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12 pages, 938 KiB

Open AccessArticle

Aflatoxin M1 Content and Mastitis-Causing Bacteria in Milk from Skopelos Dairy Goats Reared in Extensive and Intensive Farming Systems

by Ioannis Stavropoulos, Zoitsa Basdagianni, Georgios Manessis, Aikaterini Tsiftsi and Ioannis Bossis

Animals 2025, 15(9), 1238; https://doi.org/10.3390/ani15091238 - 28 Apr 2025

Viewed by 317

Abstract

This study assessed the impact of farming systems on aflatoxin M1 (AFM1) content and the prevalence of mastitis-causing bacteria in goat milk. A total of 233 milk samples were collected from two Skopelos goat farms—one intensive and one extensive farm—and analyzed for AFM1 [...] Read more.

This study assessed the impact of farming systems on aflatoxin M1 (AFM1) content and the prevalence of mastitis-causing bacteria in goat milk. A total of 233 milk samples were collected from two Skopelos goat farms—one intensive and one extensive farm—and analyzed for AFM1 content using a competitive ELISA. An additional 219 samples from goats suspected of subclinical mastitis were tested for bacterial prevalence with microbial culturing. The results showed that AFM1 concentration was significantly higher in the intensive farming system (7.76 ± 0.76 ng/kg) than in the extensive farming system (3.78 ± 0.79 ng/kg), though it remained below the legal limit of 50 ng/kg. The main effects of season and year were not significant, though higher levels of AFM1 were observed during winter. The interaction effects of season–farming system and year–season–farming system on AFM1 levels were significant. The prevalence of mastitis-causing bacteria varied by system, with Streptococcus spp. being more common in the extensive farming system, and Staphylococcus aureus was more frequently detected in milk samples from the intensive farming system. Binomial regression indicated that both the farming system and lactation stage significantly influenced Streptococcus spp. prevalence (p = 0.05; OR = 1.9 and 2.7, respectively). It is concluded that the farming system affects those quality parameters in goat milk. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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11 pages, 1538 KiB

Open AccessArticle

Evaluation of Rumen-Protected Methionine Supplementation on Milk Production and Composition in Crossbred Dairy Sheep

by Juan Carlos Angeles-Hernandez, Josué Vicente Cervantes-Bazán, Rodolfo Vieyra-Alberto, Angelica Valeria Lorenzana-Moreno, Ángel Garduño-García and Augusto César Lizarazo-Chaparro

Animals 2025, 15(7), 960; https://doi.org/10.3390/ani15070960 - 27 Mar 2025

Viewed by 376

Abstract

In dairy sheep, optimum nutrition is required to maintain a positive energy and nitrogen balance, and therefore, achieve adequate performance levels. In this sense, supplemental rumen-protected methionine (RPMet) has been a nutritional strategy used to improve the availability of amino acids in sheep [...] Read more.

In dairy sheep, optimum nutrition is required to maintain a positive energy and nitrogen balance, and therefore, achieve adequate performance levels. In this sense, supplemental rumen-protected methionine (RPMet) has been a nutritional strategy used to improve the availability of amino acids in sheep for milk production. The aim of the current study is to assess the effect of RPMet supplementation on the milk yield and milk composition of crossbred dairy sheep. Twenty F1 sheep (50% Pelibuey × 50% East Friesian) were randomly assigned to one of the following three treatments: C (control: 0 g/d), 3 g (3.0 g/d), or 6 g (6 g/d) of RPMet added to the basal diet from day 2 to 120 after lambing. Milk yield was significantly higher in sheep supplemented with 6 g of RPMet (p = 0.04) with a linear effect (p < 0.001). In relation to protein yield, the 6 g treatment showed the highest values (55.5 g/day) in comparison with the control (35.2 g/day) and 3 g (42.3 g/day) treatments. Also, lactose (p = 0.02) and non-fat solid yield (p = 0.03) were positively affected by the methionine supplementation. Our results suggest that methionine supplementation is an option to increase milk production, likely associated with the better availability of nutrients of dairy sheep farms using crossbred sheep in regions with an incipient dairy sheep industry. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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10 pages, 272 KiB

Open AccessArticle

Effects of Parity and Somatic Cell Count Threshold on Udder Morphology, Milkability Traits, and Milk Quality in Canarian Goats

by Mario Salomone-Caballero, María Fresno, Sergio Álvarez and Alexandr Torres

Animals 2024, 14(9), 1262; https://doi.org/10.3390/ani14091262 - 23 Apr 2024

Cited by 1 | Viewed by 1378

Abstract

The effects of parity and somatic cell count in milk (SCC) threshold on the udder morphology, milkability traits, and milk composition was evaluated in 41 Canarian goats in mid-lactation. The animals were divided according to parity (1st, 2nd, and 3rd), and a SCC [...] Read more.

