Using UAV-based multispectral remote sensing imagery combined with DRIS method to diagnose leaf nitrogen nutrition status in a fertigated apple orchard

Article Agronomy

Phenology determines water use strategies of three economic tree species in the semi-arid Loess Plateau of China

Wenjie Wu et al.

Summary: This study measured variations in water use strategies of peach, walnut, and apple trees and found differences in water source utilization and drought stress responses among the three tree species.

AGRICULTURAL AND FOREST METEOROLOGY (2022)

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Article Agronomy

Optimizing irrigation and fertilization at various growth stages to improve mango yield, fruit quality and water-fertilizer use efficiency in xerothermic regions

Guangzhao Sun et al.

Summary: The study found that the factors influencing fruit yield and water use efficiency were irrigation amount, fertilization rate at the fruit expansion stage, and fertilization rate at the flowering stage, while the factors influencing water, vitamin C and carotenoid contents in fruit were irrigation amount, fertilization rate at the fruit ripening stage, and fertilization rate at the fruit expansion stage. Additionally, the factors influencing soluble solids and total sugar contents were irrigation amount, fertilization rate at the fruit ripening stage, and fertilization rate at the flowering stage.

AGRICULTURAL WATER MANAGEMENT (2022)

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Article Agriculture, Multidisciplinary

Determining leaf nutrient concentrations in citrus trees using UAV imagery and machine learning

Lucas Costa et al.

Summary: This study proposes a novel methodology to determine leaf nutrient concentrations of citrus trees using UAV multispectral imagery and AI. The model developed showed high precision in determining macronutrients and moderate precision in determining micronutrients in citrus field trials. Overall, the UAV- and AI-based methodology proved efficient in determining nutrient concentrations and generating nutrient maps in commercial citrus orchards.

PRECISION AGRICULTURE (2022)

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Article Plant Sciences

Improving Fruit Yield and Quality of Mountain Apple (Malus domestica Borkh. cv. Hanfu) by Light Deficit Surge-Root Irrigation in the Loess Plateau, China

Kun Hao et al.

Summary: This study aims to investigate the effect of deficit surge-root irrigation (SRI) in different phenological phases on mountain apples in Northern Shaanxi. The results suggest that light deficit irrigation during specific phenological stages can stabilize fruit yield and improve apple quality. This provides a theoretical basis for further research and management in this area.

JOURNAL OF SOIL SCIENCE AND PLANT NUTRITION (2022)

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Article Environmental Sciences

Rapid Diagnosis of Nitrogen Nutrition Status in Summer Maize over Its Life Cycle by a Multi-Index Synergy Model Using Ground Hyperspectral and UAV Multispectral Sensor Data

Nana Han et al.

Summary: This study constructed a diagnostic model for the nitrogen life cycle of summer maize based on ground and UAV data, and evaluated the change in nitrogen nutrient status. The model demonstrated high accuracy and stability, providing valuable insights for smart agriculture and food security.

ATMOSPHERE (2022)

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Article Environmental Sciences

Carbon footprint of cotton production in China: Composition, spatiotemporal changes and driving factors

Weibin Huang et al.

Summary: This study analyzed the carbon footprint of cotton production in China and identified the main drivers of carbon emissions. It found that fertilizer, irrigation electricity, and agricultural film were significant factors at the micro level, while the economic factor played a key role at the macro level. Improving efficiency and ensuring high-quality development are effective strategies to reduce carbon emissions.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

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Article Horticulture

Apple leaf macro- and micronutrient content as affected by soil treatments with fertilizers and microorganisms

Waldemar Treder et al.

Summary: The effects of bacterial and fungal inocula on the nutritional status of 'Sampion' apple trees were evaluated. The application of beneficial microorganisms and mineral fertilization can modify the mineral composition of apple leaves and increase the concentration of nitrogen, calcium, magnesium, sulfur, and other elements.

SCIENTIA HORTICULTURAE (2022)

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Article Chemistry, Analytical

Inversion of Nitrogen Concentration in Apple Canopy Based on UAV Hyperspectral Images

Wei Li et al.

