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Cortisol is the primary biomarker associated with the hypothalamic–pituitary–adrenal (HPA) axis. This research aimed at assessing the predictive potential and the relationship of cortisol concentrations in four media (blood, milk, whey and hair) with parity, lactation stage and productive classes. Multiparous (n = 30) and primiparous (n = 38) Italian Mediterranean buffaloes were used and assigned to four productive classes (based on percentiles of mature equivalent milk yield (EMY) and mature equivalent energy corrected milk (eECM)), and cortisol concentrations were measured using a in house radioimmunoassay (RIA) method. Parity did not show a significant effect on cortisol concentrations of the four media. The catabolic stage of lactation (up to 90 d in milk (DIM)) was characterised by higher cortisol concentrations compared to the second anabolic stage (beyond 150 DIM) in milk formulations. The plasmatic concentrations of cortisol were higher at the catabolic and the first anabolic stage (91–150 DIM) compared to the second anabolic (p = 0.022 and p = 0.009, respectively). Buffaloes beyond 150 DIM differed from those below 90 DIM (p < 0.001) and between 91 and 150 DIM (p < 0.05) in hair. Finally, hair cortisol concentrations were negatively correlated to EMY, mature equivalent protein content (EPC) (p < 0.01) and eECM (p < 0.05). The whey showed a potential to predict the concentrations of cortisol in whole extracted milk (R2 = 0.31). Hence the development of a real-time automated cortisol measurement in milk could be a valuable tool in Italian Mediterranean Buffalo farming. HIGHLIGHTS: The lactation stage significantly influences plasma, hair and milk cortisol concentrations. Hair cortisol concentrations are negatively correlated to milk quality parameters. The whey is a potential predictor of the cortisol concentrations in whole extracted milk. [ABSTRACT FROM AUTHOR]

Abstract Recently, much interest has been raised for the characterization of signaling molecules carried by extracellular vesicles (EVs), which are particularly enriched in milk (mEVs). Such interest is linked to the capability of EVs to cross biological barriers, resist acidification in the gastric environment, and exert modulation of the immune system, mainly through their microRNA (miRNA) content. We characterized the small-RNA cargo of colostrum EVs (colosEVs) and mEVs from Italian Mediterranean buffalo through next generation sequencing. Colostrum (first milking after birth) and milk (day 50 of lactation) were sampled from seven subjects from five farms. ColosEVs and mEVs were subjected to morphological characterization, followed by high-depth sequencing of small RNA libraries produced from total RNA. The main difference was the amount of EV in the two samples, with colostrum showing 10 to 100-fold higher content than milk. For both matrices, miRNA was the most abundant RNA species (95% for colosEVs and 96% for mEVs) and three lists were identified: colosEV-specific, mEV-specific and shared most expressed. Gene ontology (GO) enrichment analysis on miRNA targets highlighted many terms related to the epigenetic, transcriptional and translational regulations across the three lists, with a higher number of enriched terms for colosEV-specific miRNAs. Terms specific to colosEVs were related to “cell differentiation” and “microvillus assembly”, while for mEV “cardiac and blood vessel development” and “mitochondria” emergerd. Immune modulation terms were found for both sample-specific miRNAs. Overall, both matrices carry a similar molecular message in terms of biological processes potentially modulated into receiving cells, but there is significant difference in the abundance, with colostrum containing much more EVs than milk. Moreover, colosEVs carry molecules involved in signal transduction, cell cycle and immune response, as for mEVs and EVs of other previously characterized species, but with a special enrichment for miRNAs with epigenetic regulation capacities. These beneficial characteristics of colosEVs and mEVs are essential for the calf and could also be exploited for the therapeutic purposes in humans, although further studies are necessary to measure the sanitization treatment impact on EV conservation, especially in buffalo where milk is consumed almost exclusively after processing.

