The tail tendons of skipjack tuna (Katsuwonus pelamis), a by-product from the meat-separation process in canned-tuna production, was used as an alternative source of collagen extraction. The acid-solubilized collagens using vinegar (VTC) and acetic-acid (ATC) extraction and pepsin-solubilized collagen (APTC) were extracted from tuna-tail tendon. The physiochemical properties and characteristics of those collagens were investigated. The obtained yield of VTC, ATC, and APTC were 7.88 ± 0.41, 8.67 ± 0.35, and 12.04 ± 0.07%, respectively. The determination of protein-collagen solubility, the effect of pH and NaCl on collagen solubility, Fourier-transform infrared spectroscopy (FTIR) spectrum, and microstructure of the collagen-fibril surface using a scanning electron microscope (SEM) were done. The protein solubility of VTC, ATC, and APTC were 0.44 ± 0.03, 0.52 ± 0.07, and 0.67 ± 0.12 mg protein/mg collagen. The solubility of collagen decreased with increasing of NaCl content. These three collagens were good solubility at low pH with the highest solubility at pH 5. The FTIR spectrum showed absorbance of Amide A, Amide B, Amide I, Amide II, and Amide III groups as 3286–3293 cm⁻¹, 2853–2922 cm⁻¹, 1634–1646 cm⁻¹, 1543–1544 cm⁻¹, and 1236–1237 cm⁻¹, respectively. The SEM analysis indicated a microstructure of collagen surface as folding of fibril with small pore.

This study investigated the immunonutritional potential of high-molecular-weight (Mw~85 kDa), non-degraded chitosan (NCS) and gamma-radiation-degraded, low-molecular-weight chitosan (RCS) incorporated into aquafeeds for Nile tilapia (Oreochromis niloticus). RCS was produced by γ-irradiation (10 kGy) in the presence of 0.25% (w/v) H₂O₂, yielding low-viscosity, colloidally stable nanoparticles with Mw ranging from 10 to 13 kDa. Five diets were formulated: a control, NCS at 0.50%, and RCS at 0.025%, 0.050%, and 0.075%. No adverse effects on growth were observed, confirming safety. Immune gene expression (e.g., ifng1, nfκb, tnf), antioxidant markers (e.g., reduced MDA, increased GSH and GR), and nonspecific humoral responses (lysozyme, IgM, and bactericidal activity) were significantly enhanced in the NCS-0.50, RCS-0.050, and RCS-0.075 groups. Notably, these benefits were achieved with RCS at 10-fold lower concentrations than NCS. Following challenge with Edwardsiella tarda, fish fed RCS-0.050 and RCS-0.075 diets exhibited the highest survival rates and relative percent survival, highlighting robust activation of innate and adaptive immunity alongside redox defense. These results support the use of low-Mw RCS as a biologically potent, cost-effective alternative to traditional high-Mw chitosan in functional aquafeeds. RCS-0.050 and RCS-0.075 show strong potential as immunonutritional agents to enhance fish health and disease resistance in aquaculture.

Color grading of boiled shrimp is a critical factor influencing market price, yet the process is usually conducted visually by buyers such as middlemen and processing plants. This subjective practice raises concerns about accuracy, impartiality, and fairness, often resulting in disputes with farmers. To address this issue, this study proposes a standardized and automated grading approach based on image processing and artificial intelligence. The method requires only a photograph of boiled shrimp placed alongside a color grading ruler. The grading process involves two stages: segmentation of shrimp and ruler regions in the image, followed by color comparison. For segmentation, deep learning models based on Mask R-CNN with a Feature Pyramid Network backbone were employed. Four model configurations were tested, using ResNet and ResNeXt backbones with and without a Boundary Loss function. Results show that the ResNet + Boundary Loss model achieved the highest segmentation performance, with IoU scores of 91.2% for shrimp and 87.8% for the color ruler. In the grading step, color similarity was evaluated in the CIELAB color space by computing Euclidean distances in the L (lightness) and a (red–green) channels, which align closely with human perception of shrimp coloration. The system achieved grading accuracy comparable to human experts, with a mean absolute error of 1.2, demonstrating its potential to provide consistent, objective, and transparent shrimp quality assessment.