| 1. |
- Johnsson, Martin
(författare)
-
Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries
- 2021
-
Ingår i: JDS communications. - : American Dairy Science Association. - 2666-9102. ; 2, s. 366-370
-
Tidskriftsartikel (refereegranskat)abstract
- Breeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effects of animals' phenotypes. Genetic evaluations have been successful in advanced economies because of large data sets and strong genetic connectedness, provided by the widespread use of artificial insemination (AI) and accurate recording of pedigree information. In smallholder dairy production systems of many LMICs, the limited use of AI and small herd sizes results in a data structure with insufficient genetic connectedness between herds to facilitate genetic evaluations based on pedigree. Genomic information keeps track of shared haplotypes rather than shared relatives captured by pedigree records. Therefore, genomic information could capture “hidden” genetic relationships, that are not captured by pedigree information, to strengthen genetic connectedness in LMIC smallholder dairy data sets. This study's objective was to use simulation to quantify the power of genomic information to enable genetic evaluation using LMIC smallholder dairy data sets. The results from this study show that (1) genetic evaluations using genomic information were more accurate than those using pedigree information in populations with a high effective population size and weak genetic connectedness; and (2) genetic evaluations modeling herd as a random effect had higher or equal accuracy than those modeling herd as a fixed effect. This demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in situ records collected from herds of ≤4 cows. The establishment of routine genomic evaluations could allow the development of LMIC breeding programs comprising an informal set of nucleus animals distributed across many small herds within the target environment. These nucleus animals could be used for genetic evaluation, and the best animals could be disseminated to participating smallholder dairy farms. Together, this could increase the productivity, profitability, and sustainability of LMIC smallholder dairy production systems.
|
|
| 2. |
- Oliveira de Sousa, Dannylo, et al.
(författare)
-
Effects of supplementing a Bacillus-based direct-fed microbial on performance, nutrient digestibility, rumen fermentation characteristics, and metabolic responses of lactating dairy cows
- 2024
-
Ingår i: JDS communications. - 2666-9102. ; 5, s. 107-112
-
Tidskriftsartikel (refereegranskat)abstract
- This experiment was conducted to evaluate the effects of feeding a Bacillus-based direct-fed microbial (DFM) on performance, nutrient digestibility, rumen fermentation, and metabolic response of lactating dairy cows. Sixty-eight lactating (50 ± 6 d in milk) Holstein-Friesian (n = 20) and Swedish Red (n = 48) cows were enrolled to a 15-wk experiment. Cows were blocked by breed, lactation number, and days in milk and, within blocks, assigned to 1 of the 2 treatments: (1) basal partial mixed ration (PMR) without DFM (n = 34; CON) or (2) basal PMR with the addition of 3 g/head per day of a DFM containing Bacillus licheniformis and Bacillus subtilis (n = 34; DFM). The DFM was mixed in a protein pellet, whereas the CON group was fed the same pellet without DFM (1 kg/cow per day). The PMR contained 53% clover grass silage and 47% compound feed plus 3 kg of a concentrate (dry matter basis) offered during milking. Milk yield and production efficiency were recorded daily, whereas milk samples were collected for 24 h every second week of the study for milk composition. During the experimental period, fecal, rumen fluid, and blood samples were collected from each cow for apparent nutrient digestibility, rumen fermentation, and metabolic responses, respectively. All data were analyzed using the MIXED procedure of SAS. No treatment effects were observed on cows final body weight and daily dry matter intake. However, cows fed DFM had a greater milk yield, milk production efficiency, lactose and total solids yield, and also tended to have a greater energy-corrected milk production efficiency and milk protein yield. No significant differences were observed on nutrient digestibility and total volatile fatty acids, but molar proportion of acetate was greater for cows fed DFM. In contrast, molar proportion of propionate was greater and butyrate tended to be greater for CON. Cows fed DFM had greater mean plasma insulin-like growth factor-I (IGF-I), but no differences were observed for plasma glucose and insulin. In summary, supplementing a Bacillus-based DFM benefited productive responses of lactating dairy cows, while also modulating rumen fermentation and serum IGF-I.
|
|
| 3. |
- Ren, Keni, 1983-, et al.
(författare)
-
Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms
- 2021
-
Ingår i: JDS Communications. - : American Dairy Science Association. - 2666-9102. ; 2, s. 345-350
-
Tidskriftsartikel (refereegranskat)abstract
- Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.
|
|
