Dairy Systems Research Articles

Economic values and selection indexes for dairy traits in Guzerat breed in Brazil.

Economic efficiency is affected by several traits, and as the unit of selection is the individual, in artificial selection, to promote the maximization of economic genetic gain, the traits to be improved must be weighted by their respective economic values. In Brazil, breeding goals are defined empirically, and not based on an economic evaluation, therefore, the aim of this study was to estimate economic values for traits of economic importance in dairy farming systems based on the use of purebred and crossbred Guzerat animals. The economic values for 305-days milk yield (MY), fat yield (FY), protein yield (PY), and somatic cell count (SCC) were calculated for different production systems based on the feed management: System 1, based on pasture grazingwithBrachiaria brizantha or Panicum maximum cv. Mombaçaduring rainy season, andcorn-silage supplementation during the dry season; System 2, based on pasture grazing withBrachiaria brizantha or Panicum maximum cv. Mombaçaduring rainy season, and the mixture of sugarcane including urea supplementation during thedry season. Bioeconomic models were applied to estimate economic values, and a sensitivity analysis was performed. Four selection indexes were defined, each one with different goals: milk (I1), milk + protein yield (I2), I2 + fat yield (I3) and I3 + somatic cell count (I4).The economic values for MY and PY were positive for both production systems. However, for FY, the values were positive for System 2 but negative for System 1. The economic value for SCC was negative (-7.33 per SCS per lactation).The selection responses for I1 were higher than those for I2, I3 and I4, for both production systems. I4 presented the highest expected genetic gain for each trait, except for fat yield, whose expected genetic gain was greater with the use of I2, in both production systems. The results indicates that the inclusion of milk quality traits in the selection index provides better economic return, and due to the small differences in expected genetic superiority, I1 is still the most suitable for crossbred Guzerat herds whose main activity is milk production in Brazil.

ИССЛЕДОВАНИЕ ВЛИЯНИЯ БЕЛКОВОГО ПРОФИЛЯ НА КРИСТАЛЛООБРАЗОВАНИЕ В МОДЕЛЬНЫХ МОЛОЧНЫХ СИСТЕМАХ С ПРОМЕЖУТОЧНОЙ ВЛАЖНОСТЬЮ

The purpose of research is to study the influence of the protein profile of model dairy systems with intermediate moisture content on the process of crystal formation of milk sugar (lactose). Research objectives: selection of formulation components for compiling a protein profile and study of its influence on the process of formation and growth of lactose crystals in model systems during storage. The objects of research were model systems with targeted adjustment of pH values in each of them, imitating skimmed condensed milk with sugar, in which the complete or partial replacement of the protein phase with whey proteins was carried out through the use of dry whey protein concentrate, dry hydrolyzed whey protein (obtained in native or denaturing conditions), dry cheese whey. Studies of microstructural changes in consistency were carried out using the method for determining the size of lactose crystals according to GOST 29245-91. It has been established that a change in the protein profile towards an increase in the content of native and transformed whey proteins in model systems led to a slowdown in the process of lactose crystal formation. At the same time, hydrolyzed whey proteins had a higher degree of crystal growth restriction. The complete replacement of the protein phase with dry whey protein concentrate and dry cheese whey contributed to the intensive growth of crystals at their initial minimum average size (relative to other samples). However, after 14 days of storage, the average crystal size in this model system was comparable to the rest of the samples (including the control), except for the sample using hydrolyzed whey proteins. Regularities of the influence of the active acidity of the medium on the size of the crystals were also revealed. A decrease in pH from 6.2 to 5.6 leads to the formation of lactose crystals of a smaller average size by 1.9–3.3 times.

Biotechnical, economic, and environmental assessment of dairy systems in the Peruvian Amazon utilizing the CLEANED tool

Biotechnical, economic, and environmental assessment of dairy systems in the Peruvian Amazon utilizing the CLEANED tool

Derivation of Economic Values for Breeding Objective Traits of Chinese Holstein Dairy Cows Using a Bio-Economic Model.