Recently, much interest has been raised for the characterization of signaling molecules carried by extracellular vesicles (EVs), which are particularly enriched in milk (mEVs). Such interest is linked to the capability of EVs to cross biological barriers, resist acidification in the gastric environment, and exert modulation of the immune system, mainly through their microRNA (miRNA) content. We characterized the small-RNA cargo of colostrum EVs (colosEVs) and mEVs from Italian Mediterranean buffalo through next generation sequencing. Colostrum (first milking after birth) and milk (day 50 of lactation) were sampled from seven subjects from five farms. ColosEVs and mEVs were subjected to morphological characterization, followed by high-depth sequencing of small RNA libraries produced from total RNA. The main difference was the amount of EV in the two samples, with colostrum showing 10 to 100-fold higher content than milk. For both matrices, miRNA was the most abundant RNA species (95% for colosEVs and 96% for mEVs) and three lists were identified: colosEV-specific, mEV-specific and shared most expressed. Gene ontology (GO) enrichment analysis on miRNA targets highlighted many terms related to the epigenetic, transcriptional and translational regulations across the three lists, with a higher number of enriched terms for colosEV-specific miRNAs. Terms specific to colosEVs were related to "cell differentiation" and "microvillus assembly", while for mEV "cardiac and blood vessel development" and "mitochondria" emergerd. Immune modulation terms were found for both sample-specific miRNAs. Overall, both matrices carry a similar molecular message in terms of biological processes potentially modulated into receiving cells, but there is significant difference in the abundance, with colostrum containing much more EVs than milk. Moreover, colosEVs carry molecules involved in signal transduction, cell cycle and immune response, as for mEVs and EVs of other previously characterized species, but with a special enrichment for miRNAs with epigenetic regulation capacities. These beneficial characteristics of colosEVs and mEVs are essential for the calf and could also be exploited for the therapeutic purposes in humans, although further studies are necessary to measure the sanitization treatment impact on EV conservation, especially in buffalo where milk is consumed almost exclusively after processing. [ABSTRACT FROM AUTHOR]

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Single-step genomic best linear unbiased predictor (ssGBLUP) is a method for jointly estimating breeding values (BV) for genotyped and non-genotyped animals. Genomic information in the Italian Mediterranean Buffalo (IMB) is now available and its inclusion in the genetic evaluation system could increase both accuracy and genetic progress of the traits of interest of the breed. The aim of this study was to test the feasibility of ssGBLUP and to present the first results of the implementation of a genomic evaluation for production and type traits in the IMB. Phenotypic information on production (270-day milk, mozzarella yield (MY), protein and fat kg and %, respectively) and morphology: feet and legs (FL) and mammary system (MS) were used for this study. Production records included 743,904 lactations from 276,451 buffalo cows born from 1984 to 2019. Morphological traits were from 91,966 buffalo cows from 2004 to 2022. Regarding the genotypes, a total of 2,017 buffalo cows and 133 bulls were used. Data were analysed fitting two multitrait animal models, a 6-trait model for production data and a 2-trait model for morphology data. According to the relationship matrix used, two models were fitted: (i) the BLUP with the numerator relationship matrix (A); (ii) the ssGBLUP where A and the genomic relationship matrix (G) are blended into H. BV were estimated with BLUP and ssGBLUP models. Three different scenarios were used, according to the cut-off year used to create the partial datasets, namely 2012, 2015 and 2017. In each scenario, correlation, accuracy, dispersion, and bias statistics were calculated (LR method). Both bulls (N=49) and cows (N=1288) were used for validations. On average, correlation between EBVs from partial and whole datasets estimated with BLUP and ssGBLUP increased from 6 to 49% and from 14 to 17% for production and type traits, respectively. Among the traits analysed, the ones most affected by the change were protein/fat content, MY, and AM. The accuracy increase for these traits was above 20% when using the ssGBLUP. All LR statistics improved also for non-genotyped females. These results showed that implementing ssGBLUP in the breeding program can generate more accurate predictions for important traits in dairy IMB than traditional BLUP.

