Effect of management system and dietary seasonal variability on environmental efficiency and human net food supply of mountain dairy farming systems

Mountain dairy cattle farming systems are pivotal for the economy, as well as for social and environmental aspects. They significantly contribute to rural development, which is currently strongly prioritized in the common European Union agricultural policy; at the same time, they are also increasingly criticized for having a relatively high environmental impact (such as greenhouse gas emissions) per kilogram of product. Consequently, the aim of this study was to assess and compare the environmental efficiency of 2 common alpine dairy farming systems, with a focus on the effects of grazing, considering the seasonal variability in feeding at the individual cow level and farm management over a 3-yr period. This study focuses on alpine farming systems, but can also be considered to effectively represent other topographically disadvantaged mountain areas. We compared an intensively managed and globally dominating production system (high-input) aimed at high milk yield through relatively intensive feeding and the use of the high-yielding dual-purpose Simmental cattle permanently confined in stables, with a forage-based production system (low-input) based on seasonal grazing and the use of the autochthonous dual-purpose breed Tyrolean Grey. For the present analysis, we used a dataset with information on feed intake and diet composition, as well as animal productivity at the individual cow level and farm management data based on multiyear data recording. We quantified 4 impact categories for 3 consecutive years: global warming potential (GWP100), acidification potential (AP), marine eutrophication potential (MEP), and land use (LU; in square meters per year and eco points [Pt], with the latter additionally considering the soil quality index). In addition to being attributed to 1 kg of fat- and protein-corrected milk (FPCM), these impact categories were also related to 1 m2 of on-farm area. Due to limited agronomic options beyond forage production and pasture use in alpine regions, net provision of protein was calculated for both farming systems to assess food supply and quantify the respective food-feed competition. Overall, the low-input farming system had greater environmental efficiency in terms of MEP per kilogram of FPCM, as well as MEP and AP per square meter than the high-input system. Land use was found to be consistently higher for the high-input than for the low-input system, the GWP100 per kilogram of FPCM was lower for the high-input system. Additionally, pasture access had a significant effect on the reduction of environmental impacts. Lastly, the net protein provision was slightly negative for the high-input system and marginally positive for the low-input system, indicating a lower food-feed competition for the latter. Future studies should also address the social and economic aspects of the farming systems in order to offer a comprehensive overview of the 3 key factors necessary for achieving more sustainable farming systems, particularly in disadvantaged marginal regions such as mountain areas.

Assessing the eco-efficiency of milk production systems using water-energy-labor-food nexus

Globally, massive resource inputs and undesired outputs hindered the further development of the dairy industry. This study proposed a method applying data envelopment analysis to the water-energy-labor-food nexus to assess the eco-efficiency of the milk production system (MEE) from a systemic perspective. Using national statistics on scale farms for the period 2014-2021, we illustrated the effects of scale and intensification on MEE in China. In the study period, the production cost increased by 23 % and milk production rose by 30 % at the same time. Despite the increases in both water and energy inputs, the rise in milk production weakened the resource burdens and thus lifted MEE by 24 %. The resource investment pattern shifted from water- and labor-oriented to energy-oriented. Under current conditions, production technology and system management were at higher superiority to advance than farm scale, while mechanization and on-farm clean energy production are the keys to further lifting MEE.

Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP100) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH4 emissions) as an exemplar to compare various climatatic impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

Protein quality as a complementary functional unit in life cycle assessment (LCA)

Goal and theoretical commentary

A number of recent life cycle assessment (LCA) studies have concluded that animal-sourced foods should be restricted-or even avoided-within the human diet due to their relatively high environmental impacts (particularly those from ruminants) compared with other protein-rich foods (mainly protein-rich plant foods). From a nutritional point of view, however, issues such as broad nutrient bioavailability, amino acid balances, digestibility and even non-protein nutrient density (e.g., micronutrients) need to be accounted for before making such recommendations to the global population. This is especially important given the contribution of animal sourced foods to nutrient adequacy in the global South and vulnerable populations of high-income countries (e.g., children, women of reproductive age and elderly). Often, however, LCAs simplify this reality by using 'protein' as a functional unit in their models and basing their analyses on generic nutritional requirements. Even if a 'nutritional functional unit' (nFU) is utilised, it is unlikely to consider the complexities of amino acid composition and subsequent protein accretion. The discussion herein focuses on nutritional LCA (nLCA), particularly on the usefulness of nFUs such as 'protein,' and whether protein quality should be considered when adopting the nutrient as an (n)FU. Further, a novel and informative case study is provided to demonstrate the strengths and weaknesses of protein-quality adjustment.

Case study methods

To complement current discussions, we present an exploratory virtual experiment to determine how Digestible Indispensable Amino Acid Scores (DIAAS) might play a role in nLCA development by correcting for amino acid quality and digestibility. DIAAS is a scoring mechanism which considers the limiting indispensable amino acids (IAAs) within an IAA balance of a given food (or meal) and provides a percentage contribution relative to recommended daily intakes for IAA and subsequent protein anabolism; for clarity, we focus only on single food items (4 × animal-based products and 4 × plant-based products) in the current case exemplar. Further, we take beef as a sensitivity analysis example (which we particularly recommend when considering IAA complementarity at the meal-level) to elucidate how various cuts of the same intermediary product could affect the interpretation of nLCA results of the end-product(s).

Recommendations

First, we provide a list of suggestions which are intended to (a) assist with deciding whether protein-quality correction is necessary for a specific research question and (b) acknowledge additional uncertainties by providing mitigating opportunities to avoid misinterpretation (or worse, dis-interpretation) of protein-focused nLCA studies. We conclude that as relevant (primary) data availability from supply chain 'gatekeepers' (e.g., international agri-food distributors and processors) becomes more prevalent, detailed consideration of IAA provision of contrasting protein sources needs to be acknowledged-ideally quantitatively with DIAAS being one example-in nLCA studies utilising protein as a nFU. We also contend that future nLCA studies should discuss the complementarity of amino acid balances at the meal-level, as a minimum, rather than the product level when assessing protein metabolic responses of consumers. Additionally, a broader set of nutrients should ideally be included when evaluating "protein-rich foods" which provide nutrients that extend beyond amino acids, which is of particular importance when exploring dietary-level nLCA.