Holstein cattle account for the largest proportion of dairy cattle in China. The current China Performance Index (CPI) consists mainly of production traits. To derive economic values (EV) of additional traits for balanced breeding programs, a bio-economic model is necessary. Landless and intensive dairy farms are dominant in China, wherein all feed is purchased, and in-farm technicians and veterinarians are employed. Therefore, in the present study, a tailored bio-economic model was developed using the parameters of a typical dairy farm in North China. The typical farm had 1500 cows and 1400 youngstock, with a replacement rate of 33.5% per year and a productive life of 1090 days. The bio-economic model was on a per cow per year basis and described the revenues and costs from different animal categories. The EVs of 17 traits, including production, calving, fertility, longevity, and health traits, were derived and used to develop a more balanced selection index. Results showed that the bio-economic model can represent the typical dairy farm system in North China. The EVs of production traits were 2.39 Chinese Yuan (CNY), 32.85 CNY, and 89.60 CNY per kg milk yield, fat yield and protein yield, respectively. The EVs of production traits were two to three times higher than those in some European countries, due to the higher prices on milk volume and milk solids in China. The EVs of health traits ranged from -0.45 CNY to -11.95 CNY and were nearly half of those in other countries, due to the lower in-farm veterinarian labour costs. The EVs of most other functional traits were in line with the published values of other countries with similar economic assumptions in the model. Using the calculated EVs, a more balanced selection index was derived by including functional traits. This index had higher relative weight (46.8%) on functional traits than the current CPI (12.5%). With the high milk prices, it is still most profitable to allow for a decline in functional traits, although the decline is considerably smaller with the developed balanced index than with the CPI. Collectively, the bio-economic model and EVs provided the foundations for implementing balanced breeding programs in the Chinese Holstein population.

Leveraging milk mid-infrared spectroscopy to authenticate animal welfare, farming practices, and dairy systems of Parmigiano Reggiano cheese.

Increasing consumer concerns underscore the importance of verifying the practices and origins of food, especially certified premium products. The aim of this study was to evaluate the ability of Fourier-transform mid-infrared (FT-MIR) spectroscopy to authenticate animal welfare parameters, farming practices, and dairy systems. Data on farm characteristics were obtained from the Parmigiano Reggiano Consortium in northern Italy. Animal welfare data were collected by trained veterinarians using the assessment protocol developed by the Italian National Reference Center for Animal Welfare (CREnBA), while bulk milk test-day data were obtained from the laboratory of the Breeders Association of the Emilia Romagna Region (ARAER). A merged final data set of 12,083 bulk FT-MIR spectra records from 949 farms was created. Using a non-hierarchical clustering approach, the farms were classified into 5 dairy systems: 2 'traditional' systems, comprising farms located in either the Apennines or the Po Plain, and 2 'modern' systems, those that used TMR and that did not; a further 'traditional' dairy system was identified comprising farms rearing local breeds. To evaluate the ability of bulk milk to capture differences in farming systems, we conducted an ANOVA on milk composition. The linear models included the following effects: season, dairy system, farm, and the interaction between dairy system and season. The effect of the dairy system was significant for all milk composition traits. A 10-iteration linear discriminant analysis (LDA) was used to evaluate the discriminative ability of the spectra in classifying farming practices and dairy systems. The average results of the area under the receiver operating characteristic curve (ROC-AUC) revealed good authentication performance for genetic type (0.98), housing system (0.91), and feeding system (0.89), medium-low authentication performance for geographical area (0.70), while poor results were obtained for the percentage of concentrate in the diet and animal welfare parameters (0.57 - 0.64). With regard to dairy systems, the best result was obtained when dairy systems were grouped into 2 simplified categories, 'traditional' vs 'modern' (0.89), instead of the 5 categories (0.87). The results of this study show that FT-MIR is a useful tool for authenticating farming practices and dairy systems, but not animal welfare as defined by CREnBA evaluation criteria. Our results show that infrared spectroscopy has the potential to authenticate dairy products and quality label certifications.

