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Agriculture

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The parable of arable land: Characterizing large scale land acquisitions through network analysis.

PloS one
Land is a scarce resource and its depletion is related to a combination of demographic and economic factors. Hence, the changes in dietary habits and increase in world population that upturn the food demand, are intertwined with a context of increasi...

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems.

Current opinion in biotechnology
Modern agriculture and food production systems are facing increasing pressures from climate change, land and water availability, and, more recently, a pandemic. These factors are threatening the environmental and economic sustainability of current an...

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network.

PloS one
This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country's To...

Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning.

Sensors (Basel, Switzerland)
Potato is the largest non-cereal food crop in the world. Timely estimation of end-of-season tuber production using in-season information can inform sustainable agricultural management decisions that increase productivity while reducing impacts on the...

Scaling Effects on Chlorophyll Content Estimations with RGB Camera Mounted on a UAV Platform Using Machine-Learning Methods.

Sensors (Basel, Switzerland)
Timely monitoring and precise estimation of the leaf chlorophyll contents of maize are crucial for agricultural practices. The scale effects are very important as the calculated vegetation index (VI) were crucial for the quantitative remote sensing. ...

Classification Accuracy Improvement for Small-Size Citrus Pests and Diseases Using Bridge Connections in Deep Neural Networks.

Sensors (Basel, Switzerland)
Due to the rich vitamin content in citrus fruit, citrus is an important crop around the world. However, the yield of these citrus crops is often reduced due to the damage of various pests and diseases. In order to mitigate these problems, several con...

Yield prediction with machine learning algorithms and satellite images.

Journal of the science of food and agriculture
BACKGROUND: Barley is one of the strategic agricultural products available in the world, and yield prediction is important for ensuring food security. One way of estimating a product is to use remote sensing data in conjunction with field data and me...

Multi-period evaluation and selection of rural wastewater treatment technologies: a case study.

Environmental science and pollution research international
Rapid population growth and agricultural development are generating a considerable amount of effluents, which poses threats to the quality of rural water resources as well as sanitary conditions. However, with a range of rural wastewater treatment (W...

Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture.

Sensors (Basel, Switzerland)
Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world's growing population while limiting environmental pollution. The aim of this pap...

Exploring the multiscale hydrologic regulation of multipond systems in a humid agricultural catchment.

Water research
Assessing the hydrologic processes over scales ranging from single wetland to regional is critical to understand the hydrologically-driven ecosystem services especially nutrient buffering of wetlands. Here, we present a novel approach to quantify the...