Plant Phenomics is an online-only open access journal published in affiliation with Nanjing Agricultural University (NAU) and distributed by AAAS.
15/09/2023
Using spectral preprocessing and deep transfer learning, we efficiently estimated chlorophyll content in varying cotton batches. This innovation streamlines evaluations of cotton's nutritional status. 🌱🔍
Details: https://spj.science.org/doi/10.34133/2022/9813841
15/09/2023
We developed a comprehensive model for canopy photosynthesis, capturing both foliar and nonfoliar tissues. Validated on wheat, it offers insights into optimizing photosynthesis and designing efficient crops. 🌾📊
Details: https://spj.science.org/doi/10.34133/2022/9758148
15/09/2023
Using airborne LiDAR and computer graphics, we've developed a method to model forest canopy radiation, showing accurate radiant flux measurements vital for light-dependent biophysical studies. 🌲🌞
Details: https://spj.science.org/doi/10.34133/2022/9856739
Review on high-throughput field phenotyping: Emphasizing autonomous robotic systems. Details on components, navigation, and applications. Discussing challenges & future directions. 🌱🤖
Details: https://spj.science.org/doi/10.34133/2022/9760269
14/09/2023
Addressing the challenge of detecting small green fruits, our BFP Net innovatively balances features for improved small apple detection in orchards. Better accuracy, great generalization! 🍏🔍
Details: https://spj.science.org/doi/10.34133/2022/9892464
14/09/2023
Introducing SegVeg: A robust two-step approach for pixel-wise RGB image segmentation into background, green, and senescent vegetation. High accuracy, with the toolkit now publicly available! 🌱📸
Details: https://spj.science.org/doi/10.34133/2022/9803570
14/09/2023
EasyDAM_V2: A breakthrough model for cost-effective cross-species fruit detection labeling. Achieved 82.1% precision for pitayas and 85% for mangoes. Redefining smart orchard tech! 🍊🍍
Details: https://spj.science.org/doi/10.34133/2022/9761674
14/09/2023
UAV-based multisource data combined with ensemble learning models significantly boosts accuracy in estimating maize phenotypic traits, aiding efficient breeding. Best results: LAI (0.852), FW (0.888), DW (0.929). 🌽🚁
Details: https://spj.science.org/doi/10.34133/2022/9802585
14/09/2023
Hyperspectral and chlorophyll fluorescence imaging combined with deep fusion models detect rice stress from pollutants with 97.7% accuracy. A breakthrough for environmental stress phenotyping. 🌾🔍
Details: https://spj.science.org/doi/10.34133/2022/9851096
12/09/2023
Using UAVs with imaging tech, we can accurately evaluate Chinese cabbage traits, like width, length, and chlorophyll content. Efficient and reliable for crop phenotyping! 🌱🚁
Details: https://spj.science.org/doi/10.34133/plantphenomics.0007
12/09/2023
Introducing SE-COTR: Advanced deep learning model for accurate, real-time green apple segmentation in natural orchards. Boosts efficiency in intelligent agriculture. 🍏🤖
Details: https://spj.science.org/doi/10.34133/plantphenomics.0005
12/09/2023
Introducing an innovative method for automatic cassava root analysis. Enables faster, reliable phenotyping for high-yield breeding. Crucial for global starch supply. 🌱📊
Details: https://spj.science.org/doi/10.34133/2022/9767820
12/09/2023
Sorghum's root system architecture (RSA) responds variably to phosphorus levels. Study finds genotype-dependent plasticity, suggesting potential root trait trade-offs. Vital for crop optimization. 🌾🔬
Details: https://spj.science.org/doi/10.34133/plantphenomics.0002
12/09/2023
New deep learning approach accurately models individual strawberry plant canopies and biomass from high-res images. Groundbreaking results using VGG-16 & ResNet-50. 🍓🌱
Details: https://spj.science.org/doi/10.34133/2022/9850486
11/09/2023
Improved Mask R-CNN model accurately detects and reconstructs vine fruit tree branches, aiding harvest robots and phenotypic data extraction, even in complex orchard backgrounds. 🤖🌳
Details: https://spj.science.org/doi/10.34133/plantphenomics.0088
11/09/2023
UAV multispectral imagery improves winter wheat yield predictions. Our new Spectral-Textural Index (SPSI) increases accuracy, reducing spectral saturation. Crucial for sustainable farming. 🌾🚁
Details: https://spj.science.org/doi/10.34133/plantphenomics.0087
11/09/2023
Using drone tech and image analysis, we accurately predicted broccoli head sizes, determining optimal harvest dates, reducing food loss and boosting profits. 🥦🚁
Details: https://spj.science.org/doi/10.34133/plantphenomics.0086
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