Sustainable intensification of dairy farms in temperate Atlantic climate; effects on productive, nutritional and environmental aspects

CONTEXTAnimal diet, farm management, and feed production are factors that need to be considered in order to maximize the efficiency and minimize the environmental impacts of dairy farms. Sustainable forage intensification could be one possible solution in order to maintain food security and profitability and at the same time respect the environment under the threat of climate change. OBJECTIVEThis work simulates the productive, nutritional, and environmental effects of cattle dairy farms in wet temperate regions of North Spain, under sustainable intensification. This approach was based on forage intensification by converting grassland areas to annual forage crops and replacing the concentrate intake in dairy cows' diet by up to 30 %, with silage from the forages produced on-farm. METHODSTwo intensive dairy systems were used, identified according to the herd's diet composition. A model farm that represents an average farm in each of the two characteristic intensive systems was employed, taking into consideration field area and use, number of animals, diet, milk yield and slurry management. The simulation model DairyCant was used to run simulations of the average farms under present management (baseline) and under scenarios over succession of Zea mays L. to various winter forage crops (7 scenarios), with variation of the number of dairy cows in the herd (7 scenarios) and under partial replacement of concentrate in the herd's diet (14 more scenarios), resulting to 28 simulations for each intensive dairy system. RESULTS AND CONCLUSIONSUsing forage intensification, the production of forages was increased and as a consequence, feed imports are reduced, thus feed production is relocated and farmers' profitability could be increased. Besides, the environmental factors, such as the nitrogen (N) surplus and the total N footprint were decreased, indicating that would have the potential to reduce farm GHG emissions and nitrogen losses. The scenarios involving Z. mays L. succession to Trifolium incarnatum were the most interesting, from a productive, nutritional and environmental point of view. SIGNIFICANCEReplacing grassland with annual forage crops and reducing concentrate intake of dairy cows could result to increase of the nitrogen use efficiency (NUE), which means less nitrogen excreted to the environment. At the same time, the reduction of the concentrate provides the potential to improve the economic sustainability of the farms. To establish the realistic implementation of the forage management described here, farmers' abilities and willingness, together with potential supportive policies, must be taken into account.

Animal as the Solution II: Phenotyping for Low Milk Urea Nitrogen A1PF Dairy Cows.

The societal pressure on intensive pastoral dairying demands the search for strategies to reduce the amount of N flowing through and excreted by dairy cows. One of the strategies that is being currently explored focuses on the animal as a solution, as there are differences in N metabolism between cows even within the same herd. This work was conducted to explore such an approach in A1PF herds in New Zealand and the possibility of identifying A1PF cows that are divergent for milk urea nitrogen (MUN) concentration through phenotyping as a potential viable strategy to reduce N leaching and emissions from temperate dairy systems. Three herd tests were conducted to select a population sample of 200 cows (exhibiting the lowest 100 and highest 100 MUN concentrations). Milk samples were collected from the 200 cows during mid and late lactation to test for milk solids content and MUN. From the 200 cows, urine for urinary N concentration (UN), blood for plasma urea N, total antioxidants (TAS), and glutathione peroxidase (GPx) were collected from the 20 extremes (the lowest 10 and highest 10 MUN concentrations). Milk urea N was greater in cows selected as high-MUN cows (16.2 vs. 14.32 ± 0.23 mg/dL) and greater during late lactation (16.9 vs. 13.0 ± 0.19 mg/dL). Milk solids and fat content were 38% and 20% greater in cows selected as low-MUN cows than in high-MUN cows during mid lactation (p < 0.001). Low-MUN cows had lower UN than high-MUN cows during mid lactation (0.64 vs. 0.88 ± 0.11%). The N concentration in the plasma (p = 0.01) and Tas (p = 0.06) were greater during late lactation. There was a positive relationship between the MUN concentration phenotype used for selection and the MUN concentration for the trial period and MUN concentration and UN concentration during mid and late lactation (p < 0.001). Our results suggest that A1PF cows within a commercial herd can be phenotyped and selected for low-MUN, which may be potentially a viable strategy to reduce N losses to the environment and create healthier systems. Following genetic tracking, those cows can be bred to further promote low-MUN A1PF herds.

