Prediction of pork loin quality using online computer vision system and artificial intelligence model

A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies

“…References Accuracy of 92.5%, 75.0% (Sun et al, 2018) Correlation coefficient of 0.98734 (Taheri et al, 2019) Correlation coefficient of 0.926 (Tappi et al, 2017) Accuracy of 81.7% (Chmiel et al, 2016a, b) Error of 7.8% (Mortensen et al, 2016) Note: Support vector machine (SVM), genetic algorithm (GA), artificial neuronal network (ANN), analyses of variance (ANOVA), least significant difference (LSD), and multivariate linear regression (MLR).…”

“…In recent years, with the increasing attention and continuous development of artificial intelligence, additionally, the growing demand for high-quality and safe meat paired with increasing population, various non-destructive detection technologies have become more and more widely used in the field of meat quality testing (Chen et al, 2013). Throughout the existing research achievements on non-destructive detection for meat quality (Table 1-Table 4), the studies on meat quality mainly focuses on the four categories of beef (Wei et al, 2019), pork (Sun et al, 2018), lamb (Zheng et al, 2019), and poultry (chicken) (Jiang et al, 2017a), including the evaluation of sensory characteristics, detection of nutrient components, identification of physical-chemical properties, discrimination of processing quality (quantitative analysis) and judgement of safety quality (qualitative analysis) (Taheri-Garavand et al, 2019b).…”

A Review on Computer Vision Technology for Monitoring Poultry Farm—Application, Hardware, and Software

“…It includes automation of the house management, behavior, and welfare [11,[29][30][31][32][33][34][35][36][37][38][39][40], disease detection [28,[41][42][43][44][45][46][47], weight measurement [27,[48][49], slaughtering process [50][51], carcass quality [52][53][54][55], and egg examination [56][57][58][59][60][61][62][63][64][65]. On the other hand, computer vision also popular on other livestock monitoring, such as pig [73][74][75][76][77][78][79][80], sheep or cattle [81][82]…”

A Novel Chicken Meat Quality Evaluation Method Based on Color Card Localization and Color Correction

“…Image analysis based methods were also used to predict the weight of live chickens [11] and predict the IMF content of fat meat [12]. Sun et al [13] realized the online color and marbling detection of pork loin. Lu et al [14] predicted the color fraction of pork accurately.…”