## 4 Application of AI in Food Integrity
### AI and ML in the Detection of Food Fraud
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**S/No.**} & **Intelligent Approach** & **Model(s)** & **Application** & **Objective** & **Food Commodity** & **Reference** \\ \hline \multirow{4}{*}{33.} & \multirow{4}{*}{ML} & Decision tree, random forest, gradient boost decision tree (GBDT), and adaptive boosting models & Food pathogen detection, classification, and virulence/resistance prediction & Prediction of microorganisms that cause foodborne illnesses & [88] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{34.} & \multirow{4}{*}{ML} & PCA, Kernel principal component analysis (KPCA), decision tree decision tree (DT), CART, and PCA-SVM classifier & Food pathogen detection, classification, and virulence/resistance prediction & Rapidly identify food-borne pathogens at the single-cell level & [89] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{35.} & \multirow{4}{*}{ML} & Rules-based (RB) algorithm and logistic regression algorithm & Food pathogen detection, classification, and virulence/resistance prediction & Prediction of antimicrobial resistance profiles & [90] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{36.} & \multirow{4}{*}{ML} & Hidden Markov Models (HMMs) and SVM & Food pathogen detection, classification, and virulence/resistance prediction & Syndromic surveillance monitoring and disease outbreak detection & Various food commodities & [91] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{37.} & \multirow{4}{*}{ML} & Variations of random forest, SVM, logistic regression, and linear regression & Food pathogen detection, classification, and virulence/resistance prediction & Classification and estimation of pathogenic bacterial persistence & Various food commodities & [92] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{38.} & \multirow{4}{*}{ML} & \multirow{4}{*}{Random forest prediction} & Food pathogen detection, classification, and virulence/resistance prediction & Distinguish between invasive and long-established gastrointestinal & [93] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{39.} & \multirow{4}{*}{AI} & R-CNN deep learning model & Food pathogen detection, classification, and virulence/resistance prediction & Rapid pathogen detection & From liquid food to agricultural water & [94] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{40.} & \multirow{4}{*}{ML} & SVM, Naive Bayes, Adaboost, and random forest prediction & Food pathogen detection, classification, and virulence/resistance prediction & Forecast antimicrobial resistance behaviors of & [95] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \multirow{4}{*}{41.} & \multirow{4}{*}{ML} & Different ML models including PCA, PLS-DA, and KNN & Chemical and biochemical food hazards prediction and analysis & Classification and prediction of aflatoxin B1 (AFB1) levels & Maize kernels & [96] \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \cline{1-1} \cline{2-6}  & & & & & \\ \hline \hline \end{tabular}
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