Characterization of In Situ Ruminal Degradation of Crude Protein and Individual Amino Acids from Ryegrass

In temperate pasture-based dairy systems, ryegrass (Lolium perenne L.) is a key forage due to its high crude protein (CP) content, yet its rapid ruminal degradation could limit the supply of rumen-undegraded protein and essential amino acids (EAAs) to dairy cows. This study aimed to investigate the in situ ruminal degradability of CP and individual amino acids (AAs) in fresh ryegrass at the vegetative stage. Three second-parity, rumen-cannulated Holstein Friesian cows (487 kg body weight, 16.5 kg milk/day) were used for the incubation of ryegrass samples collected in different seasons at the vegetative stage. The degradation kinetics were assessed using the Ørskov and McDonald model, with mathematical corrections for microbial contamination. Results showed that the effective degradability (ED) of AAs was generally higher than that of CP (p &lt; 0.05), exceeding 2%, and that some EAAs, particularly lysine, exhibited an ED up to 5.5% greater than CP (p &lt; 0.05). These differences underscore the need for caution when using CP as a proxy for AA degradation in dietary formulations. Given the high degradability of ryegrass AAs, it would be important to monitor and adjust their supply in diets with high ryegrass inclusion to prevent potential deficiencies that could impair milk production and reduce feed efficiency.

120 Juvenile in vitro fertilization embryo transfer in seasonal pasture-based dairy systems

120 Juvenile in vitro fertilization embryo transfer in seasonal pasture-based dairy systems

Efecto de la aplicación de excretas bovinas y caprinas como una alternativa de fertilización, sobre la producción, calidad nutricional y sanidad en el pasto estrella africana (Cynodon nlemfuensis), en la Finca Experimental Santa Lucía, Heredia

Livestock activity in Costa Rica triggers a growing demand for quality forage for dairy production. Fertilization, a key factor in this process, poses environmental and economic challenges for the sector. The objective of the study was to evaluate the use of bovine and caprine excreta on biomass, nutritional quality, and disease incidence in African star grass, as a nitrogen fertilization alternative in specialized dairy systems. Conducted at the Santa Lucia Experimental Farm of the National University, the study utilized a block design with three repetitions and four treatments. Biomass production was assessed by weighing harvested material, while quality and health were evaluated in the laboratory. The results show that biomass production was not reduced with excreta application, and the grass maintained its nutritional quality, making it a viable fertilization alternative. Puccinia sp. was identified as the main pathogen present in the pasture; however, its incidence is not attributed to the excreta applied. Additionally, no direct effect of the treatments was observed on the nematode population density present in the pasture.

Use of conjoint analysis to weight biosecurity practices on pasture-based dairy farms to develop a novel audit tool-BioscoreDairy.

Risk assessments are important tools to identify deficits in biosecurity management practices. A major strength of some existing tools is that they facilitate cross-country comparisons. However, a weakness is their failure to account for unique intra-national farming enterprise structures such as, for example, pasture-based dairying. Currently, there are no suitable biosecurity risk assessment tools applicable to pasture-based dairying as practiced in Ireland. In addition to a need for enterprise-specific biosecurity risk assessment tools, the weighting of risk scores generated by these tools needs to be context-specific to ensure validity in assessing biosecurity risks in the farming sector of interest. Furthermore, existing biosecurity audits rely exclusively on respondent recall to answer questions about management practices. To address each of these limitations of existing biosecurity risk assessment tools we developed and optimised a new biosecurity risk assessment tool (BioscoreDairy) designed to assess the biosecurity status of pasture-based dairy farms in Ireland. It consists of two parts, a biosecurity questionnaire and a cattle movement records audit. A questionnaire was developed on biosecurity management practices appropriate for a pasture-based dairy system. Multiple national expert groups were leveraged to provide weightings for the different management practices in the questionnaire using the best-worst scaling methodology of MaxDiff. The results of this process provided a numerical categorisation that could then be used to assign scores to the individual biosecurity management practices. These practices were grouped into three biosecurity areas; risk of disease entry, speed of disease spread and diagnosis of infection. Within each of these three areas, a traffic light system was used to compare a farm's biosecurity risks to other similar farms-least risk (green; within the top third of farms), concerning practice (amber; middle third) and worst practice or greatest risk (red; lowest third). In addition to these scores, the cattle introduction profile of a herd over the previous 3 years, based on nationally recorded data, was audited, compared amongst dairy farm enterprise subtypes, and included in the BioscoreDairy report. BioscoreDairy is therefore the first biosecurity risk assessment tool tailored to pasture-based dairy farm systems, both for individual farm reporting and for benchmarking against comparable farms.