The Italian Mediterranean Buffalo is the most important buffalo’s breeds for milk production and its derivatives, which has a selection program implemented more than 20 years ago. The selection is based on an aggregate index that includes dairy, mozzarella yield, and functional traits. The improvement of udder conformation (UC) traits is an aspect that plays an essential role in udder health and longevity; it is of great interest due to its direct relationship with economic losses caused by mastitis or poor milkability. The aim of this study was the development of an aggregate selection index (ASI) considering MP (milk production), MSCS150 (geometric mean of somatic cell score at 150 days in milk), and UC traits (fore udder attachment– FUA; rear udder width– RUW; rear legs height– RLH; teat direction – TD; teat length – TL and teat position – TP). The first step was to estimate the genetic (co)variances between the UC, MP, and MSCS150 traits and to estimate the relative weight for each UC trait. The phenotypic records of 15,275 females and a pedigree with 43,395 animals were used. A multitrait animal model that included CG (herd-year-calving season), calving month, and parity as fixed effects, and the animal as a random effect was used. The estimated heritability for MP and MSCS150 were 0.391 and 0.134, respectively, and varied between 0.11 and 0.23 for UC traits. Low negative genetic correlations were observed between MP and RLH (−0.119), the same pattern between MSCS150 and RLH (−0.350) and MSCS150 and FUA (−0.220). A positive correlation was found between FUA and MP (0.4272) and MP and RUW (0.645). Using ASI as selection criteria, an annual reduction of −0.03 is expected for MSCS150 and an increase of 0.26 kg for MP. During a selection period of ten years, the expected cumulative genetic gains would be -0.32 for MSCS150 and an increase of MP in 2.57 kg. Selective breeding programs aim to improve specific traits over time by selecting individuals with desirable genetic characteristics as parents of the next generation. According to the results, by focusing on RUW, RLH, and TD traits, genetic improvements are expected to lead to reduced severity of MSCS150 while maintaining or increasing milk production.

In buffalo breeding, calves require special attention and housing systems that provide thermal comfort, good air quality, brightness, and adequate space. Overcrowding, poor ventilation, high temperatures, or improper management of animals can result in increased concentrations of environmental gases such as ammonia (NH3), carbon dioxide (CO 2 ), and hydrogen sulfide (H2 S), altered microclimate parameters, and worsened air quality. The increase in these gases can be problematic for the environment and the calves, whose stress levels can increase and adversely affect the buffalo calves´ nutrition, health, and physiological parameters. During the late spring and early summer season, gas monitoring was carried out in 7 buffalo calf housing spaces in the Campania region, and special measuring instruments were used to measure CO 2 (Portable indoor air quality CO2 meter, Extech instruments), H 2 S and NH3 (Pro gas badge, Industrial scientific) produced by calves. The recording of perceived data was performed continuously and over 15 minutes. Measurements were taken early in the morning before the morning milk feed, and the instruments were positioned at the height of the calves. The calves analysed are all housed in completely closed structures equipped with doors and windows, usually left open in the summer, and closed in the winter. Furthermore, the age range of the animals housed ranges from 0 to 90 days of life, during which the calf mainly takes on reconstituted milk and then is sent towards weaning in the last few weeks. The m 2 available per calf varies on each farm, and all the calves are housed individually. On average, the available space is approximately 100 cm x 1.40 cm. In all structures, the litter used is straw, mandatory for the first two weeks of the calf’s life. In addition, the “Health score” of 300 calves was also evaluated. Score 0 indicated no cough; normal serous discharge or a small amount of unilateral turbid discharge; normal eyes or a small amount of ocular discharge; normal ear, flick ear, or head shake; normal or semi-formed feces; forelimbs entirely covered by bedding when calf lying down. Score 1 indicates coughs on movement; bilateral, excessive, or mucopurulent mucus discharge; moderate or heavy ocular discharge; head tilt or unilateral/bilateral droop; loose or watery feces sifts through the bedding; partially visible or visible forelimbs when the calf is lying down. Each parameter has its score and is considered independent of the other. Finally, as regards the state of cleanliness of the litter, rather than in the calf score, the state of cleanliness of the litters was considered in the data collection regarding the management of the calf house, expressing a judgment such as: “The litter is: kept in good condition; fairly well kept; it is not kept in good condition”. The data collected show that in all calf housing spaces, the estimated NH3 concentrations were in the range of 0 ppm. Only in one particularly overcrowded, the maximum concentration was 1 ppm. For CO 2 levels, the values recorded also never exceeded 1,000 ppm, ranging from a minimum of 678 ppm to a maximum of 946 ppm, and the H 2 S values were 0 ppm in each one. In addition, all buffalo calves evaluated with the calf health score had a score of 0, indicating optimal health conditions. The monitored seven buffalo farms showed adequate attention to environmental conditions, and all the raised buffalo calves showed optimal health status.

