An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg-1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg-1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg-1 FPCM and 0.006 kg N kg-1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

Rhizosphere engineering for soil carbon sequestration

The rhizosphere is the central hotspot of water and nutrient uptake by plants, rhizodeposition, microbial activities, and plant-soil-microbial interactions. The plasticity of plants offers possibilities to engineer the rhizosphere to mitigate climate change. We define rhizosphere engineering as targeted manipulation of plants, soil, microorganisms, and management to shift rhizosphere processes for specific aims [e.g., carbon (C) sequestration]. The rhizosphere components can be engineered by agronomic, physical, chemical, biological, and genomic approaches. These approaches increase plant productivity with a special focus on C inputs belowground, increase microbial necromass production, protect organic compounds and necromass by aggregation, and decrease C losses. Finally, we outline multifunctional options for rhizosphere engineering: how to boost C sequestration, increase soil health, and mitigate global change effects.

Normalized Difference Vegetation Index (NDVI) for soybean biomass and nutrient uptake estimation in response to production systems and fertilization strategies

The system fertilization approach emerged to improve nutrient use efficiency in croplands. This new fertilization concept aims at taking advantage of nutrient cycling within an agroecosystem to obtain maximum production from each nutrient unit. To monitor this effect, methodologies such as the Normalized Difference Vegetation Index (NDVI) are promising to evaluate plant biomass and nutrient content. We evaluated the use of NDVI as a predictor of shoot biomass, P and K uptake, and yield in soybean. Treatments consisted of two production systems [integrated crop-livestock system (ICLS) and cropping system (CS)] and two periods of phosphorus (P) and potassium (K) fertilization (crop fertilization—P and K applied at soybean sowing—and system fertilization—P and K applied in the pasture establishment). NDVI was evaluated weekly from the growth stage V2 up to growth stage R8, using the Greenseeker® canopy sensor. At the growth stages V4, V6, R2, and R4, plants were sampled after NDVI evaluation for chemical analysis. Soybean yield and K uptake were similar between production systems and fertilization strategies (P > 0.05). Soybean shoot biomass and P uptake were, respectively, 25.3% and 29.7% higher in ICLS compared to CS (P < 0.05). For NDVI, an interaction between the production system and days after sowing (P < 0.05) was observed. NDVI increased to 0.95 at 96 days after sowing in CS and to 0.92 at 92 days after sowing in ICLS. A significant relationship between NDVI and shoot biomass, and P and K uptake was observed (P < 0.05). Our results show that the vegetation index NDVI can be used for estimating shoot biomass and P and K uptake in the early growth stages of soybean crops, providing farmers with a new tool for evaluating the spatial variability of soybean growth and nutrition.

Economic Implications of a Protein Transition: Evidence From Walloon Beef and Dairy Farms

In Europe, cattle production is confronted with major challenges across all dimensions of sustainability, urging the need to promote environmentally friendly but also economically viable livestock systems. In addition, animal protein consumption greatly exceeds the dietary guidelines in most European countries. The protein transition, defined as the rebalancing between animal and alternative proteins in diets, is presented as a solution to mitigate the harmful effects of cattle production on the environment, but also as an opportunity to induce healthier diets. Yet, the implications of such a transition on current livestock farmers are still unclear. In this article, we investigate different factors associated with a protein transition (e.g., reduction of herd size, increased concentrate autonomy and increased share of pastures) and assess their implications for the economic performance of dairy and beef farmers in Wallonia, Belgium. In the dairy sector, we find that a reduction in herd size, a higher share of pastures and an increased concentrate autonomy are correlated with lower operating costs, resulting in higher margins. Therefore, a switch to more extensive grazing systems that rely on on-farm fodder production can entail economic benefits for farmers. In the beef sector, on the other hand, farm characteristics are uncorrelated with most economic indicators, but highly associated with subsidies. This suggests that changes in this sector will rather be induced by policy choices than by economic parameters.