• Energy Research

Abstract Purpose Life cycle assessment studies on smallholder farms in tropical regions generally use data that is collected at one moment in time, which could hamper assessment of the exact situation. We assessed seasonal differences in greenhouse gas emissions (GHGEs) from Indonesian dairy farms by means of longitudinal observations and evaluated the implications of number of farm visits on the variance of the estimated GHGE per kg milk (GHGEI) for a single farm, and the population mean. Methods An LCA study was done on 32 smallholder dairy farms in the Lembang district area, West Java, Indonesia. Farm visits (FVs) were performed every 2 months throughout 1 year: FV1–FV3 (rainy season) and FV4–FV6 (dry season). GHGEs were assessed for all processes up to the farm-gate, including upstream processes (production and transportation of feed, fertiliser, fuel and electricity) and on-farm processes (keeping animals, manure management and forage cultivation). We compared means of GHGE per unit of fat-and-protein-corrected milk (FPCM) produced in the rainy and the dry season. We evaluated the implication of number of farm visits on the variance of the estimated GHGEI, and on the variance of GHGE from different processes. Results and discussion GHGEI was higher in the rainy (1.32 kg CO2-eq kg−1 FPCM) than in the dry (0.91 kg CO2-eq kg−1 FPCM) season (P < 0.05). The between farm variance was 0.025 kg CO2-eq kg−1 FPCM in both seasons. The within farm variance in the estimate for the single farm mean decreased from 0.69 (1 visit) to 0.027 (26 visits) kg CO2-eq kg−1 FPCM (rainy season), and from 0.32 to 0.012 kg CO2-eq kg−1 FPCM (dry season). The within farm variance in the estimate for the population mean was 0.02 (rainy) and 0.01 (dry) kg CO2-eq kg−1 FPCM (1 visit), and decreased with an increase in farm visits. Forage cultivation was the main source of between farm variance, enteric fermentation the main source of within farm variance. Conclusions The estimated GHGEI was significantly higher in the rainy than in the dry season. The main contribution to variability in GHGEI is due to variation between observations from visits to the same farm. This source of variability can be reduced by increasing the number of visits per farm. Estimates for variation within and between farms enable a more informed decision about the data collection procedure.

Sustainable livestock production is important to ensure continuous availability of resources for future generations. Most smallholder livestock farming systems in developing countries have been perceived to be environmentally, socially and economically unsustainable. Farming with livestock that is robust and adaptable to harsh environments is important in developing countries especially in semi-arid and arid environments. This review discusses the different sheep farming systems employed by smallholder farmers and associated sustainability problems facing them. The review also gives an overview of sustainability indicators and limitations to the sustainability for the different smallholder sheep production systems in South Africa. It is argued that genetic diversity is important for sustainability and needs to be maintained in sheep for sustainable production and reproduction performance. The application of traditional breeding and genomics to ensure sustainable production is explored. Animal breeding approaches, specifically genomics can be applied to improve areas of environmental sustainability of smallholder sheep farming systems but must be targeted to the specific production environments, challenges, and opportunities of smallholder production. The genetic traits important for sustainability, the role of genomics in improving these traits and linking these genetic traits to different farming systems in South Africa are discussed.

Although livestock production accounts for a sizeable share of global greenhouse gas emissions, numerous technical options have been identified to mitigate these emissions. In this review, a subset of these options, which have proven to be effective, are discussed. These include measures to reduce CH4 emissions from enteric fermentation by ruminants, the largest single emission source from the global livestock sector, and for reducing CH4 and N2O emissions from manure. A unique feature of this review is the high level of attention given to interactions between mitigation options and productivity. Among the feed supplement options for lowering enteric emissions, dietary lipids, nitrates and ionophores are identified as the most effective. Forage quality, feed processing and precision feeding have the best prospects among the various available feed and feed management measures. With regard to manure, dietary measures that reduce the amount of N excreted (e.g. better matching of dietary protein to animal needs), shift N excretion from urine to faeces (e.g. tannin inclusion at low levels) and reduce the amount of fermentable organic matter excreted are recommended. Among the many 'end-of-pipe' measures available for manure management, approaches that capture and/or process CH4 emissions during storage (e.g. anaerobic digestion, biofiltration, composting), as well as subsurface injection of manure, are among the most encouraging options flagged in this section of the review. The importance of a multiple gas perspective is critical when assessing mitigation potentials, because most of the options reviewed show strong interactions among sources of greenhouse gas (GHG) emissions. The paper reviews current knowledge on potential pollution swapping, whereby the reduction of one GHG or emission source leads to unintended increases in another.