Single-step genomic best linear unbiased predictor (ssGBLUP) is a method for jointly estimating breeding values (BV) for genotyped and non-genotyped animals. Genomic information in the Italian Mediterranean Buffalo (IMB) is now available. Its inclusion in the genetic evaluation system could increase both the accuracy and genetic progress of the traits of interest of the breed. The study aimed to test the feasibility of ssGBLUP and show the first results of implementing a genomic evaluation for production and type traits in the IMB. Phenotypic information on production (270-day milk, mozzarella yield (MY), protein and fat kg and %, respectively) and morphology: feet and legs (FL) and mammary system (MS) were used for this study. Production records included 743,904 lactations from 276,451 buffalo cows born from 1984 to 2019. Morphological traits were from 91,966 buffalo cows from 2004 to 2022. Regarding the genotypes, 2,017 buffalo cows and 133 bulls were used. Data were analyzed fitting two multi-trait animal models, a 6-trait model for production data and a 2-trait model for morphology data. According to the relationship matrix used, two models were fitted: (i) the BLUP with the numerator relationship matrix (A) and (ii) the ssGBLUP where A and the genomic relationship matrix (G) are blended into H. BVs were estimated with BLUP and ssGBLUP models. The cutoff year used to create the partial data set was 2012. The correlation, accuracy, dispersion, and bias statistics were calculated (LR method). Both bulls (N=49) and cows (N=1288) were used for validations. On average, the correlation between EBVs from partial and whole datasets estimated with BLUP and ssGBLUP increased from 6 to 49% and from 14 to 17% for production and type traits, respectively. Among the traits analyzed, the most affected by the change were protein/fat content, MY, and AM. The accuracy increase for these traits was above 20% when using the ssGBLUP. All LR statistics also improved for non-genotyped females. These results showed that implementing ssGBLUP in the breeding program can generate more accurate predictions for essential traits in dairy IMB than traditional BLUP.

Milk is one of the most nutritionally complete foods and plays an important role in the human diet. Buffalo milk represents 15% of worldwide milk production and is an important source of bioactive compounds. Buffalo milk has a great market in the Mediterranean area, and dairy products, such as Mozzarella and Ricotta di Bufala Campana, obtained with the Italian Mediterranean buffalo milk, are acknowledged with the Protected Designation of Origin (PDO). This study aimed to characterize, using high-throughput sequencing of the 16S rRNA gene, the milk core microbiome of water buffalo rises in the Amaseno Valley included in the Mozzarella PDO region. The principal features of the core and the auxiliary buffalo milk microbiome are the predominance of Firmicutes and Lactococcus, one of the most important lactic acid bacteria (LAB) taxa in the dairy industry. The comparative analysis of the core microbiomes indicated that the milk of the Italian Mediterranean Buffalo and other mammals share the presence of Streptococcus-affiliated OTUs (operational taxonomic units). Our data also demonstrated that the core microbiome of milk samples collected from PDO and non-PDO regions differ in the number and type of taxa. Key points: • Buffalo milk and their derivate products are becoming more popular worldwide. • Dairy locations and practice management affect the structure of the milk microbiota. • Next-generation sequencing (NGS) analysis allows to identify the features of the Italian Buffalo milk microbiome. [ABSTRACT FROM AUTHOR]

Highlights • Reasonable imputation accuracy for buffalo can be achieved by imputing from a low-density to 90K SNP BeadChip even using a small reference population size. • With a small reference population size, minimac performed better than the two other imputation tools. • Accurate imputations were obtained using FImpute followed by Beagle and minimac when a relatively large reference population size was used. • Poor imputation for rare alleles could be traced when using the correlation coefficient as a measure of imputation accuracy. Abstract The accuracy of genotype imputation from a customized low-density to a moderate-density single-nucleotide polymorphism marker panel was tested in Italian Mediterranean buffalo using different sizes of reference populations (RP) and imputation programs. Masked genotypes were imputed using Beagle, minimac and FImpute. The accuracy of predicted genotypes was assessed by the percentage of correctly imputed genotypes. As expected, overall imputation accuracy was better for larger RP sizes. However, increasing the RP size from small to intermediate (i.e., from 42 to 202) resulted in a greater improvement in imputation accuracy compared to increasing the RP size from intermediate to large (i.e., from 202 to 736). The percentage of correctly imputed genotypes was 97.3%, 97.9% and 98.0% for minimac, Beagle and FImpute, respectively, using 736 reference individuals. The accuracy of imputation tended to decrease for high minor-allele frequency of imputed genotypes especially when the RP size was small. The variation in accuracy with increasing RP size was highest for Beagle and lowest for minimac. The accuracy of imputation was larger when the genomic relationship between the reference and the target populations was higher for all three imputation software tools used in this study. The trend of increasing imputation accuracy with genomic relationship was strongest when the RP size was small. Our results indicate that imputation of genotypes from a low to a moderate density panel (i.e., 10K to 90K) is a valid option to reduce the cost of genotyping for genomic evaluation in Italian Mediterranean buffalo. [ABSTRACT FROM AUTHOR]