The Kerbernez long-term experiment: A dataset on crop yield and soil organic matter evolution in forage crop rotations and permanent grasslands in a temperate oceanic climate.

Forage crop rotations including grasslands, common in dairy systems, are known to ensure good productivity and limit the decrease of soil organic matter frequently observed in permanent arable land. A dataset was built to compile data from the Kerbernez long-term experiment, conducted in Brittany(France) from 1978 to 2005. This experiment compared the effect of different forage crop rotations fertilized with ammonium nitrate and/or slurry, with or without grassland, on forage production (quantity, quality) and changes in soil physio-chemical characteristics. These forage crop rotations were based on silage maize and cut monospecific grasslands of Italian ryegrass (Lolium multiflorum L.) or perennial ryegrass (Lolium perenne L.). More precisely, the experiment compared silage maize monocultures, rotations with silage maize and Italian ryegrass established for 6 to 18 months, and rotations with silage maize and perennial ryegrass established for three to more than 10 years. They are representative of the forage crop rotations and permanent grasslands that were at the heart of Brittany's forage revolution in the 1970s. The dataset includes information about the climate and soil conditions, the management of crops and grasslands, the evolution of topsoil organic carbon and nitrogen stocks, the inter-annual variations in crop and grassland dry matter yields and nitrogen contents. The dataset also includes characterisation of soil structural stability, particle-size soil organic matter fractions and potential soil carbon and nitrogen mineralisation at the end of the trial. It consists of fourteen csv files. This dataset can be used for a variety of purposes, namely for assessing the ability of mechanistic models to simulate soil organic matter dynamics and associated fluxes, and to estimate the influence of grassland presence and duration in forage crop rotations on such fluxes.

Relationships between paddock-level pasture mass and cow data derived from GPS and behavior-monitoring on-animal sensors in rotationally grazed dairy systems.

Data from behavior-monitoring and location (global positioning system) devices fitted to dairy cows may improve our understanding of how animal behavior and movement are associated with feed availability and quality. We hypothesized that data from behavior-monitoring and location sensors may be associated with feed availability in a paddock within a rotationally grazed dairy system. To investigate this, 100 cows were randomly assigned to one of 4 groups (n = 25 cows per group) and allocated to different target pasture allocations to meet either 80%, 100%, or 120% of their estimated ME requirements across 2 experimental periods (n = 20 d per experimental period), during late spring (experimental period 1; November 7 to November 26, 2021) and late summer (experimental period 2; February 27 to March 18, 2022). During both periods, all 4 groups were allocated 100% of ME requirements for 5 d (baseline). Then, 2 groups were under-allocated (80%), whereas the other 2 groups were over-allocated (120%) for 5 d. Subsequently, all groups returned to baseline for 5 d (100%), followed by a switch, where the under-allocated groups were over-allocated, and vice versa, for the final 5 d. Each cow was fitted with 5 devices that were commercially available in New Zealand and measured rumination, eating, grazing, and lying time, and activity. One device also determined cows' location, and these data were used to derive 3 additional behaviors: distance traveled, mean distance to herd mates, and proximity. These data were used as independent variables to build linear models with pasture mass as the response, which was estimated during the experiment using a calibrated rising plate meter. Distance traveled, standardized by pasture area allocated, was an important variable for explaining the variance in paddock-level pasture mass, alongside mean distance to herd mates and rumination time. Using location variables alone (distance traveled and distance to herd mates), adjusted R2 values were 0.38 and 0.40 for both pre- and postgrazing pasture mass (kg DM/cow), respectively. Further, including both location and behavior, model fit improved due to greater variation in pasture mass explained by these independent variables. The best linear model (adjusted R2 = 0.58) was for postgrazing pasture mass (kg DM/cow) with standardized distance traveled, distance to herd mates, and rumination time included as the independent variables. Model fit varied depending on location and behavior variables included, and devices lacking behavior data related to ingestion and mastication of feed (e.g., rumination, grazing, or eating data) were generally poorer performers. Our results demonstrate the additional value that location-based data can provide. Irrespective of this, predictive potential may be limited due to a moderate amount of variation in pasture mass explained by data from behavior-monitoring and location sensors using linear modeling approaches. Therefore, this method may not be suitably accurate to make near real-time grazing management decisions, but the results are promising as a concept.