Purpose: Life cycle assessment studies on smallholder farms in tropical regions generally use data that is collected at one moment in time, which could hamper assessment of the exact situation. We assessed seasonal differences in greenhouse gas emissions (GHGEs) from Indonesian dairy farms by means of longitudinal observations and evaluated the implications of number of farm visits on the variance of the estimated GHGE per kg milk (GHGEI) for a single farm, and the population mean. Methods: An LCA study was done on 32 smallholder dairy farms in the Lembang district area, West Java, Indonesia. Farm visits (FVs) were performed every 2 months throughout 1 year: FV1–FV3 (rainy season) and FV4–FV6 (dry season). GHGEs were assessed for all processes up to the farm-gate, including upstream processes (production and transportation of feed, fertiliser, fuel and electricity) and on-farm processes (keeping animals, manure management and forage cultivation). We compared means of GHGE per unit of fat-and-protein-corrected milk (FPCM) produced in the rainy and the dry season. We evaluated the implication of number of farm visits on the variance of the estimated GHGEI, and on the variance of GHGE from different processes. Results and discussion: GHGEI was higher in the rainy (1.32 kg CO2-eq kg−1 FPCM) than in the dry (0.91 kg CO2-eq kg−1 FPCM) season (P < 0.05). The between farm variance was 0.025 kg CO2-eq kg−1 FPCM in both seasons. The within farm variance in the estimate for the single farm mean decreased from 0.69 (1 visit) to 0.027 (26 visits) kg CO2-eq kg−1 FPCM (rainy season), and from 0.32 to 0.012 kg CO2-eq kg−1 FPCM (dry season). The within farm variance in the estimate for the population mean was 0.02 (rainy) and 0.01 (dry) kg CO2-eq kg−1 FPCM (1 visit), and decreased with an increase in farm visits. Forage cultivation was the main source of between farm variance, enteric fermentation the main source of within farm variance. Conclusions: The estimated GHGEI was significantly higher in the rainy than in the dry season. The main contribution to variability in GHGEI is due to variation between observations from visits to the same farm. This source of variability can be reduced by increasing the number of visits per farm. Estimates for variation within and between farms enable a more informed decision about the data collection procedure.

Vanuit de samenleving komt steeds nadrukkelijker de vraag naar zogenaamde collectieve functies van het platteland: natuur, landschap, openheid, rust en stilte, waterberging en waterwinning.

Two experiments, experiment 1 with six steers in a 3 × 3 Latin-square design and experiment 2 with four wether sheep in a cross-over design, were conducted to study the effect of species and ammonia treatment on intake and utilization of the energy of untreated wheat straw. Treatments were: (1) untreated wheat straw offered ad libitum on top of a basal diet (B) consisting of hay (0·25) and grass pellets (0·75) (UWS), (2) ammoniated wheat straw offered ad libitum plus B (AWS) and (3) ammoniated wheat straw offered at a restricted level plus B (AWS-). B was offered as a maintenance diet for both species and AWS- was only studied in steers. Voluntary intake of AWS zvas higher than that of UWS. No significant differences emerged between whole rations UWS and AWS with regard to energy digestion (ED), energy metabolizability (ρ = metabolizable energy (ME) I gross energy (GE)) and losses of digestible energy (DE) in urine and methane (average 187 J/KJ DE), but the efficiency of utilization of ME for growth (kg) was significantly higher for AWS than for UWS. ED and ρ of the straw part of the ration was significantly higher for AWS than for UWS. AWS- and AWS did not differ significantly with regard to ED, ρ and DE losses in methane and urine. Steers had a higher intake per kg0·75 per day than wether sheep. Across species, digestible energy intake (DEI) of the whole ad libitum fed diets was related to live weight (M)0·946 (s.e. of exponent 0·0152). ED and ρ of the straw part of the rations did not differ significantly between species, but steers had a significantly higher ED and ρ of β than wether sheep. Steers excreted a significantly lower proportion of DE in urine and a significantly higher proportion of DE in methane than did wethers. Total energy losses in urine and methane, however, did not differ between species.

CONTEXT: The livestock sector in Sub-Saharan Africa (SSA) is under increasing pressure to define its role in jointly addressing food security and climate change. Climate-smart agriculture (CSA) has been widely leveraged as an approach to achieving both food security and climate change outcomes through suites of interventions that maximize synergies and reduce tradeoffs among three pillars: productivity, climate change resilience, and climate change mitigation. However, operationalization of the CSA approach in the livestock sector is hindered by a lack of clarity around what the pillars mean for livestock systems, given their fundamental attributes compared to crops and the spatial and temporal dimensions of these attributes. A conceptual framework is also lacking for assessing and comparing the potential CSA synergies and tradeoffs that different livestock systems and interventions may generate. OBJECTIVE: In this paper we aim to offer guidance on the operationalization of the CSA approach in the livestock sector. METHODS: We draw on a literature review to explore the essential attributes of livestock systems in SSA as they relate to CSA objectives over different temporal and spatial scales. Based on this review, we propose a practical and flexible framework for assessing and comparing the synergies and tradeoffs that different livestock systems may generate among food security and climate change objectives over different spatial and temporal scales. The framework consists of four elements: CSA pillars, spatial-temporal scales, CSA objectives mapped to each spatial-temporal scale, and indicator guidance. Using farm survey data and national statistics, an illustrative application of the framework to two dairy farms in Rwanda is presented and discussed. RESULTS AND CONCLUSIONS: The illustrative application demonstrates how the framework can be used to identify important, spatial-temporal CSA synergies and tradeoffs that otherwise may go unrecognized. Additional applications are needed to assess the utility, practicality, and potential of the framework to guide CSA operationalization in the livestock sector in SSA. SIGNIFICANCE: Maximizing synergies and reducing tradeoffs among food security and climate change outcomes in the livestock sector is critical for a sustainable food future. With an emphasis on flexibility for tailoring to specific development contexts and compatibility with varying levels of data availability and methodological complexity, the framework is intended to support diverse stakeholders involved in policy and development seeking to identify those livestock systems that contribute most to food security and climate change objectives over time and space.