The effects of parity and somatic cell count in milk (SCC) threshold on the udder morphology, milkability traits, and milk composition was evaluated in 41 Canarian goats in mid-lactation. The animals were divided according to parity (1st, 2nd, and 3rd), and a SCC threshold of 2000 × 10³ cells/mL in milk was set to evaluate the effect of this factor on the different measured parameters. Results showed that primiparous goats had the udder smaller and less distended than multiparous goats, but no differences were detected on milk flow parameters. Furthermore, SCC and total bacterial count (TBC) tended to be higher when the parity increased. On the other hand, goats with SCC ≤ 2000 × 10³ had higher cistern-floor distance (CF) and lower TBC values compared with those goats with a count above the predetermined threshold. The results suggest that a reduction in SCC can be achieved by a selection of udder morphological traits. Moreover, milk flow parameters do not seem to be a tool to determine the udder health status in Canarian goats, but long-term studies are needed to verify it. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

13 pages, 970 KiB

Open AccessArticle

Exploring Breed-Specific Milk Coagulation in Spanish Dairy Sheep: A Canonical Correlation Approach

by Javier Caballero-Villalobos, Ana Garzón, Elena Angón, Ramón Arias, Alessio Cecchinato, Nicolò Amalfitano and José M. Perea

Animals 2024, 14(6), 900; https://doi.org/10.3390/ani14060900 - 14 Mar 2024

Cited by 1 | Viewed by 1460

Abstract

The transformation of milk into cheese largely depends on the technological properties of the raw material, with breed being a crucial factor that influences both the composition and coagulation properties of the milk used for cheesemaking. This study uses canonical correlation analysis to [...] Read more.

The transformation of milk into cheese largely depends on the technological properties of the raw material, with breed being a crucial factor that influences both the composition and coagulation properties of the milk used for cheesemaking. This study uses canonical correlation analysis to explore the relationships between physicochemical traits and coagulation properties in milk from various Spanish breeds, aiming to identify both common and breed-specific patterns that impact milk technological aptitude. A total of 832 milk samples from Manchega, Assaf, Merino de Grazalema, and Merino de Los Pedroches breeds were analyzed. The milk characteristics investigated included pH, composition (fat, protein, lactose, total solids), and coagulation properties (curd firmness—A₆₀, rennet clotting time—RCT, curd firming time—k₂₀, and individual laboratory curd yield—ILCY). The results reveal a shared correlation structure across breeds and unique covariation patterns in some breeds that deviate from the general trend. While Assaf and Merino de Los Pedroches follow the common correlation pattern, Manchega and Merino de Grazalema exhibit distinct patterns. This research underscores the need for in-depth study and suggests that the dairy industry could benefit from shifting from the traditional focus on maximizing fat and protein for higher curd yields to considering technological traits for selective breeding. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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13 pages, 1004 KiB

Open AccessArticle

Effect of Acute and Cumulative Stress on Gene Expression in Mammary Tissue and Their Interactions with Physiological Responses and Milk Yield in Saanen Goats

by Marta Liliane de Vasconcelos, Priscila dos Santos Silva, Henrique Barbosa Hooper, Giovana Krempel Fonseca Merighe, Sandra Aparecida de Oliveira and João Alberto Negrão

Animals 2023, 13(23), 3740; https://doi.org/10.3390/ani13233740 - 3 Dec 2023

Viewed by 2219

Abstract

This study addresses the hypothesis that different acute stressors can cumulatively decrease milk yield. In fact, in a time of global warming, the impact of environmental stress and farm management practices on milk production remains unclear. In this context, our objective was to [...] Read more.

This study addresses the hypothesis that different acute stressors can cumulatively decrease milk yield. In fact, in a time of global warming, the impact of environmental stress and farm management practices on milk production remains unclear. In this context, our objective was to investigate the effect of acute and cumulative stress on gene expression in mammary tissue and their interactions with physiological responses and milk yield in Saanen goats. Thirty lactating goats were subjected to two treatments: (1) control (CT), in which goats were maintained following a habitual routine under comfort conditions; (2) stress (ST), in which the goats were subjected to different types of environmental stress: heat stress, adrenocorticotropic hormone administration, hoof care management, and exposure to rain. These stressors were performed sequentially, with one stress per day on four consecutive lactation days, to evaluate their effect on milk quality and milk yield. Our results showed that compared to CT goats, cumulative stress increased the gene expression of glucocorticoid receptor (GR), interferon-gamma (IFN-γ), superoxide dismutase (SOD), and catalase (CAT) in mammary tissue, which are indicators of cortisol action, inflammatory response, and antioxidant enzymes. Furthermore, the acute challenges imposed on ST goats changed their rectal temperature and respiratory frequency and increased cortisol, glucose, cholesterol, triglycerides, and high-density lipoprotein release in plasma when compared to CT goats. Although these physiological and metabolic responses restore homeostasis, ST goats showed lower milk yield and higher somatic cell count in milk than CT goats. In conclusion, the results confirmed our initial hypothesis that different acute stressors cumulatively decrease the milk yield in Saanen goats. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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19 pages, 3970 KiB

Open AccessArticle

Variations in Composition, Antioxidant Profile, and Physical Traits of Goat Milk within the Semi-Intensive Production System in Mountainous Areas during the Post-Weaning to End-of-Lactation Period

by Eleni Kasapidou, Iraklis-Vasileios Iliadis, Paraskevi Mitlianga, Georgios Papatzimos, Maria-Anastasia Karatzia, Vasileios Papadopoulos, Michail Amanatidis, Vasiliki Tortoka, Ekaterini Tsiftsi, Antonia Aggou and Zoitsa Basdagianni

Animals 2023, 13(22), 3505; https://doi.org/10.3390/ani13223505 - 13 Nov 2023

Cited by 3 | Viewed by 1694

Abstract

Dairy products from mountain-origin milk are known for their superior composition and quality. This study aimed to examine changes in composition, nutritional quality, and antioxidant properties of milk from semi-intensively managed goats in mountainous regions during the post-weaning to end-of-lactation period. Bulk tank [...] Read more.