Sorghum could be a potential substitute to maize in Mediterranean buffaloes feed in order to improve sustainability of buffalo-based agriculture, due to its reduced water and nitrogen requirements compared with maize, which is currently fed primarily. The aim of this study is to obtain information on rumen degradability of fibre fraction of maize and sorghum silages and to investigate the relationship between degradability and rumen microbial populations. As such four cannulated buffalo milking cows were fed ad libitum two different iso-energetic and iso-proteic diets based on maize silage (MS) and sorghum silage (SS). Based on plate counts, values of cellulolytic bacteria showed to be higher within the rumen of SS fed buffaloes compared to MS fed buffaloes (4.4 × 109 vs 1.9 × 109 cfu/ml, P

Abstract: Sixteen Italian Mediterranean Buffalo young bulls were divided into two groups fed isoprotein and isoenergy diets and only differing for protein source of concentrate: faba bean (FB) vs soybean (SB). Animals were slaughtered at 350kg BW. Meat from FB group showed significantly lower fat, protein, cholesterol and saturated fatty acids than SB group. Significant differences were also found between the three muscles analysed [Longissimus thoracis (LT), Semitendinosus (ST) and Iliopsoas plus Psoas minor (IP)]. ST showed the most favourable fatty acids profile: lower SFA, higher PUFA, MUFA, ω-3, ω-6, CLA and, consequently, lower values for both atherogenic and thrombogenic indexes. Results showed that faba bean can be used as a protein source alternative to soybean in the diet of young buffalo bulls for the production of high quality meat. [Copyright &y& Elsevier]

The present paper contributes to improve knowledge about the environmental impact of the production chain of buffalo mozzarella, a topic little studied in literature. The analysis involved 6 farms located in North-Eastern Italy, specialized in buffalo milk production, and one dairy plant, where the whole milk was processed in mozzarella cheese. A "from cradle to plant gate" Life Cycle Assessment approach was used, considering, at farm level, a MILK Scenario, that reflected the real situation of farms, and a BEEF Scenario, that included buffalo beef production. Two further scenarios were considered at plant level: MOZZARELLA Scenario, that considered the mozzarella production only, and CHEESE Scenario, that considered the production of ricotta and ripened cheese in addition to mozzarella cheese. Three allocation methods were performed: no-allocation, physical allocation and economic allocation. 1 kg of fat and protein corrected milk and 1 kg of packaged mozzarella cheese were used as functional units. Within the MOZZARELLA Scenario, Global Warming Potential (GWP) was 33.9, 28.9 and 32.7 kg CO 2 eq, Acidification Potential (ACP) was 247.9, 211.4 and 238.7 g SO 2 eq, and Eutrophication Potential (EUP) was 62.2, 53.0 and 59.9 g PO 4 3−eq per kg of mozzarella cheese, performed with no-allocation, physical allocation and economic allocation, respectively. Within the CHEESE Scenario, GWP was 36.7, 27.9 and 33.2 kg CO 2 eq, ACP was 267.9, 203.6 and 242.8 g SO 2 eq, EUP was 67.2, 51.1 and 60.9 g PO 4 3−eq per kg of mozzarella cheese, performed with no-allocation, physical allocation and economic allocation, respectively. GWP, ACP, and EUP of mozzarella cheese derived mainly by the emissions from milk production processes, were 95%, 92%, 81%, respectively. Therefore, the main strategy for reducing the emission is to improve the farm efficiency in terms of milk production. At plant level, the limited or no reduction of the emissions obtained with the economic allocation pointed out the necessity of a proper economic exploitation of alternative products in order to reduce the environmental impact of the principal one. • Environmental impacts of buffalo mozzarella cheese production were assessed. • The fattening of young buffalo bulls can influence the impact of mozzarella cheese. • More than 90% of mozzarella cheese impact was ascribed to milk production. • Global warming potential of 1 kg of buffalo mozzarella cheese is 29–34 kg CO 2 eq. [ABSTRACT FROM AUTHOR]