Temporal and spatial dynamics of surface run‐off from Lake Basaka catchment (Ethiopia) using SCS‐CN model coupled with remote sensing and GIS

The Lake Basaka catchment (Ethiopia) has undergone a significant land use–land cover (LULC) change and lake level rise over the past five decades. Significant quantities of water and sediment flow annually into the lake through erosion processes. An appropriate method of estimating the surface run‐off from such ungauged and dynamic catchment is extremely important for delineating sensitive areas (based on run‐off responses) to be protected and for development of suitable measures to reduce run‐off and associated soil loss. Reliable prediction of run‐off, however, is very difficult and time‐consuming for catchments such as that of Lake Basaka. The present study estimated the dynamics of surface (direct) run‐off using the NRCS‐CN model in ArcGIS, assisted by remote sensing and ancillary data. The results indicated the Lake Basaka catchment experienced significant temporal and spatial variability in its run‐off responses, depending on the rainfall (amount and distribution) pattern and LULC changes. A significant run‐off increase occurred after 1973, consistent with significant LULC changes and lake level increments occurring after that period. A reduced vegetation cover also resulted in increased run‐off coefficient of the lake catchment from 0.11 in the 1970s to 0.23 in the 2000s, indicating the important need to consider possible future LULC evolution when forecasting the lake catchment run‐off behaviour.     

Analysing decadal land use/cover dynamics of the Lake Basaka catchment (Main Ethiopian Rift) using LANDSAT imagery and GIS

Development of accurate classification methods for rapidly changing catchments like that of Lake Basaka is fundamental to better understanding the catchment dynamics, which were not addressed in previous studies. Thus, the aim of this study was to map the decadal land use/cover (LUC) regimes of the Lake Basaka catchment, utilizing time series of LANDSAT images and to analyse the changes that occurred at different time periods. Both unsupervised and supervised image classification systems were utilized in Earth Resources Data Analysis System (ERDAS) Imagine (9.1). Appropriate pre‐ and postprocessing also was utilized. Seven major LUC classes were identified in the final land cover maps produced after the supervised (maximum likelihood) classification exercise. The analysis results indicated the Lake Basaka catchment had experienced a drastic change in its LUC conditions over the last 4–5 decades because of rapid increases in human settlement, deforestation, establishment of irrigation schemes and Awash National Park (ANP). Approximately 18 924 ha of forest and 4730 ha of grazing lands were devastated between 1973 and 2008. At the same time, there was a shift in land cover from forests/woodlands to open woodlands, shrub and grazing lands. The land cover classifications generally were achieved at a very high overall accuracy (84.34%) and overall kappa statistics (0.802), substantiating the value of using the classified LUC in this study as an input to hydrological models. This study results provide an opportunity to better understand and quantify the hydrological response regimes of the lake catchment from the perspective of changing LUC conditions during different hydrological periods and the resulting dynamics of the lake water balance.     

Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions

Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH₄) emissions from individual cows. Several techniques have been developed to measure CH₄ in a research setting but most are not suitable for large-scale recording on farm. Several groups have explored proxies (i.e., indicators or indirect traits) for CH₄; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH₄ proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The proxies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbiome profiling. Proxies based on rumen samples are generally poor to moderately accurate predictors of CH₄, and are costly and difficult to measure routinely on-farm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH₄ emission in dairy cows. No single proxy was found to accurately predict CH₄, and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of variation in CH₄ and one proxy can correct for shortcomings in the other(s). The most important applications of CH₄ proxies are in dairy cattle management and breeding for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavorable correlated responses. Finally, although combinations of proxies appear to provide the most accurate estimates of CH₄, the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments.     

Dispersive Liquid–Liquid Microextraction Followed by Capillary High-Performance Liquid Chromatography for the Determination of Six Sulfonylurea Herbicides in Fruit Juices

In this study a simple, rapid, and efficient method has been developed for the determination of six sulfonylurea herbicides (SUHs): triasulfuron, metsulfuron-methyl, chlorsulfuron, flazasulfuron, chlorimuron-ethyl, and primisulfuron-methyl in commercial grape and apple juice samples, using dispersive liquid–liquid microextraction coupled with capillary high-performance liquid chromatography with diode array detection. Various parameters that influence the extraction efficiency, such as the type and volume of extraction and disperser solvents, sample pH, and salt addition, were investigated and optimized. Under the optimum conditions, limits of detection and quantification of the method were in the ranges of 2–9 and 8–29 μg L^?1, respectively, lower than the maximum residue limits set by the European Union for the raw fruits, such as grape and apple. The intra- and inter-day relative standard deviations varied from 1.0 to 8.2 and 1.8 to 9.8 %, respectively, with recoveries between 72.0 and 109.5 % for commercial grape (both white and red) and apple juice samples, showing satisfactory accuracy for the determination of SUHs in fruit juices.     