Dairy products from mountain-origin milk are known for their superior composition and quality. This study aimed to examine changes in composition, nutritional quality, and antioxidant properties of milk from semi-intensively managed goats in mountainous regions during the post-weaning to end-of-lactation period. Bulk tank milk samples from 10 farms were collected bi-weekly in the period from March to September. The farms were situated in regions with an average altitude of 772.20 m above sea level. The results revealed significant variations in milk composition, with fluctuations in fat, protein, lactose, and total solids. Milk yield per doe showed seasonal differences, with the highest yield in April and the lowest in September. Fatty acid composition exhibited changes throughout the sampling period, with variations in polyunsaturated fatty acids. Nutritional indices, such as the atherogenicity index and thrombogenicity index, remained within the recommended values. Antioxidant properties, including total phenolic content, DPPH, FRAP, and ABTS, showed significant differences, with higher values toward the end of the study. Milk pH, electrical conductivity, brix value, and refractive index also exhibited variations, while density and freezing point remained relatively stable. The study provided valuable information that can be used to develop breeding and feeding plans to achieve uniform milk quality in mountainous regions. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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11 pages, 1084 KiB

Open AccessArticle

Application of Machine Learning Algorithms to Describe the Characteristics of Dairy Sheep Lactation Curves

by Lilian Guevara, Félix Castro-Espinoza, Alberto Magno Fernandes, Mohammed Benaouda, Alfonso Longinos Muñoz-Benítez, Oscar Enrique del Razo-Rodríguez, Armando Peláez-Acero and Juan Carlos Angeles-Hernandez

Animals 2023, 13(17), 2772; https://doi.org/10.3390/ani13172772 - 31 Aug 2023

Cited by 3 | Viewed by 1940

Abstract

In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting and modeling complex data. Therefore, the aim of this study was to evaluate the prediction ability of different ML algorithms and a traditional empirical model to estimate the parameters [...] Read more.

In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting and modeling complex data. Therefore, the aim of this study was to evaluate the prediction ability of different ML algorithms and a traditional empirical model to estimate the parameters of lactation curves. A total of 1186 monthly records from 156 sheep lactations were used. The model development process involved training and testing models using ML algorithms. In addition to these algorithms, lactation curves were also fitted using the Wood model. The goodness of fit was assessed using correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and relative root mean square error (RRSE). SMOreg was the algorithm with the best estimates of the characteristics of the sheep lactation curve, with higher values of r compared to the Wood model (0.96 vs. 0.68) for the total milk yield. The results of the current study showed that ML algorithms are able to adequately predict the characteristics of the lactation curve, using a relatively small number of input data. Some ML algorithms provide an interpretable architecture, which is useful for decision-making at the farm level to maximize the use of available information. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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15 pages, 750 KiB

Open AccessArticle

Preliminary Feasibility of Near-Infrared Spectroscopy to Authenticate Grazing in Dairy Goats through Milk and Faeces Analysis

by Pablo Rodríguez-Hernández, Cipriano Díaz-Gaona, Carolina Reyes-Palomo, Santos Sanz-Fernández, Manuel Sánchez-Rodríguez, Vicente Rodríguez-Estévez and Nieves Núñez-Sánchez

Animals 2023, 13(15), 2440; https://doi.org/10.3390/ani13152440 - 28 Jul 2023

Cited by 1 | Viewed by 1358

Abstract

Consumers are increasingly prone to request information about the production systems of the food they buy. For this purpose, certification and authentication methodologies are necessary not only to protect the choices of consumers, but also to protect producers and production systems. The objective [...] Read more.

Consumers are increasingly prone to request information about the production systems of the food they buy. For this purpose, certification and authentication methodologies are necessary not only to protect the choices of consumers, but also to protect producers and production systems. The objective of this preliminary work was to authenticate the grazing system of dairy goats using Near-Infrared Spectroscopy (NIRS) analyses of milk and faeces of the animals. Spectral information and several mathematical pre-treatments were used for the development of six discriminant models based on different algorithms for milk and faeces samples. Results showed that the NIRS spectra of both types of samples had some differences when the two feeding regimes were compared. Therefore, good discrimination rates were obtained with both strategies (faeces and milk samples), with classification percentages of up to 100% effectiveness. Discrimination of feeding regime and grazing authentication based on NIRS analysis of milk samples and an alternative sample such as faeces is considered as a potential approach for dairy goats and small ruminant production. Full article

(This article belongs to the Special Issue Lactation Physiology and Milk Quality of Small Ruminants)

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