专题:Leaf Properties and Growth Measurement

This cluster of papers focuses on the development and validation of non-destructive methods for estimating leaf area in various plant species. The methods include digital image analysis, allometric models, linear measurements, and artificial neural networks. The research also covers the relationship between leaf area and plant growth, as well as phytochemical studies.
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Quinoa (Chenopodium quinoa Willd.) Growth Dynamics and Yield under Varied Geometry and Fertility Levels

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Assessing some ecophysiological traits of Protea ‘Pink Ice’ for the quantification of productive parameters

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Morpho-Anatomical Adaptations in Mung Bean Under Drought Stress

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Evaluation of Nutritional Profile, Phytochemical Content, and Antioxidant Potential of Finger Millet Landraces from the Tribal Belt of Chhattisgarh, India

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Pantropical moist forests are converging towards a middle leaf longevity

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Code to support "Amazon rainforests are rejuvenating their canopies by producing more photosynthetically efficient young leaves under climate change"

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Pre-Sowing Seed Treatment with Glucose Boosts the Photosynthetic Efficiency, Metabolic Enzymes and Antioxidant Defense System to increase the Growth of <i>Abelmoschus esculentus</i> (L.) Moench

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Modelling water - use and yield of selected irrigated subtropical crops using machine learning and hybrid models in north - eastern South Africa

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Artificial intelligence-based modeling for accurate leaf area estimation in olive (Olea europaea L.) cultivars

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Bigger is not always better: Optimizing leaf area index with narrow-leaf shape in soybean

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