The role of livestock diversification in ensuring household food security under a changing climate in Borana,Ethiopia

While food insecurity is a growing concern across the developing nations, accentuated by climate variability and change, it could be even worse for pastoralists given their unpredictable exposure to climate risks. The Borana herders experience food insecurity as a result of recurring droughts causing huge losses of cattle, and are thus increasingly shifting from cattle pastoralism to multi-species herding. The present study examines the role of livestock diversification in combating household food insecurity using herders’ perceptions, a modified household food insecurity access scale (mHFIAS) and dietary diversity score. Herders perceived child growth, adult height and body condition to be decreasing as a result of declining milk production and changing dietary trends. Results also revealed a high level of seasonal food insecurity and low dietary diversity with the majority (81 %) consuming one to three food groups. Livestock diversification was a major factor affecting household food security. Households practising diversification had significantly fewer months of food deficit (2.3 vs. 3.8), lower mHFIAS (5.5 vs. 8.7) and a higher average off-take in the form of livestock sales (7.4 vs. 4.0) than non-diversified ones. Diversification improved dietary intake of specific food groups and the average number of meals consumed per day. While fruits, eggs and fish are not part of the Borana diet, a large number of respondents consumed no vegetables (93 %) or meat (96 %), potentiating the risk of micronutrient deficiencies. This study highlights the particular significance of livestock diversification, among other socio-demographic factors, in attaining food security under a changing climate in the study area.     

Genetic association of clinical mastitis with test-day somatic cell score and milk yield during first lactation of Finnish Ayrshire cows

In this study the genetic association during lactation of 2 clinical mastitis (CM) traits: CM1 (7 d before to 30 d after calving) and CM2 (31 to 300 d after calving) with test-day somatic cell score (SCS) and milk yield (MY) was assessed using multitrait random regression sire models. The data analyzed were from 27,557 first-lactation Finnish Ayrshire cows. Random regressions on second- and third-order Legendre polynomials were used to model the daily genetic and permanent environmental variances of test-day SCS and MY, respectively, while only the intercept term was fitted for CM. Results showed that genetic correlations between CM and the test-day traits varied during lactation. Genetic correlations between CM1 and CM2 and test-day SCS during lactation varied from 0.41 to 0.77 and from 0.34 to 0.71, respectively. Genetic correlations of test-day MY with CM1 and CM2 ranged from 0.13 to 0.51 and from 0.49 to 0.66, respectively. Correlations between CM1 and SCS were strongest during early lactation, whereas correlations between CM2 and SCS were strongest in late lactation. Genetic correlations lower than unity indicate that CM and SCS measure different aspects of the trait mastitis. Milk yield in early lactation was more strongly correlated with both CM1 and CM2 than milk yield in later lactation. This suggests that selection for higher lactation MY through selection on increased milk yield in early lactation will have a more deleterious effect on genetic resistance to mastitis than selection for higher yield in late lactation. The approach used in this study for the estimation of the genetic associations between test-day and CM traits could be used to combine information from traits with different data structures, such as test-day SCS and CM traits in a multitrait random regression model for the genetic evaluation of udder health.     