Multispecies pasture diet and cow breed affect the functional lipid profile of milk across lactation in a spring-calving dairy system.

This study compared the effect of 2 pasture-based feeding systems, namely a traditional perennial ryegrass (PRG) diet, and a recently introduced, more sustainable multispecies swards (MSS) diet, on the functional lipid profile of raw milk. In addition to the 2 pasture diets, the study uniquely examined the combined effects of breed, namely Holstein Friesian (HF) or Jersey Holstein Friesian (JFX), and lactation stage in Ireland, spanning from March to November. Bulk milk samples (n = 144 yearly) for the 4 groups examined were collected for 4 wk per each of the 9 mo specified. Changes in total fatty acid (FA) and triglyceride carbon number profiles were determined by GC with a flame ionization detector, and those in polar lipids (PL) content by HPLC-evaporative light scattering-MS. Based on multivariate analysis, both diet (34.0% contribution) and breed (19.1% contribution) influenced milk FA on a yearly basis; however, in early lactation there were no differences in FA profile between the groups. In middle lactation and late lactation (LL), the MSS diet increased proportions of nutritionally beneficial n-6 and n-3 PUFA in milk, including C18:3 n-3 (ALA), C18:2 n-6 (LA) and C22:5 n-3 (DPA). Although proportions of ALA and LA increased in MSS milks, the LA/ALA ratio remained around 1 for the 2 feeding systems, confirming the beneficial modulation of LA and ALA in milks from pasture-based diets. Particularly in LL, the milk of JFX cows tended to have increased de novo FA, compared with HF, suggesting implications for techno-functional properties of dairy products such as butter. The milk of PRG HF group showed improved health-promoting properties, with lower thrombogenicity and atherogenicity indices on a yearly basis. Regarding techno-functional properties, the PRG HF group resulted in higher oleic acid reflecting in lower spreadability index, suggesting that butter made of this group would be more spreadable, compared with the one made from the other milk groups examined. The triglyceride and PL profiles were mainly affected by stage of lactation. Overall, these results show the effects of cow diet, breed, and stage of lactation on milk lipid profile, with important implications for the nutritional and techno-functional characteristics of dairy products.

Doing GOOD: defining a green operational outcomes domain for nitrogen use in New York corn silage production

