Asian soybean rust early using hyperspectral imaging & deep learning. It combines deformable & dilated convolutions, achieving 96.73% accuracy. #CropDisease
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New study uses AI & citizen science w/ smartphones to count coffee cherries on trees. Tested in Peru & Colombia, it shows promising results for scalable, low-cost crop monitoring in low-income regions. #AI #Coffee #CitizenScience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 31, 2025 at 2:47 PM
New study uses AI & citizen science w/ smartphones to count coffee cherries on trees. Tested in Peru & Colombia, it shows promising results for scalable, low-cost crop monitoring in low-income regions. #AI #Coffee #CitizenScience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Hyperspectral imaging + machine learning = game-changing tool for analyzing pigments in Neopyropia! Fast, nondestructive, and accurate phenotyping of phycoerythrin, phycocyanin, allophycocyanin.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 17, 2025 at 3:03 PM
Hyperspectral imaging + machine learning = game-changing tool for analyzing pigments in Neopyropia! Fast, nondestructive, and accurate phenotyping of phycoerythrin, phycocyanin, allophycocyanin.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
MG-YOLO: A novel detection algorithm for gray mold spores in precision ag. Combines Multi-head self-attention, BiFPN, and GhostCSP for high accuracy and speed. Achieves 0.983 accuracy in 0.009s/image, outperforming YOLOv5 by 6.8%.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 17, 2025 at 3:03 PM
MG-YOLO: A novel detection algorithm for gray mold spores in precision ag. Combines Multi-head self-attention, BiFPN, and GhostCSP for high accuracy and speed. Achieves 0.983 accuracy in 0.009s/image, outperforming YOLOv5 by 6.8%.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
PanicleNeRF uses smartphone videos to create 3D rice panicle models in fields. Combining SAM and YOLOv8, it achieves high segmentation accuracy and outperforms traditional methods. #Reconstruction
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 17, 2025 at 3:03 PM
PanicleNeRF uses smartphone videos to create 3D rice panicle models in fields. Combining SAM and YOLOv8, it achieves high segmentation accuracy and outperforms traditional methods. #Reconstruction
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New VQA model for crop disease detection! ILCD uses co-attention, MUTAN, and bias balancing to identify disease stages. Achieves 86.06% accuracy on CDwPK-VQA dataset. Check it out: github.com/SdustZYP/ILCD-…
Details: spj.science.org/doi/10.34133/p���
Details: spj.science.org/doi/10.34133/p���
March 12, 2025 at 12:03 PM
New VQA model for crop disease detection! ILCD uses co-attention, MUTAN, and bias balancing to identify disease stages. Achieves 86.06% accuracy on CDwPK-VQA dataset. Check it out: github.com/SdustZYP/ILCD-…
Details: spj.science.org/doi/10.34133/p���
Details: spj.science.org/doi/10.34133/p���
New study improves LNC retrieval in Ginkgo trees using modified ratio indices & advanced BRF spectra methods. Results show enhanced accuracy & highlight potential for better nitrogen status assessment. #LeafNitrogen #RemoteSensing
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 12, 2025 at 12:02 PM
New study improves LNC retrieval in Ginkgo trees using modified ratio indices & advanced BRF spectra methods. Results show enhanced accuracy & highlight potential for better nitrogen status assessment. #LeafNitrogen #RemoteSensing
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New study develops LNA estimation model for wheat using UAV & hyperspectral data. Models consider vertical heterogeneity, improving accuracy. RF-LNASum model shows best results with 17.8% error.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 12, 2025 at 12:02 PM
New study develops LNA estimation model for wheat using UAV & hyperspectral data. Models consider vertical heterogeneity, improving accuracy. RF-LNASum model shows best results with 17.8% error.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New study uses field excavation & 3D digitization to analyze grapevine root systems, revealing genotype-specific water uptake. Excavation & in situ digitization are accurate, despite some fine root length underestimation. #Sustainableagriculture
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 12, 2025 at 12:01 PM
New study uses field excavation & 3D digitization to analyze grapevine root systems, revealing genotype-specific water uptake. Excavation & in situ digitization are accurate, despite some fine root length underestimation. #Sustainableagriculture
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Using drones & deep learning, we measured plant maturity, stand count, & height in fields. CNN-LSTM models improved maturity prediction. This tech offers accuracy & cost savings over traditional methods. #DeepLearning
