AIMC Topic: Fertilizers

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Unlocking groundwater desalination potential for agriculture with fertilizer drawn forward osmosis: prediction and performance optimization via RSM and ANN.

Environmental science and pollution research international
The agricultural sector uses 70% of the world's freshwater. As clean water is extracted, groundwater quality decreases, making it difficult to grow crops. Brackish water desalination is a promising solution for agricultural areas, but the cost is a b...

Evaluating the efficacy of vermicomposted products in rain-fed wetland rice and predicting potential hazards from metal-contaminated tannery sludge using novel machine learning tactic.

Chemosphere
The study assessed the ecotoxicity and bioavailability of potential metals (PMs) from tannery waste sludge, alongside addressing the environmental concerns of overuse of chemical fertilizers, by comparing the impacts of organic vermicomposted tannery...

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Waste management (New York, N.Y.)
Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to ...

Dissolved organic matter evolution and straw decomposition rate characterization under different water and fertilizer conditions based on three-dimensional fluorescence spectrum and deep learning.

Journal of environmental management
Straw returning is a sustainable way to utilize agricultural solid waste resources. However, incomplete decomposition of straw will cause harm to crop growth and soil quality. Currently, there is a lack of technology to timely monitor the rate of str...

Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm.

Sensors (Basel, Switzerland)
The application of agricultural robots can liberate labor. The improvement of robot sensing systems is the premise of making it work. At present, more research is being conducted on weeding and harvesting systems of field robot, but less research is ...

Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning.

PloS one
Portable X-ray fluorescence (pXRF) and Diffuse Reflectance Fourier Transformed Mid-Infrared (DRIFT-MIR) spectroscopy are rapid and cost-effective analytical tools for material characterization. Here, we provide an assessment of these methods for the ...

Deep Learning for Non-Invasive Diagnosis of Nutrient Deficiencies in Sugar Beet Using RGB Images.

Sensors (Basel, Switzerland)
In order to enable timely actions to prevent major losses of crops caused by lack of nutrients and, hence, increase the potential yield throughout the growing season while at the same time prevent excess fertilization with detrimental environmental c...

Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice.

Scientific reports
Leaf nitrogen content (LNC) is a significant factor which can be utilized to monitor the status of paddy rice and it requires a reliable approach for fast and precise quantification. This investigation aims to quantitatively analyze the correlation b...

Machine learning-driven optimization of arsenic phytoextraction using amendments.

Ecotoxicology and environmental safety
Exogenous amendments are crucial for enhancing the remediation efficiency of arsenic-contaminated soils by Pteris vittata. However, their effectiveness is unstable due to various factors, and neglecting their economic costs hinder broader application...

Predicting growth parameters of biofertilizer inoculated pepper, using root capacitance assessments and artificial neural networks in two soils.

Biologia futura
Monitoring the root system plays an important role in understanding plant physiological processes; however, its assessment using non-destructive methods remains challenging. Here, we evaluate the utility of root capacitance (C) as a practical indicat...