AIMC Topic: Hydrogen-Ion Concentration

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Artificial intelligence-driven food quality prediction: Applying machine learning ensemble models for dynamic forecasting of pork pH and meat color changes.

Food chemistry
This study presents a food chemistry-driven approach to predict post-slaughter pork quality dynamics, focusing on the biochemical mechanisms governing pH evolution and meat color development over 48 h. The interconversion of myoglobin redox states an...

A generalized platform for artificial intelligence-powered autonomous enzyme engineering.

Nature communications
Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we r...

Modeling Soil pH at regional scale using environmental covariates and machine learning algorithm.

Environmental monitoring and assessment
Soil pH serves as a critical indicator of soil chemistry and fertility, and mapping its spatial distribution holds significant importance for effective crop management. Digital soil mapping (DSM) is a commonly employed method for making rapid and cos...

Iterative enhancement of cutinase thermostability by multiple strategies based on combined directed evolution and computationally assisted design.

Bioresource technology
Cutinase exhibits versatile biocatalytic potential in polymer degradation, textile processing, and industrial biocatalysis, where enhancing the thermal stability under extreme conditions is essential for practical applications. To enhance the thermal...

A study on time-series prediction and analysis of acidity of Daqu based on multivariate data fusion and KNN-Attention-LSTM-XGBoost modeling.

Bioprocess and biosystems engineering
Daqu is a traditional Chinese brewing ingredient that serves dual functions of saccharification and fermentation during the brewing process. The acidity content during the Daqu fermentation process directly affects the quality of the Daqu. Traditiona...

Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis.

Journal of dairy science
Low reticuloruminal pH (rpH) for a prolonged period could lead to SARA. This disease negatively affects cow health and is associated with monetary losses for the dairy industry. The aim of this study was to predict rpH and SARA separately using diffe...

The Highly Conserved Cys95 Residue of Fructose-1,6-Bisphosphatase 1 Mediates the pH-Driven Structure and Activity of the Enzyme and Photosynthesis.

Plant, cell & environment
In Arabidopsis, exposure to microbial volatile compounds promotes thiol reduction of the Cys95 residue of the photosynthetic enzyme fructose-1,6-bisphosphatase (cFBP1). Although highly conserved in plants, the Cys95 function still remains unknown. We...

Prediction of Metal Nanoparticle Interactions with Soil Properties: Machine Learning Insights into Soil Health Dynamics.

ACS nano
Metal nanoparticles (MNPs) offer great potential to enable precision and sustainable agriculture. However, a comprehensive understanding of the interactions between multiple MNPs and soil properties, including impacts on overall soil health, remains ...

Unraveling four decades of soil acidification on the Qinghai-Tibetan Plateau: Patterns, drivers, and future projections.

Environmental pollution (Barking, Essex : 1987)
Soil acidification poses escalating threats to ecosystem functions, yet its spatiotemporal dynamics and drivers across vulnerable high-altitude regions remain poorly resolved. Here, we integrate four-decade soil surveys (1980s-2020s) with machine lea...

Unveiling the factors shaping variability in biomass productivity: Meta-analysis of outdoor pilot-scale microalgal cultures.

Bioresource technology
Meta-analysis and machine learning is used to investigate factors influencing variation in biomass productivity in outdoor algal systems. Understanding these factors is essential for optimizing algal systems. Mean productivity across the analysed stu...