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Published Date::26/09/2024
Discover the recent breakthroughs in data analysis, machine learning, and artificial intelligence that are revolutionizing industries such as food, water, and agriculture.
Discover the recent breakthroughs in data analysis, machine learning, and artificial intelligence that are revolutionizing industries such as food, water, and agriculture.
We live in a data-driven world, and spectroscopy is at the forefront of several data innovations. Here, we've compiled recent research news that highlights the latest advancements in data analysis, machine learning (ML), and artificial intelligence (AI).
A recent study by researchers from the University of Campinas (UNICAMP) and IMT Nord Europe tested an electronic tongue (e-tongue) prototype for food and beverage analysis. The device accurately distinguished between fresh and industrialized coconut water by measuring impedance data and utilizing machine learning techniques like PCA and PLS-DA.
The e-tongue achieved over 90% accuracy in classifying samples based on key parameters like soluble solid content and titratable acidity. This tool, therefore, showcases its potential as a faster, cost-effective alternative to traditional methods when it comes to quality control in the food industry.
However, the authors acknowledge that further research is needed for commercial adoption.
Artificial intelligence and machine learning are also improving water quality monitoring. A recent review published in TrAC Trends in Analytical Chemistry highlighted how AI and ML are enhancing the detection of pollutants in water sources, such as drinking water, surface water, and wastewater, by analyzing spectral data.
AI-based models can quickly identify contaminants, predict water quality parameters, and support early warning systems, addressing challenges in traditional monitoring methods.
Although promising, several limitations remain, which include the need for large, diverse data sets. The review emphasizes the importance of selecting appropriate ML algorithms for specific water quality issues to ensure effective management.
AI-powered spectroscopy has the potential for rapid, non-destructive food analysis, but it faces significant challenges. A recent study published in Foods highlighted the need for larger data sets, better experimental designs, and robust validation to ensure AI-driven methods can reliably enhance food quality assessment and eventually replace traditional techniques.
Non-linear memory-based learning (N-MBL) has been developed to improve soil property predictions using visible near-infrared (vis-NIR) spectroscopy, a rapid, non-destructive method. Traditional linear models, like partial least squares regression, struggle to capture the complex relationships between soil properties and spectral data.
N-MBL, tested on a large soil spectral library, outperformed conventional models, especially in predicting soil organic matter and total nitrogen. This advancement in non-linear modeling offers a more accurate and reliable approach to soil analysis, with potential benefits for improving agricultural productivity and addressing global food security.
Multispectral analysis combined with chemometrics can enhance beer production efficiency. A recent study published in Food Chemistry demonstrates how combining near-infrared (NIR), Raman, and ultraviolet-visible (UV-vis) spectroscopy with chemometrics can improve the brewing process of Qingke beer, focusing on key components like sugars, amino nitrogen, and phenols.
Using neural network and partial least squares models, they achieved precise predictions, improving consistency and quality control in the brewing process.
About University of Campinas (UNICAMP) The University of Campinas is a public research university located in Campinas, São Paulo, Brazil.
About IMT Nord Europe IMT Nord Europe is a French graduate school of engineering located in Douai, France.
About Queen's University Belfast Queen's University Belfast is a public research university located in Belfast, Northern Ireland.
About Zhejiang University Zhejiang University is a public research university located in Hangzhou, Zhejiang, China.
About Sichuan University Sichuan University is a public research university located in Chengdu, Sichuan, China.
About Wuliangye Group Wuliangye Group is a Chinese company that produces baijiu, a type of Chinese liquor.
FAQS:
FAQS:
Q: What is the electronic tongue (e-tongue) prototype?
A: The e-tongue prototype is a device that uses machine learning techniques to analyze impedance data and distinguish between fresh and industrialized coconut water.
Q: How does AI-powered spectroscopy improve water quality monitoring?
A: AI-powered spectroscopy enhances the detection of pollutants in water sources by analyzing spectral data and identifying contaminants, predicting water quality parameters, and supporting early warning systems.
Q: What are the challenges faced by AI-powered spectroscopy in rapid food analysis?
A: AI-powered spectroscopy faces challenges such as small sample sizes, overuse of complex models, and difficulties in transitioning to industrial settings, which hinder its effectiveness in rapid food analysis.
Q: How does non-linear memory-based learning (N-MBL) improve soil property predictions?
A: N-MBL improves soil property predictions by capturing complex relationships between soil properties and spectral data, outperforming conventional linear models like partial least squares regression.
Q: How does multispectral analysis combined with chemometrics enhance beer production efficiency?
A: Multispectral analysis combined with chemometrics enhances beer production efficiency by improving the brewing process of Qingke beer, focusing on key components like sugars, amino nitrogen, and phenols, and achieving precise predictions.
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