Summary: This study explores an effective approach for inversing and mapping the distributions of canopy nitrogen concentration (CNC) based on Unmanned Aerial Vehicle (UAV) hyperspectral image data. The findings show that the BPNN model based on random two-band spectral indices and red-edge parameters is the optimal model for accurately retrieving CNC.

SENSORS (2022)

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Article Environmental Sciences

The Self-Supervised Spectral-Spatial Vision Transformer Network for Accurate Prediction of Wheat Nitrogen Status from UAV Imagery

Xin Zhang et al.

Summary: This study proposes a novel deep learning framework that utilizes remote sensing and deep learning techniques to accurately predict the nitrogen status of wheat fields in UAV digital aerial imagery. Compared to other advanced models, this method achieves high accuracy and generalizability.

REMOTE SENSING (2022)

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Article Environmental Sciences

Prediction of the Nitrogen, Phosphorus and Potassium Contents in Grape Leaves at Different Growth Stages Based on UAV Multispectral Remote Sensing

Xuelian Peng et al.

Summary: In this study, a prediction model for the nutrient contents in grape leaves was established using unmanned aerial vehicle (UAV) remote sensing technology and machine learning algorithms. By optimizing the combination of spectral variables and machine learning models, accurate predictions of nitrogen, phosphorus, and potassium nutrient contents during different grape growth periods were achieved.

REMOTE SENSING (2022)

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Article Agriculture, Multidisciplinary

Estimation of nitrogen nutrition index in rice from UAV RGB images coupled with machine learning algorithms

Zhengchao Qiu et al.

Summary: The combination of RGB images from UAV and machine learning algorithms can be used for rapid and accurate estimation of rice Nitrogen Nutrition Index (NNI), which improves nitrogen use efficiency and provides guidance for precision fertilization in rice production.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

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Article Remote Sensing

Improving Unmanned Aerial Vehicle (UAV) remote sensing of rice plant potassium accumulation by fusing spectral and textural information

Jingshan Lu et al.

Summary: This study compares the performance of different sets of spectral and textural indices derived from UAV data for estimating rice K nutritional status, and finds that fusion of spectral and textural indices allows for more accurate mapping of PKA.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2021)

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Article Environmental Sciences

Estimating Leaf Nitrogen Content in Corn Based on Information Fusion of Multiple-Sensor Imagery from UAV

Xingang Xu et al.

Summary: This study utilized UAVs equipped with multispectral and RGB sensors to evaluate leaf nitrogen content in corn, introducing a novel CASIs method for estimation. CASIs proved to be more effective than traditional VIs for estimating LNC in all growth stages, with the R1 stage showing the best performance.

REMOTE SENSING (2021)

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Article Environmental Sciences

Hyperspectral imagery to monitor crop nutrient status within and across growing seasons

Nanfeng Liu et al.

Summary: Imaging spectroscopy is a valuable tool for monitoring nutrient status and predicting yield of potatoes across cultivars, growth stages, and growing seasons. Ordinary least-squares regression models showed poor predictions, while partial least-squares regression models performed well using different spectral regions. Cross-season models exhibited some bias and require further optimization.

REMOTE SENSING OF ENVIRONMENT (2021)

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Article Environmental Sciences

Estimation of Apple Tree Leaf Chlorophyll Content Based on Machine Learning Methods

Na Ta et al.

Summary: The study evaluated four different approaches for estimating leaf chlorophyll content of apple tree leaves at five growth stages, showing that the random forest model had the highest prediction accuracy at different growth stages.

REMOTE SENSING (2021)

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Article Agronomy

Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices

Guomin Shao et al.

Summary: This study aimed to explore the potential of leaf area index (LAI) and multispectral vegetation indices (VIs) obtained by an unmanned aerial vehicle (UAV) for estimating the crop coefficient (Kc) value for maize on a field scale. The results showed that the RFR algorithm effectively estimated maize Kc values based on ground-based LAI and UAV-based VIs, which could provide a potential solution for the distribution of water use and precision irrigation on a field scale.

AGRICULTURAL WATER MANAGEMENT (2021)

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Article Computer Science, Artificial Intelligence