The application of computer technologies associated with sensors and artificial intelligence (AI) in the quantification and qualification of quality parameters of meat products of various domestic species is an area of research, development, and innovation of great relevance in the agri-food industry. This review covers the most recent advances in this area, highlighting the importance of computer vision, artificial intelligence, and ultrasonography in evaluating quality and efficiency in meat products' production and monitoring processes. Various techniques and methodologies used to evaluate quality parameters such as colour, water holding capacity (WHC), pH, moisture, texture, and intramuscular fat, among others related to animal origin, breed and handling, are discussed. In addition, the benefits and practical applications of the technology in the meat industry are examined, such as the automation of inspection processes, accurate product classification, traceability, and food safety. While the potential of artificial intelligence associated with sensor development in the meat industry is promising, it is crucial to recognise that this is an evolving field. This technology offers innovative solutions that enable efficient, cost-effective, and consumer-oriented production. However, it also underlines the urgent need for further research and development of new techniques and tools such as artificial intelligence algorithms, the development of more sensitive and accurate multispectral sensors, advances in computer vision for 3D image analysis and automated detection, and the integration of advanced ultrasonography with other technologies. Also crucial is the development of autonomous robotic systems for the automation of inspection processes, the implementation of real-time monitoring systems for traceability and food safety, and the creation of intuitive interfaces for human-machine interaction. In addition, the automation of sensory analysis and the optimisation of sustainability and energy efficiency are key areas that require immediate attention to address the current challenges in this agri-food and agri-industrial sector, highlighting and emphasising the importance of ongoing innovation in the field.

Livestock production in the basins of the northern macro-region of Peru has as its primary source pastures of Lolium multiflorum L. ‘Cajamarquino ecotype’ (ryegrass CE) in monoculture, or in association with white clover Ladino variety, for feeding. The objective of this research work was the morphological characterisation, yield evaluation, and cutting time evaluation of two local genotypes (LM-58 and LM-43) of Lolium multiflorum L. in six locations. An ANOVA was performed to compare fixed effects and interaction. It was determined that the LM-58 genotype is intermediate, growing semi-erect, with a dark green colouring and 0.8 cm broadleaf, and can reach an average stem length of 46 cm, up to 1.6 cm. day⁻¹, achieving fourth-leaf growth at 28 days under appropriate management conditions. Despite the differentiated characteristics, according to BLASTn evaluation, the ITS1 sequences showed a greater than 99.9% similar identification to Lolium multiflorum L., characterising it as such. It was determined that the LM-58 genotype outperforms LM-43, achieving a forage yield of 4.49 Mg. ha⁻¹, a seed production of 259.23 kg. ha⁻¹, and an average of 13.48% crude protein (CP). The best biomass yield (49.10 Mg. ha⁻¹.yr⁻¹) is reached at 60 days; however, at 30 days, there is a high level of CP (14.84%) and there are no differences in the annual protein production at the cutting age of 60 and 45 days. With the results of the present study, LM-58 from a selection and crossbreeding of 680 ryegrass EC accessions emerges as an elite genotype adapted to the conditions of the northern high Andean zone of Peru.

Background Evaluation of forage resources is vital for the sustainability of livestock farming in the South American Andes, especially under conditions of low water availability for irrigation and acid soils. Methods We evaluated the productivity and nutritive value of two cultivars of chicory (Cichorium intybus L.) and one of plantain (Plantago lanceolata L.) in three high-altitude sites (AL) of the northern highlands of Peru: AL-I: 2300–2800 m.a.s.l, AL-II: 2801–3300 m.a.s.l. and AL-III: 3301–3800 m.a.s.l., for 1 year. The parameters evaluated were dry matter yield (DMY), plant height (PH), growth rate (GR) and nutritional value. Results Plantain achieved the greatest annual DMY (ADMY), PH and GR compared to the two chicory cultivars (9.34, 9.56 and 13.39 Mg ha−1 for Puna II and Sese 100 chicory and Tonic plantain, respectively; p = 0.0019). The greatest ADMY and GR occurred at AL-I. Regarding nutritional value, differences were observed only for in vitro digestibility of dry matter and metabolisable energy with chicory cultivars higher than plantain. Conclusions The results indicate that the three cultivars evaluated may be used as a nutritional supplement in cattle feed, associated with grasses because they have high nutritive value suitable for milk production in the mountain regions of Peru.