CONTEXTEffective nitrogen (N) management is an essential aspect of productivity and sustainability of corn silage (Zea mays L.) production in New York (NY) dairy systems. Implementing end-of-season evaluations for N use can help farms identify opportunities to refine N management over time, and support field experimentation through the NY adaptive N management process. OBJECTIVESThe objectives of this study were to (1) define operational or feasible outcome values for end-of-season field N use efficiency (NUE) indicators in NY corn silage production, (2) characterize NUE indicators across a dataset of field observations, and (3) delineate complementary graphical tools and numerical indicators to identify opportunities for N management refinement over time. METHODSData were collected for 994 corn silage field*year observations (10,048ha) across eight NY dairies. For each observation, N balances (N supply - N removal) and N removal/N supply were calculated based on land-grant university (LGU) guidelines and farm management data. A green operational outcomes domain (GOOD) was defined, and a series of complementary graphical tools and numerical indicators were created to identify opportunities for N management refinement over time. RESULTS AND CONCLUSIONSFeasible outcome values for NUE indicators in the GOOD framework were established at a 50% minimum N removal/N supply and a 159kgN ha-1 maximum tolerable available N balance. Feasible values were in partial agreement with previous literature, did not constrain P-based manure applications, and identified fields with large N balances and low efficiencies in the context of adaptive N management. Considerable farm-to-farm differences existed, with 66% of field*year observations meeting the GOOD feasible values and 34% displaying opportunities for refinement. The strategies with largest potential for enhancing N management included reducing N inputs and evaluating non-N yield barriers (e.g. drainage, pests) for fields with low yields and high balances, increasing manure N utilization efficiency (with spring injection or incorporation), and crediting N contributions from sod. SIGNIFICANCEThe current work proposes a practical end-of-season evaluation framework for N management in corn silage that is easy to scale across NY dairies to facilitate implementation of the NY adaptive N management process. The framework also allows farmers to assess current practices and identify opportunities for management refinement over time. Enhancing NUE in corn silage should result in financial benefits for farms and reduced N losses to prevent water quality impairment and/or direct or indirect nitrous oxide emissions that contribute to global warming.

The Application of Digital-Genomic Tools to Improve Productivity and Profitability in Smallholder Dairy Systems in sub-Saharan Africa

Abstract The dairy sector contributes 30% and 44% of the livestock-related agricultural GDP in Tanzania and Kenya, respectively. Despite this significant contribution, it is predominantly comprised smallholder farmers with few cows providing vital support in terms of food security, household income and employment for millions of farmers. Research aimed at enhancing productivity and sustainability in these smallholder dairy systems is crucial for rural development, increasing farm incomes, creating employment and supporting women and youth. However, a major challenge is the absence of a routine performance data collection system. Previous efforts to address this limitation often relied on methods from well-established dairy systems in developed countries which frequently failed to adapt effectively. Advances in mobile technology have prompted attempts to investigate alternative cost-effective and practical data recording systems in the smallholder dairy farming with a major focus on information and communications technology (ICT). Successful implementation of digital tools for data collection and synthesis to generate management information as feedback to farmers using ICT-based extension tools has led to increased productivity and household income. Additionally, the use of genomic information allows for genetic evaluation with minimal pedigree information and supports the initiation of breed improvement programs for increased productivity. Information © The Authors 2024

Feasibility study of a grid-connected PV/wind hybrid energy system for an urban dairy farm

This study evaluates the energy efficiency of an urban dairy farm in Tlemcen, Algeria, by assessing the feasibility of a grid-connected photovoltaic (PV)/wind hybrid energy system. Using HOMER and MATLAB software, the study explores the potential for replacing the farm's existing energy systems with a hybrid system integrated into a low-voltage electrical grid. The HOMER software determined the configuration that resulted in the lowest net present cost, energy cost in kWh, greenhouse gas emission mitigation, and renewable fraction (RF). The selected specifications of the renewable energy (RE) system components, power rates, and costs are based on the local market. The results indicate a net current cost of $106,117.90 and a levelized cost of energy of $0.0959/kWh, with a reduction in CO2 emissions by 594 kg/day. The system delivers 98 % RF with 4 kWh/m2/day medium solar radiation and 4 m/s wind speeds, and the ideal investment recovery takes 33 months. On the other hand, generation includes 933 kWh/year in grid buys and 42,488 kWh/year in sold-backs. The PV array generates 5457 kWh annually, the wind turbine produces 40,761 kWh/year, and an additional 939 kWh/year is purchased from the grid. Additionally, hybrid power systems in dairy farms reduce energy consumption by 90 % and increase milk production by 40 %, promoting sustainable agriculture. The findings highlight the importance of adopting RE systems in agricultural operations to achieve both economic and environmental sustainability.

