Measuring water holding capacity in pork meat images using deep learning

Article Engineering, Electrical & Electronic

Automated assessment of water holding capacity in digital images

Renan Gomes de Andrade et al.

Summary: A method for automatic estimation of water holding capacity (WHC) of pork meat using filter paper images was proposed. Results indicated that this approach is a feasible solution for automatic WHC estimation.

SIGNAL IMAGE AND VIDEO PROCESSING (2022)

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Article Engineering, Chemical

Enhancing the water holding capacity of model meat analogues through marinade composition

Steven H. Cornet et al.

Summary: Meat analogues can have a more sustainable texture and juiciness through controlling water uptake based on ionic strength and pH levels. By adjusting the marinade pH and ionic strength, the water holding capacity (WHC) of meat analogues can be effectively controlled, leading to improved sensory characteristics and yield.

JOURNAL OF FOOD ENGINEERING (2021)

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Article Computer Science, Software Engineering

Wild boar recognition using convolutional neural networks

Luis Carlos Silva Junior et al.

Summary: This study focuses on monitoring wild boar populations and classifying them using convolutional neural networks. The results indicate that ResNet-50 has the highest accuracy in classifying wild boars and other similar species. The impact of wild boars on the ecosystem is significant, requiring effective control measures.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2021)

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Article Computer Science, Artificial Intelligence

Automated detection and counting of Artemia using U-shaped fully convolutional networks and deep convolutional networks

Gang Wang et al.

Summary: This study proposes a two-stage method for detection and counting of brine shrimp, combining a target marker proposal network with a target classification network. Experimental results confirm that the proposed method can accurately detect and count brine shrimp objects that are highly adjacent in images.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Engineering, Chemical

Evaluation of quality changes in big-eye tuna (Thunnus obesus) based on near-infrared reflectance spectroscopy (NIRS) and low field nuclear magnetic resonance (LF-NMR)

Weiqing Lan et al.

Summary: The study investigated the effect of temperature fluctuations on the quality of big-eye tuna through simulation of logistical processes. Results showed that WHC dropped significantly in the L2 group and protein degradation accelerated with temperature increase. NIRS and LF-NMR were effective in reflecting quality changes, with changes in absorbance value and water migration observed. The study provided a theoretical foundation for the application of NIRS and LF-NMR in aquatic products.

JOURNAL OF FOOD PROCESS ENGINEERING (2021)

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Article Computer Science, Artificial Intelligence