1,721,198 research outputs found
SNPs in coat colour genes in goats
No full textCoat colour genes are useful candidates for breeds traceability of farm animals. To identify SNPs in genes involved in pigmentation in goat, we carried out in silico studies in human, mouse and cattle. We analysed 41 genes and we found: 88 SNPs in mouse, 29 synonymous and 59 non synonymous; 279 SNPs in humans, 121 synonymous and 158 non synonymous, 78 of which validated; 147 putative SNPs in cattle, 62 synonymous and 75 non synonymous, 10 of which validated. To identify the more interesting coding regions, we collected in these species information on pigmentation traits or on pathologies associated to different mutation. In goat, molecular information were available only on 7 genes and no SNP is reported, moreover poor information exists on association between mutations and different coat colour. Starting from the information collected in mouse, human and cattle, we obtained PCR products in goat for 61 exons in 36 genes. The PCR products were sequenced and checked for homology with the target sequences. Sequences on 8 animals from 4 breeds (Alpine, Saanen, Blonde of Adamello, Orobica) characterised by different coat colour phenotypes have been compared, revealing 25 SNPs (11 synonymous, 14 non synonymous) in 21 genes
DALLA DOMESTICAZIONE ALLA GENOMICA, COME L’UOMO MODIFICA LE SPECIE ANIMALI CHE ALLEVA
Full text linkThe paper briefly reviews the main steps of animal breeding starting from livestock domestication. The
major cultural changes in biology comprehension during XIX and XX centuries are reported with some
emphasis on the meaning of the infinitesimal model interpreting quantitative phenotypes. Genomic analysis,
dominant on the scenes since the beginning of this century, is explored in a wider way. Genomic selection,
production traceability and association between economic traits and specific regions of genome are briefly
discussed
AI Meets Tradition: Enhancing Italian Small Ruminant Biodiversity through Breed Identification
Full text linkThe conservation and sustainable management of Italian small ruminant breeds are crucial for preserving livestock
biodiversity. Italy counts over 100 sheep and goat breeds, often raised in extensive farming systems and
mountainous and marginal areas, many of which hold high cultural and environmental value. Their presence supports
rural economies and contributes to the identity and landscape of regions with strong tourist appeal. However,
many local breeds are at risk due to limited distribution and declining populations. One key challenge in their
management is the correct registration of an animal to a breed, traditionally based on expert morphological evaluation
and assessment of standard adherence. Artificial intelligence (AI), particularly deep learning techniques, offers
innovative solutions to support this sector. A promising application, explored in few studies with encouraging
results, is the development of AI-powered image-based classification tools for breed identification. Extending this
approach to a broader scale could have significant practical implications. With photographic data collected under
diverse conditions and image augmentation techniques, it becomes possible to build a robust and efficient system
adaptable to the morphological variability of local breeds. Also, georeferencing images might be especially valuable,
as many populations are strongly localized in specific regions; spatial data could thus enhance breed recognition,
even in cases of high phenotypic variability or morphological similarity between breeds. A possible outcome
of this approach could be a user-friendly mobile application to assist breeders, technicians, and associations in
breed identification and registration, streamlining procedures and minimizing animal handling. Additionally, such
a tool could serve an educational purpose, providing users—including tourists and local communities—with information
about each breed’s history, risk status, and typical products. By raising public awareness and fostering
a connection between people and livestock biodiversity, this AI-based solution may contribute to the conservation
and valorization of Italy’s small ruminant heritage, while supporting the resilience of rural areas
Analisi di geni candidati nelle variazioni quanti-qualitative della frazione lipidica del latte caprino
No full textFactors affecting milk production and prolificacy of Alpine goats in Lombardy (Italy)