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

Currently, routine recordings of dry matter intake (DMI) in commercial herds are practically nonexistent. Recording DMI from commercial herds is a prerequisite for the inclusion of feed efficiency (FE) traits in dairy cattle breeding goals. To develop future on-farm phenotyping strategies, recording strategies that are low cost and less demanding logistically and that give relatively accurate estimates of the animal's genetic merit are therefore needed. The objectives of this study were (1) to estimate genetic parameters for daily DMI and FE traits and use the estimated parameters to simulate daily DMI phenotypes under different DMI recording scenarios (SCN) and (2) to use the simulated data to estimate for different scenarios the associated reliability of estimated breeding value and accuracies of genomic prediction for varying sizes of reference populations. Five on-farm daily DMI recording scenarios were simulated: once weekly (SCN1), once monthly (SCN2), every 2 mo (SCN3), every 3 mo (SCN4), and every 4 mo (SCN5). To estimate reliability of estimated breeding values, DMI and FE observations and true breeding values were simulated based on variance components estimated for daily observations of Nordic Red cows. To emulate realistic on-farm recording, 5 data set replicates, each with 36,037 DMI and FE records, were simulated for real pedigree and data structure of 789 Holstein cows. Observations for the 5 DMI recording scenarios were generated by discarding data in a step-wise manner from the full simulated data per the scenario's definitions. For each of these scenarios, reliabilities were calculated as correlation between the true and estimated breeding values. Variance components and genetic parameters were estimated for daily DMI, residual feed intake (RFI), and energy conversion efficiency (ECE) fitting the random regression model. Data for variance components were from 227 primiparous Nordic Red dairy cows covering 8 to 280 d in milk. Lactation-wise heritability for DMI, RFI, and ECE was 0.33, 0.12, and 0.32, respectively, and daily heritability estimates during lactation ranged from 0.18 to 0.45, 0.08 to 0.32, and 0.08 to 0.45 for DMI, RFI, and ECE, respectively. Genetic correlations for DMI between different stages of lactation ranged from ?0.50 to 0.99. The comparison of different on-farm DMI recording scenarios indicated that adopting a less-frequent recording scenario (SCN3) gave a similar level of accuracy as SCN1 when 17 more daughters are recorded per sire over the 46 needed for SCN1. Such a strategy is less demanding logistically and is low cost because fewer observations need to be collected per animal. The accuracy of genomic predictions associated with the 5 recording scenarios indicated that setting up a relatively larger reference population and adopting a less-frequent DMI sampling scenario (e.g., SCN3) is promising. When the same reference population size was considered, the genomic prediction accuracy of SCN3 was only 5.0 to 7.0 percentage points lower than that for the most expensive DMI recording strategy (SCN1). We concluded that DMI recording strategies that are sparse in terms of records per cow but with slightly more cows recorded per sire are advantageous both in genomic selection and in traditional progeny testing schemes when accuracy, logistics, and cost implications are considered.     

From triadic closure to conference closure: the role of academic conferences in promoting scientific collaborations

An academic conference is not only a venue for publishing papers but also a nursery room for new scientific encounters. While previous research has investigated scientific collaboration mechanisms based on the triadic closure and focal closure, in this paper, we propose a new collaboration mechanism named conference closure. Conference closure means that scholars involved in a common conference may collaborate with each other in the future. We analyze the extent to which scholars will meet new collaborators from both the individual and community levels by using 22 conferences in the field of data mining extracted from DBLP digital library. Our results demonstrate the existence of conference closure and this phenomenon is more remarkable in conferences with high field rating and large scale attendees. Scholars involved in multiple conferences will encounter more collaborators from the conferences. Another interesting finding is that although most conference attendees are junior scholars with few publications, senior scholars with fruitful publications may gain more collaborations during the conference. Meanwhile, the conference closure still holds if we control the productivity homophily. Our study will shed light on evaluating the impact of a conference from the social function perspective based on the index of conference closure.     

Chemical composition of naturally fermented buttermilk

Naturally fermented buttermilk, prepared from soured cream or milk, was collected during two seasons from sixteen farms in northern Ethiopia, to study chemical composition and flavour compounds. Protein, fat, organic acids, carbohydrates and volatile compounds were quantified using Kjeldahl, Gerber, high‐pressure liquid chromatography (HPLC) and headspace GC methods, respectively. Widely differing concentrations of organic acids and volatile compounds among samples indicated variable fermentation in the products. This indicates the need for the introduction of the standardisation of the process to supply the market with homogenous buttermilk products.     

Genetic and phenotypic relationships among milk yield and somatic cell count before and after clinical mastitis

This paper studies whether cows with originally lower somatic cell count (SCC) are more susceptible to clinical mastitis (CM) than cows with higher somatic cell count, and evaluates the correlations between CM, SCC, and milk yield. Data were extracted from the Finnish national milk-recording database and from the health recording system. First and second lactation records of 87,861 Ayrshire cows calving between January 1998 and December 2000 were included. Traits studied were incidence of CM, test-day SCC, and test-day milk yield before and following CM. Genetic parameters were estimated using multitrait REML with a sire model. Results did not indicate that cows with genetically low SCC would be more susceptible to CM. The genetic correlation between CM in the first and second lactation was reasonably high (0.73), suggesting that susceptibility to mastitis remains similar across lactations. The genetic correlation between CM and milk yield traits was positive (from 0.38 to 0.56), confirming the genetic antagonism between production and udder health traits. The genetic correlation between SCC and milk was positive in the first lactation, but negative, or near zero in the second lactation. This indicates that breeding for lower SCC might not affect milk production in later lactations. The results of this study support the use of SCC as an indicator of mastitis and a tool for selection for mastitis resistance.