## 4 Application of AI in Food Integrity
### AI and ML in the Detection of Food Fraud
\begin{table}
\begin{tabular}{p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt}} \hline \hline \multirow{2}{*}{**S/No.**} & **Intelligent Approach** & **Model(s)** & **Application** & **Objective** & **Food Commodity** & **Reference** \\ \hline \multirow{2}{*}{1.} & \multirow{2}{*}{AI} & & Food quality control and regulatory compliance & \multirow{2}{*}{Food inspection system} & Raspberries, almonds, strawberries, cashew, carrots, and blueberries & [49] \\ \hline \multirow{2}{*}{2.} & \multirow{2}{*}{ML} & \multirow{2}{*}{SVM} & Food quality control and regulatory compliance & Discriminate defective grains & \multirow{2}{*}{Rice} & [51] \\ \hline \multirow{2}{*}{3.} & \multirow{2}{*}{ML} & \multirow{2}{*}{Fuzzy system} & Food quality control and regulatory compliance & Categorizing and grading & Mozafati dates & [52] \\ \hline \multirow{2}{*}{4.} & \multirow{2}{*}{ML} & Radial basis function (RBF) kernel-SVM classifier & Food quality control and regulatory compliance & Identify and grade food products & Tomatoes & [53] \\ \hline \multirow{2}{*}{5.} & \multirow{2}{*}{ML} & Partial least squares (PLS) regression & Food quality control and regulatory compliance & Predict nutritional/chemical composition & \multirow{2}{*}{Mutation} & [55] \\ \hline \multirow{2}{*}{6.} & \multirow{2}{*}{ML} & \multirow{2}{*}{KNN} & Food quality control and regulatory compliance & Detection and classification of mechanically-damaged fruits & \multirow{2}{*}{’Manila’ mangos} & [56] \\ \hline \multirow{2}{*}{7.} & \multirow{2}{*}{ML} & \multirow{2}{*}{PCA} & Food quality control and regulatory compliance & Detection of fecal contamination & Apple skins & [57] \\ \hline \multirow{2}{*}{8.} & \multirow{2}{*}{AI} & \multirow{2}{*}{Mask-RCNN and regulatory compliance} & Food quality control and regulatory identification, and dimensions estimation & Fruit detection, identification, and dimensions estimation & Tomatoes & [59] \\ \hline \multirow{2}{*}{9.} & \multirow{2}{*}{ML} & classification and regression trees (CART) and LDA & Food quality control and regulatory compliance & Early detection of rottenness caused by _Penicillium digitatum_ & Mandarins & [58] \\ \hline \multirow{2}{*}{10} & \multirow{2}{*}{AI and ML} & \multirow{2}{*}{Food supply chain traceability} & Swift source tracking of agricultural commodities & \multirow{2}{*}{Various food products} & [63] \\ \hline \multirow{2}{*}{11.} & \multirow{2}{*}{ML} & Bayesian regression and random forest & Food supply chain traceability & Food supply chain tracing & Perishable foods & [65] \\ \hline \multirow{2}{*}{12.} & \multirow{2}{*}{ML} & \multirow{2}{*}{SVM} & Food supply chain traceability & Trace geographical origin of food & Refined sugar & [66] \\ \hline \multirow{2}{*}{13.} & \multirow{2}{*}{ML} & \multirow{2}{*}{OPLS-DA} & Food supply chain traceability & Trace geographical origin of food & Saanen goat milk & [67] \\ \hline \multirow{2}{*}{14.} & \multirow{2}{*}{ML} & PCA and PLS-DA & Food supply chain traceability & Trace geographical origin of food & _Crassostrea gigas_ oyster species & [68] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Applications of AI and ML in food integrity.