No full textIn order to evaluate the adaptation of a newly introduced breed and of a production system, the effects of herd-year, season of kidding, parity, and, where appropriate, prolificacy on milk yield, lactation length and prolificacy of Alpine goats in the Italian region of Lombardy were investigated. Analysis of two consecutive years, 1298 lactation records, from 34 herds, gave mean values (±SE) of 567±6 kg for milk yield, 231±1 days for lactation length and 1.6±0.01 kids per kidding. Milk yield and lactation length were primarily influenced by the herd-year factor (p<0.001, partial R 2 0.68 and 0.55, respectively) which mainly reflects differences in herd management. Milk yield was also affected by season of kidding (p<0.001, partial R 2 0.4), parity (p<0.001, partial R 2 0.03) and litter size (p<0.001, partial R 2 0.01). Lactation length was also affected by parity (p<0.001 R 2 0.16) and season of kidding (p<0.001 R 2 0.06) Prolificacy was affected by parity and by herd-year factor (p<0.001, partial R 2 0.09). Kidding early in the year gave higher milk yields, longer lactations and higher prolificacy, but in the choice of the kidding season also the higher prices of kid meat just before Easter have to be considered. Maximum milk yield and prolificacy were attained late (in 4th and 5th lactation), probably due to early age at first kidding. The relevant effect of the herd-year factor indicates that performances of Alpine goats in Lombardy can be successfully improved with an adequate management. Our findings confirm that litter size should not be ignored when establishing correction factors in order to compare milk yields
Stearoyl CoA desaturase (SCD) gene polymorphisms in Italian cattle breeds
No full textStearoyl CoA desaturase (SCD) is the key enzyme involved in the endogenous synthesis of conjugated linoleic acid (CLA) in ruminants. Changes in the enzymatic activity as a result of SCD gene polymorphism and regulation have been hypothesized to cause diet-independent variations of CLA content in milk. Evidences for the direct influence of SCD polymorphism on fatty acid composition of milk and beef have also been reported. To evaluate genetic differences because of breed and/or selection goal, we investigated the polymorphism of three previously reported single nucleotide polymorphisms located in exon 5 of the SCD gene in 11 cattle breeds raised in Italy and selected for different production goals. Results obtained: (i) evidenced a high variability in the allele frequencies across breeds; (ii) detected three novel haplotypes, one of which is private to indigenous beef breeds, and (iii) showed a significant association between haplotypes and selective goal
Sustainability challenges in the Italian pet sector
Full text linkItaly is home to 8.8 million dogs and 10 million cats, with an additional 1-2 million stray dogs and 2.5 million
stray cats. Despite only 15% of dogs and < 1% of cats have a registered pedigree, the purebred animal market
valued at €165-350 million per year. The Italian pet food industry generates €3 billion annually, selling 673,000
tons of pet food. Beyond food, Italians spend €100 million/year on cat litter and €85 million on accessories. A
rough estimate for the impact of pet food sector alone is 1.4-3.8 Mt CO2eq, accounting for 5-12% of agricultural
emissions. It consumes 0.13-0.28 km3 of freshwater, equal to 0.8-1.7% of agricultural water use, while occupying
6-9% (1-1.5MHa) of Italy’s total agricultural area. Our pilot survey describes 60 Italian dogs and 56 Italian cats.
Among dogs, 45% were purebred, including 15% with unregistered pedigrees, while 86% of cats were mixedbreed.
Regarding diet, 73% of cat owners provided both dry and wet food, primarily poultry and fish-based, while
65% of dog owners fed only dry food, with ruminant proteins (beef, lamb) as the most common, followed by
poultry and fish. Monthly food expenses ranged from €13-58 per cat and €35-60 per dog. Litter usage for cats
varied between 4-10 kg per month, costing €5-19, but only 23% of owners purchasing litter chose biodegradable
materials. Annual veterinary and medication costs ranged from €64-170 for cats and €160-400 for dogs. Additional
costs included pet sitters, boarding, accessories, grooming, training, and insurance. These findings highlight
economic and environmental challenges in pet ownership. Sustainable pet care requires multidisciplinary expertise,
genetic management, and alternative proteins to reduce the pet food carbon footprint. Life Cycle Assessment
should be applied across the supply chain, with environmental certification on packaging to promote sustainable
choices. Italy should foster scientific innovation while ensuring environmental responsibility and ethical animal
care. The future challenge is sustainable breeding and management of pets, safeguarding biodiversity and animal
welfare within a One Health approach
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