Several studies support the general conclusion that plant-based diets have a lower environmental impact than animal-based diets. These studies, however, do not account for the nutritional quality of diets. The main objective of our study, therefore, was to explore if accounting for nutritional quality affects the comparison of the environmental impacts of human diets varying in their percentage of animal-source food products (ASFP). We also explored whether meals or daily diets are equally suitable to compare environmental impacts of diets. Fifty peer-reviewed studies were found that examined the environmental impact of diets, generally using life cycle assessment (LCA). Only 12 of these studies were reviewed, based on five criteria: study contains more than one scenario; diet scenarios vary in their percentage of ASFP; the weight of each food product was provided; the study assessed global warming potential and/or land use; diet scenarios are not designed for specific (health) groups. For each diet described in the reviewed studies, we quantified the daily intake of nine qualifying and three disqualifying nutrients. Global warming potential and land use, as provided by the reviewed studies, were expressed in four ways: per day, per daily protein intake capped to the recommended intake level of 57 g; per daily protein intake uncapped; and per NRD9.3 (i.e. a composite nutrient score of a diet). We concluded that the nutrient intake resulting from a meal cannot be used to assess the nutritional quality of a daily diet and, hence, the environmental impact of meals cannot be compared to that of daily diets. Studies on meals were therefore excluded from further analysis. Our results further show that daily diets that had higher percentages of ASFP were associated with higher (excess) intakes of total protein and lower values of NRD9.3. Diets that had higher percentages of ASFP were associated with higher GWPs and LU's per gram protein capped and per unit NRD9.3. Without capping protein to the recommended intake level, GWP and LU per gram of protein were generally lower for diets that had higher percentages of ASFP. Without capping, diets with higher percentages of ASFP are credited for overconsumption of protein. Since overconsumption of protein does not benefit health, we recommend capping to the recommended intake level. The effect of using NRD9.3 rather than day as functional unit was small for GWP. For LU we found no effect. When using NRD9.3 as functional unit, it must be considered that this functional unit requires more data than day or protein. Our analysis is based on a limited number of studies. Although initially a substantial number of studies were found, many of these were excluded because insufficient data were provided about diet composition, only one diet scenario was assessed, or because the studies assessed the environmental impact of meals rather than of diets. We found mainly Western-oriented diets, often designed by the researchers and not representative for actual consumption. For further research on the environmental impact of diets, we therefore recommend analysis on representative daily diets.

De maatschappelijke opbrengst lijkt echter enige malen hoger te zijn dan de landbouwkundige kosten (tabel 3). Zowel boer als burger lijkt derhalve baat te kunnen hebben bij multifunctionele landgebruik.

Breeding is a promising greenhouse gas (GHG) mitigation option for the dairy sector that offers potential permanent and cumulative effects. However, there is limited understanding of how genetic traits affect GHG emissions from the dairy production chain and how breeding indices could be used to find a balance between GHG emissions and farm profit. Using a typical Chinese dairy farm as a case study, we developed a novel method to address these gaps. The farm comprised of 1523 Holstein-Friesian dairy cows and 1429 young stock. The average milk yield at the farm was 11,533 kg per cow per year. Life cycle assessment was combined with an existing bio-economic model to determine the emission intensity values (IV) of six genetic traits: milk yield, protein yield, fat yield, calving interval, productive life, and incidence of clinical mastitis. The IVs and economic values of the traits were used to form different breeding indices, of which the economic and environmental consequences were assessed. Results showed that for the next generation, breeding animals with optimal indices could reduce carbon dioxide equivalents per ton of fat-and-protein-corrected milk by six to 10 kg, while increasing profitability by 822 to 1355 Chinese Yuan per cow unit. Different indices can balance farm profit and GHG emissions to different degrees. However, the indices with higher profit showed less potential in reducing GHG emissions. This study provides insights into how breeding strategies could contribute to GHG mitigation in the dairy sector.