This study aimed to explore the effect of abiotic [microclimate, management (MS) and milking system (MLS)] and biotic risk factors (microorganism group, age class of ewes, lactation month and ewe genotype) on the occurrence of subclinical mastitis in low-input dairy sheep farms. Samplings were carried out in 10 extensively and 10 semi-intensively managed low-input dairy sheep farms, with three milking systems: milking parlour machine (MPM), portable milking machine (PM) and hand milking (HM). Over two consecutive lactations, milk samples (n = 9624) were collected monthly in each farm, from 20 ewes (10 primi- and 10 multi-parous ewes). The ovine major histocompatibility complex (MHC) DQA2 gene was genotyped for all sampled ewes (n = 800). Ambient air temperature and relative humidity were recorded hourly at each farm, in order to calculate the temperature-humidity index (THI) affecting each sampled sheep. Daily milk yield (DMY) per ewe, pH, total bacterial count (TBC) and somatic cell count (SCC) of milk samples were measured. The fixed effects of microclimate, MS, MLS, bacterial pathogen (microorganism group), age class of ewes, lactation month, involved in milk SCC and subclinical mastitis occurrence, were explored with linear mixed-effects (LME) models. Milk samples with SCC 400 × 10³ (cells/mL) and ≥250/mL Colony Forming Units of one or two udder pathogens (in the microbiological examination) were defined as subclinical mastitis positive. Subclinical mastitis was found in 53 % (n = 1336) of microbiologically examined milk samples, with Staphylococcus spp. being the most prevalent amongst isolated pathogens. A positive correlation was found between SCC and TBC values (r = 0.687, p < 0.001, df = 1598). LME models revealed that subclinical mastitis prevalence was related to the age class of ewes (p < 0.05) and lactation month (p < 0.001), but not to MS or MLS (p> 0.05). MLS (p < 0.01), age class of animals (p < 0.05) and lactation month (p < 0.05) affected SCC of milk samples. The LME model, with SCC milk values ≥400 × 10³ as dependent variables, revealed a significant effect of microclimate (β = 0.014, SE = 0.004, p < 0.001) and microorganism group [F(1,162) = 4.29, p < 0.001] on SCC. The MHC DQA2 allele B1 ("0602") was found at a lower frequency in ewes with subclinical mastitis (p < 0.05). In conclusion, microclimate and MLS (from the abiotic factors) and microorganism group, age class of ewes and lactation month (from the biotic factors) had a significant effect on milk SCC, while age class of ewes and lactation month (from the biotic factors) had a significant effect on subclinical mastitis occurrence. To our knowledge, this is the first report exploring the effect of microclimate (THI), PM milking and DQA2 gene on subclinical mastitis of sheep reared under low-input management systems.

这项研究旨在探讨非生物性[小气候，管理（MS）和挤奶系统（MLS）]和生物危险因素（微生物组，母羊的年龄等级，泌乳月和母羊基因型）对低临床亚乳腺炎发生的影响。输入奶牛场。在10个广泛管理和10个半密集管理的低投入奶牛场中进行了采样，这些农场具有三个挤奶系统：挤奶厅机（MPM），便携式挤奶机（PM）和手动挤奶机（HM）。连续两次泌乳，每个农场每月从20头母羊（10头母羊和10头多​​头母羊）中采集牛奶样本（n = 9624）。绵羊主要组织相容性复合体（MHC）DQA2对所有采样母羊（n = 800）进行基因分型。每个农场每小时记录一次环境温度和相对湿度，以计算影响每只采样绵羊的温度-湿度指数（THI）。测量了每只母羊的每日产奶量（DMY），pH，牛奶样品的总细菌数（TBC）和体细胞数（SCC）。利用线性混合效应（LME）模型探讨了小气候，MS，MLS，细菌病原体（微生物组），母羊的年龄等级，泌乳月，牛奶SCC和亚临床乳腺炎发生的固定作用。SCC 400×10 ^3的牛奶样品一或两种乳房病原体的菌落形成单位（细胞/ mL）和≥250/ mL（在微生物学检查中）被定义为亚临床乳腺炎阳性。在53％（n = 1336）的微生物学检查的牛奶样本中发现亚临床乳腺炎，葡萄球菌属。在分离的病原体中是最普遍的。在SCC和TBC值之间发现正相关（r = 0.687，p <0.001，df = 1598）。LME模型显示，亚临床乳腺炎患病率与母羊的年龄类别（p <0.05）和哺乳期（p <0.001）有关，而与MS或MLS（p> 0.05）不相关。MLS（p <0.01），动物年龄等级（p <0.05）和泌乳月（p <0.05）影响了牛奶样品的SCC。LME模型，SCC牛奶值≥400×10 ³作为因变量，揭示了微气候（β= 0.014，SE = 0.004，p <0.001）和微生物组[F（1,162）= 4.29，p <0.001]对SCC有显着影响。在患有亚临床性乳腺炎的母羊中发现MHC DQA2等位基因B1（“ 0602 ”）的频率较低（p <0.05）。总之，小气候和MLS（来自非生物因素）和微生物组，母羊的年龄等级和泌乳月（来自生物因素）对牛奶SCC有显着影响，而母羊的年龄等级和哺乳期（来自生物因素） ）对亚临床乳腺炎的发生有重大影响。据我们所知，这是第一个探讨小气候（THI），PM挤奶和DQA2的影响的报告 低投入管理系统饲养的绵羊亚临床乳腺炎基因