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 12, 2025 at 12:01 PM
Using drones & deep learning, we measured plant maturity, stand count, & height in fields. CNN-LSTM models improved maturity prediction. This tech offers accuracy & cost savings over traditional methods. #DeepLearning
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
We studied Phragmites australis & Typha orientalis to understand their canopy structure and solar radiation patterns. Key findings: layered solar radiation transmittance is more sensitive to canopy structure than pigments.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 10, 2025 at 11:52 AM
We studied Phragmites australis & Typha orientalis to understand their canopy structure and solar radiation patterns. Key findings: layered solar radiation transmittance is more sensitive to canopy structure than pigments.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
We propose using low-altitude aerial photography to create 3D point clouds and multispectral images of wheat plots. This helps extract dynamic digital phenotypes for genome-wide association studies. #Wheatplot #Image
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 10, 2025 at 11:52 AM
We propose using low-altitude aerial photography to create 3D point clouds and multispectral images of wheat plots. This helps extract dynamic digital phenotypes for genome-wide association studies. #Wheatplot #Image
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Introducing CHCNet: A unified model for counting cereal crops like maize, rice, sorghum, and wheat using few-shot learning. It reduces labeling costs and enhances cross-crop generalization. Check it out at cerealcropnet.com
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 10, 2025 at 11:52 AM
Introducing CHCNet: A unified model for counting cereal crops like maize, rice, sorghum, and wheat using few-shot learning. It reduces labeling costs and enhances cross-crop generalization. Check it out at cerealcropnet.com
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
New AI model for plant disease diagnostics outperforms GPT-4! Uses 3 stages of image-text alignment to generate accurate phenotypic descriptions. Check it out: plantext.samlab.cn #ChartGPT
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 10, 2025 at 11:51 AM
New AI model for plant disease diagnostics outperforms GPT-4! Uses 3 stages of image-text alignment to generate accurate phenotypic descriptions. Check it out: plantext.samlab.cn #ChartGPT
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Our study explores nitrogen responsiveness in wheat using drone phenotyping & machine learning. We quantify traits, map genetic components, and classify varieties for optimized N use. #nitrogen
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 4, 2025 at 11:42 AM
Our study explores nitrogen responsiveness in wheat using drone phenotyping & machine learning. We quantify traits, map genetic components, and classify varieties for optimized N use. #nitrogen
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Exploring plant drought response? Chlorophyll fluorescence beats spectral reflectance in reliability. But using both methods together offers best insights. Study on tobacco & barley leaves shows the way! #ClimateChange #PlantScience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 4, 2025 at 11:42 AM
Exploring plant drought response? Chlorophyll fluorescence beats spectral reflectance in reliability. But using both methods together offers best insights. Study on tobacco & barley leaves shows the way! #ClimateChange #PlantScience
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
🌾 CSNet revolutionizes wheat breeding! 🌾 Our count-supervised network uses quantity info to accurately count wheat ears without location data. Boosting yield & reducing costs! 🚀🌱 Learn more #AgTech #AI #FoodSecurity
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 4, 2025 at 11:41 AM
🌾 CSNet revolutionizes wheat breeding! 🌾 Our count-supervised network uses quantity info to accurately count wheat ears without location data. Boosting yield & reducing costs! 🚀🌱 Learn more #AgTech #AI #FoodSecurity
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
Using AI and computer vision, we developed models to detect sorghum panicles and estimate grain numbers from smartphone images. Our Sorghum-Net model achieved a 17% error rate, paving the way for efficient crop yield estimation.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…
March 4, 2025 at 11:41 AM
Using AI and computer vision, we developed models to detect sorghum panicles and estimate grain numbers from smartphone images. Our Sorghum-Net model achieved a 17% error rate, paving the way for efficient crop yield estimation.
Details: spj.science.org/doi/10.34133/p…
Details: spj.science.org/doi/10.34133/p…