Evaluation of forage resources under poorly drained soils for dairy systems

Alfalfa is crucial for dairy farms, but its potential production and persistence can be hindered by waterlogging, poorly drained soils, and high-water tables. The objectives of this study were (a) to evaluate herbage mas and quality of different forage species on poorly drained soils, and (b) to evaluate root biomass accumulation and their impacts on soil physical properties. The study was conducted in Santa Fe, Argentina, on an Aquic Argiudoll. Four treatments were established in March 2017: Alfalfa (control), Fescue, Annual (Ryegrass and Sorghum rotation regime), and Mixture (a mixture of Brome, Chicory, Red clover, and White clover). Aboveground herbage mass and nutritive quality were analyzed frequently, while roots and soil samples were collected after 2 years for further analysis. Root biomass was significantly higher (p < 0.05) in Annual and Mixture pastures compared to Alfalfa and Fescue. Lower root biomass in Alfalfa was attributed to temporary waterlogging and low plant density. Fescue exhibited reduced root biomass due to higher bulk density and lower soil porosity. Soil bulk density was lowest in Mixture, and no significant differences in soil penetration resistance were found among treatments (p > 0.05). There are alternatives to alfalfa with high production and quality that ensure a good economic return to farmers. The choice of forages for its root biomass accumulation has effects on the physics of the soil that ultimately modify the water dynamics. These findings have implications for sustainable forage management strategies, particularly in areas prone to waterlogging and poorly drained soils.

Anti-breast cancer effects of dairy protein active peptides, dairy products, and dairy protein-based nanoparticles.

Breast cancer is the most frequently diagnosed and fatal cancer among women worldwide. Dairy protein-derived peptides and dairy products are important parts of the daily human diet and have shown promising activities in suppressing the proliferation, migration, and invasion of breast cancer cells, both in vitro and in vivo. Most of the review literature employs meta-analysis methods to explore the association between dairy intake and breast cancer risk. However, there is a lack of comprehensive summary regarding the anti-breast cancer properties of dairy protein-derived peptides, dairy products, and dairy protein-based nanoparticles as well as their underlying mechanisms of action. Therefore, the present study discussed the breast cancer inhibitory effects and mechanisms of active peptides derived from various dairy protein sources. Additionally, the characteristics, anti-breast cancer activities and active components of several types of dairy products, including fermented milk, yogurt and cheeses, were summarized. Furthermore, the preparation methods and therapeutic effects of various dairy protein-containing nanoparticle delivery systems for breast cancer therapy were briefly described. Lastly, this work also provided an overview of what is currently known about the anti-breast cancer effects of dairy products in clinical studies. Our review will be of interest to the development of natural anticancer drugs.

Use of CLEANED to Assess the Productive, Environmental, and Economic Impact of Dairy Farms in the Peruvian Amazon.

Dairy farms in developing countries are key to fighting hunger and poverty. However, their environmental and economic impact in the tropical region of Peru has been scarcely studied. The CLEANED tool, developed by the Alliance of Bioversity International and the International Center for Tropical Agriculture, allows us to assess the productive situation and the environmental and economic impact of different dairy systems. The objective of the study was to use the CLEANED tool to evaluate the production, environmental, and economic impacts of extensive and semi-intensive dairy systems in the tropical region of Peru. Data from twelve dairy farms (six extensive and six semi-intensive systems), in two seasons (rainy and dry) were recorded using semi-structured surveys. The required area (ha/year), production (L milk/ha/year), environmental impact (water use in m3/product), and methane (CH4) and nitrous oxide (N2O) emissions in kg CO2eq/kg fat- and protein-corrected milk (FPCM) were estimated, and the economic analysis was performed for each livestock system. Results showed that the required area was of 28.9 and 32.6 ha, milk yield was 382 and 1254 L/ha/year, water use was 0.59 and 0.29 m3/kg FPCM, CH4 emissions were 1.7 and 1.0 kg CO2eq/kg FPCM, and N2O emissions were 0.22 and 0.17 kg CO2eq/kg FPCM, for the extensive and semi-intensive systems, respectively. The study revealed significant positive differences in semi-intensive livestock systems, including increased productivity, the reduced intensity of CH4 and N2O emissions, and greater profitability.