Livestock production in the Cajamarca, La Libertad and Amazonas basins is based on pasture-based feeding with "Cajamarquino ecotype" ryegrass under monoculture or in association with white clover. The objective of this research work was the morphological characterization and evaluation of the productive yield and cutting time of annual ryegrass - Lolium multiflorum L. Six local genotypes of Lolium multiflorum in six locations were characterised, using the multiplicative interaction effect model and additive main effects for the analysis of interaction and variability of the genotypes and locations. Ryegrass “Cajamarquino ecotype” is semi-erect with intermediate growth, with a dark green colouring, 0.8 cm broadleaf, and can reach an average stem length of 46 cm, up to 1.6 cm.day, achieving the growth of the fourth leaf after 28 days under adequate management conditions. Despite the differentiated characteristics, according to the BLASTn evaluation, the ITS1 sequences showed an identification greater than 99.9% similar to Lolium multiflorum L. It was determined that the Cajamarquino ecotype produces from 3.52 to 4.98 Mg.ha.biomass cutting. Likewise, the pasture's quality is better when used at 30 days with 14.84% protein and at 45 days, it achieves 12.75% protein with a biomass of 4.05 Mg.ha.cut. With these morphological and yield characteristics, the "Cajamarca ecotype" ryegrass is a well-adapted species for local livestock farming. These species are adapted to the Sierra Norte area of Peru.

Sustainable Kikuyu (Pennisetum clandestinum) production in the Peruvian highlands was evaluated through productivity, growth, and chemical composition. This study assessed the effects of nitrogen (N) rate, organic matter application, and cutting frequency on Kikuyu grass’s yield, chemical composition, plant height, and growth rate. The experiment followed a randomised block design with split plots. A multivariate analysis of variance (MANOVA) assessed the differences across study factors. Applying 120 kg of N ha⁻¹ yr⁻¹ raised the protein yield to 3454.53 kg ha⁻¹, with a crude protein (CP) content of 23.54%. Moreover, fencing with cypress (Cupressus lusitanica) trees influenced the Kikuyu biomass, producing 19,176.23 kg of dry matter (DM) ha⁻¹ yr⁻¹ at 8.5–11.5 m from the tree base. Organic matter enhanced the Kikuyu aboveground biomass. While dry matter production showed no significant difference between 30- and 60-day cutting intervals, CP content was higher at 30 days (p < 0.05). Peak daily dry matter (DM) production occurred at 45 days, achieving a biomass accumulation of 21,186.9 kg of DM ha⁻¹ yr⁻¹. Given its high yield and favourable chemical composition, Kikuyu is a viable option for dairy cattle feed, especially in highland areas. Implementing a plant improvement programme for Kikuyu could further enhance its nutritional value for high-production dairy cows.

The productive sustainability of Pennisetum clandestinum in the Peruvian highlands was evaluated through productivity, growth and chemical composition. The effect of the nitrogen (N2) dose applied to the soil, the use of organic matter and the frequency of cutting or phenological age on the productive yields, chemical composition, plant height and growth rate of Kikuyu were determined. Experimentation was carried out under a randomised block design in divided plots. A multivariate analysis of variance (MANOVA) was used to determine the associated differences in each study factor. It was determined that applying 120 kg of N2 increases the annual protein production to 3 454.53 kg ha-1. yr-1, and a crude protein (CP) level of 23.54%, the distance of the live fences influences the biomass production to 19 176.23 kg DM ha-1 at an interval of 8.5 to 11.5 meters from the base of the cypress tree (Cupressus lusitanica). Organic matter favours the biomass yield of Kikuyu. Although there is no difference in dry matter production between 30 and 60 days of cutting, CP production is higher at 30 (p<0.05). The highest DM production per day is obtained at 45 days, generating a higher biomass accumulation of 21 186.9 kg DM ha-1. yr-1. The consideration of Pennisetum clandestinum for dairy cattle is viable, taking into account that the possibility of implementing a plant improvement programme on this species is open, aimed at increasing the composition of the diet in high-production cows due to its high yield and good chemical composition in highland conditions.