Dairy intensification in developing countries:effects of market quality on farm-level feeding and breeding practices

Smallholder dairy production represents a promising income generating activity for poor farmers in the developing world. Because of the perishable nature of milk, marketing arrangements for collection, distribution and sale are important for enhanced livelihoods in the smallholder dairy sector. In this study we examined the relationship between market quality and basic feeding and breeding practices at farm level. We define market quality as the attractiveness and reliability of procurement channels and associated input supply arrangements. We took as our study countries, India with its well-developed smallholder dairy sector, and Ethiopia where the smallholder dairy industry has remained relatively undeveloped despite decades of development effort. We conducted village surveys among producer groups in 90 villages across three States in India and two Regions in Ethiopia. Producer groups were stratified according to three levels of market quality – high, medium and low. Data showed that diet composition was relatively similar in India and Ethiopia with crop residues forming the major share of the diet. Concentrate feeding tended to be more prominent in high market quality sites. Herd composition changed with market quality with more dairy (exotic) cross-bred animals in high market quality sites in both India and Ethiopia. Cross-bred animals were generally more prominent in India than Ethiopia. Herd performance within breed did not change a great deal along the market quality gradient. Parameters such as calving interval and milk yield were relatively insensitive to market quality. Insemination of cross-bred cows was predominantly by artificial insemination (AI) in India and accounted for around half of cross-bred cow inseminations in Ethiopia. Data on perceptions o

Accuracy of genomic breeding values in multi-breed dairy cattle populations

<p>Abstract</p> <p>Background</p> <p>Two key findings from genomic selection experiments are 1) the reference population used must be very large to subsequently predict accurate genomic estimated breeding values (GEBV), and 2) prediction equations derived in one breed do not predict accurate GEBV when applied to other breeds. Both findings are a problem for breeds where the number of individuals in the reference population is limited. A multi-breed reference population is a potential solution, and here we investigate the accuracies of GEBV in Holstein dairy cattle and Jersey dairy cattle when the reference population is single breed or multi-breed. The accuracies were obtained both as a function of elements of the inverse coefficient matrix and from the realised accuracies of GEBV.</p> <p>Methods</p> <p>Best linear unbiased prediction with a multi-breed genomic relationship matrix (GBLUP) and two Bayesian methods (BAYESA and BAYES_SSVS) which estimate individual SNP effects were used to predict GEBV for 400 and 77 young Holstein and Jersey bulls respectively, from a reference population of 781 and 287 Holstein and Jersey bulls, respectively. Genotypes of 39,048 SNP markers were used. Phenotypes in the reference population were de-regressed breeding values for production traits. For the GBLUP method, expected accuracies calculated from the diagonal of the inverse of coefficient matrix were compared to realised accuracies.</p> <p>Results</p> <p>When GBLUP was used, expected accuracies from a function of elements of the inverse coefficient matrix agreed reasonably well with realised accuracies calculated from the correlation between GEBV and EBV in single breed populations, but not in multi-breed populations. When the Bayesian methods were used, realised accuracies of GEBV were up to 13% higher when the multi-breed reference population was used than when a pure breed reference was used. However no consistent increase in accuracy across traits was obtained.</p> <p>Conclusion</p> <p>Predicting genomic breeding values using a genomic relationship matrix is an attractive approach to implement genomic selection as expected accuracies of GEBV can be readily derived. However in multi-breed populations, Bayesian approaches give higher accuracies for some traits. Finally, multi-breed reference populations will be a valuable resource to fine map QTL.</p

Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium

COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions

Traditional medicinal plant knowledge and use by local healers in Sekoru District, Jimma Zone, Southwestern Ethiopia

The knowledge and use of medicinal plant species by traditional healers was investigated in Sekoru District, Jimma Zone, Southwestern Ethiopia from December 2005 to November 2006. Traditional healers of the study area were selected randomly and interviewed with the help of translators to gather information on the knowledge and use of medicinal plants used as a remedy for human ailments in the study area. In the current study, it was reported that 27 plant species belonging to 27 genera and 18 families were commonly used to treat various human ailments. Most of these species (85.71%) were wild and harvested mainly for their leaves (64.52%). The most cited ethnomedicinal plant species was Alysicarpus quartinianus A. Rich., whose roots and leaves were reported by traditional healers to be crushed in fresh and applied as a lotion on the lesions of patients of Abiato (Shererit). No significant correlation was observed between the age of traditional healers and the number of species reported and the indigenous knowledge transfer was found to be similar. More than one medicinal plant species were used more frequently than the use of a single species for remedy preparations. Plant parts used for remedy preparations showed significant difference with medicinal plant species abundance in the study area

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP

Quality of Neonatal Healthcare in Kilimanjaro Region, Northeast Tanzania: Learning from Mothers' Experiences.

With a decline of infant mortality rates, neonatal mortality rates are striking high in development countries particularly sub Saharan Africa. The toolkit for high quality neonatal services describes the principle of patient satisfaction, which we translate as mother's involvement in neonatal care and so better outcomes. The aim of the study was to assess mothers' experiences, perception and satisfaction of neonatal care in the hospitals of Kilimanjaro region of Tanzania. A cross sectional study using qualitative and quantitative approaches in 112 semi structured interviews from 14 health facilities. Open ended questions for detection of illness, care given to the baby and time spent by the health worker for care and treatment were studied. Probing of the responses was used to extract and describe findings by a mix of in-depth interview skills. Closed ended questions for the quantitative variables were used to quantify findings for statistical use. Narratives from open ended questions were coded by colours in excel sheet and themes were manually counted. 80 mothers were interviewed from 13 peripheral facilities and 32 mothers were interviewed at a zonal referral hospital of Kilimanjaro region. 59 mothers (73.8%) in the peripheral hospitals of the region noted neonatal problems and they assisted for attaining diagnosis after a showing a concern for a request for further investigations. 11 mothers (13.8%) were able to identify the baby's diagnosis directly without any assistance, followed by 7 mothers (8.7%) who were told by a relative, and 3 mothers (3.7%) who were told of the problem by the doctor that their babies needed medical attention. 24 times mothers in the peripheral hospitals reported bad language like "I don't have time to listen to you every day and every time." 77 mothers in the periphery (90.6%) were not satisfied with the amount of time spent by the doctors in seeing their babies. Mothers of the neonates play great roles in identifying the illness of the newborn. Mother's awareness of what might be needed during neonatal support strategies to improve neonatal care in both health facilities and the communities

Pitfalls of predicting complex traits from SNPs

The success of genome-wide association studies (GWASs) has led to increasing interest in making predictions of complex trait phenotypes, including disease, from genotype data. Rigorous assessment of the value of predictors is crucial before implementation. Here we discuss some of the limitations and pitfalls of prediction analysis and show how naive implementations can lead to severe bias and misinterpretation of results