EVALUATION AND CHARACTERIZATION OF DIETARY STRATEGIES ON ENVIRONMENTAL SUSTAINABILITY OF DAIRY COW MILK PRODUCTION

The livestock sector is facing different challenges, and the demand for higher sustainability seems to be one of the most urgent. This PhD project debated, in particular, the environmental impacts related to ruminant nutrition, focusing on dairy cows, since nutrition is bound tightly to two of the most important sources of impact: enteric CH4 emission and land use change (LUC). Enteric CH4 emission from ruminants represents 29-38% of the total (anthropic + natural) emission of this powerful (21 CO2 equivalent) greenhouse gas. The production of CH4 is a physiological process used by ruminants to discharge the [H] resulting from rumen fermentation. Different strategies can be implemented to mitigate this impact, and they can be roughly grouped into three main categories: animal and feed management, diet formulation, and rumen manipulation. The second issue investigated in the project is the high reliance of European livestock on soybean meal as a protein source for diet formulation. A total of 30 million tonnes of this feedstuff was imported into Europe in 2020. The main countries of origin are in South America (65% of total import), where 20% of soybean meal production was linked with deforestation (and consequently LUC) in the last decades. Clearing these areas means loss of carbon sink and emission of CO2 in the atmosphere. Other feedstuffs, like grain legumes, oilseed meals alternative to soybean, and high quality forages could be considered to provide protein feed with a lower environmental cost. In this context, the PhD project was developed as follows:  To address the problem of CH4 emission, plant essential oils, as modulators of rumen fermentation, were evaluated (Experiment 1). Furthermore, the effect on CH4 emission of different forages in the diet of dairy cows was investigated (Experiment 2). For validation of mitigation strategies and inventory computation of emissions at a national scale, country-specific equations to quantify CH4 emission were evaluated (Experiment 3).  To address the problem of soybean meal environmental impact, soybean silage and responsible soybean meal (not connected with land use change) were evaluated as protein source alternatives to soybean meal in the diet of lactating cows (Experiments 4 and 5). Enteric methane direct emission In the first experiment, Achille moschata essential oil and its main pure components, namely bornyl acetate, camphor, and eucalyptol, were evaluated in an in vitro experiment. The trial comprehended a short-term in vitro incubation (48 h), with 200 mg of compound per L of inoculum, and a long-term one by continuous fermenter (9 d), with 100 mg/L for each compound. In the first incubation, no differences due to the treatments were found for in vitro gas production (on average, 30.4 mL/200 mg DM, P = 0.772 at 24 h and 45.2 mL/200 mg DM, P = 0.545 at 48 h). Camphor and eucalyptol reduced CH4 production when expressed as % of gas production at 48 h (P < 0.05): -7.4% and -7% compared to control. In the second incubation, CH4 was reduced by eucalyptol (-18%, P < 0.05). Regarding volatile fatty acids, the main effects were a decrease of total production for camphor (-19.5%, P < 0.05) and an increase in acetate production at 9 d with bornyl acetate and camphor (+13% and 7.6%, respectively, P < 0.05) compared to control. Total protozoa count was increased compared to the control (on average: +37%, P = 0.006, at 48 h and +48%, P < 0.001, at 9 d) with all the pure compounds tested. In the short-term incubation, all the treatments reduced Bacteroidetes (30.3%, on average, vs. 37.1% of control, P = 0.014) and Firmicutes (26.3%, on average, vs. 30.7% of control, P = 0.031) abundances but increased Proteobacteria (36.0%, on average, vs. 22.5% of control, P = 0.014). In the long-term incubation, eucalyptol increased the genus Ruminococcus abundance (2.60% vs. 1.18% of control, P = 0.011). An adaptation at long time incubation was observed. In particular, considering eucalyptol addition at 9 d incubation, VFA production was reduced (26.8 vs. 33.3 mmol of control, P < 0.05) contrary to the 48 h incubation (P = 0.189). Furthermore, the treatments affected protozoa genera relative abundances at 24 h (increased abundance for Entodinium with all the treatments, P < 0.001, and reduced for Diplodinium, P = 0.001); at 9 d, instead, protozoa genera relative abundances were not affected by the treatment. The additives tested showed potential in reducing CH4 production without compromising the overall fermentation efficiency. A meta-analysis (Experiment 2) investigated the effects on lactation performance and enteric CH4 of the main forage included in the diet. In the dataset, composed of in vivo experiments, four main forage bases were evaluated: corn silage, alfalfa silage, grass silage, and green forage. Cows fed corn, and alfalfa silages had the highest DMI (21.9 and 22.0 kg/d, P < 0.05) and milk yield (29.7 and 30.4 kg/d, P < 0.05). On the opposite, NDF digestibility was highest for grass silage and green forage (67.6% and 73.1%, P < 0.05) than corn and alfalfa silages (51.8% on average). CH4 production was lower (P < 0.05) for green forage (332 g/d) than the silage diets (on average 438 g/d). Instead, corn silage and alfalfa silage gave the lowest CH4 per kg of milk yield (14.2 g/kg and 14.9 g/kg, P < 0.05). Considering CH4 per kg of DMI, the only difference was between corn silage and grass silage (19.7 g/kg vs. 21.3 g/kg respectively for corn and grass silage, P < 0.05). Finally, prediction models for CH4 production were obtained through a step-wise multi regression. In particular, the models for the prediction of: CH4 in g/d (CH4 = - 65.3(±63.7) + 11.6(±1.67) × DMI - 4.47(±1.09) × CP - 0.86(±0.33) × Starch + 2.62(±0.78) × OM digestibility + 30.8(±9.45) × Milk fat) and for CH4 in g/kg of milk yield (CH4/milk yield = - 55.5(±20.1) - 0.37(±0.13) × DMI + 0.18(±0.05) × Total forage inclusion on diet DM - 0.10(±0.04) × Inclusion of the main forage on diet DM + 0.48(±0.21) × OM + 0.14(±0.06) × NDF + 1.98(±0.86) × Milk fat +4.34(±1.66) × Milk protein) showed high precision (R2 = 95.4% and 88.6%, respectively), but the best AIC value (320) was found for the model predicting CH4 in g/kg DMI: CH4/kg DMI = 6.16(±3.89) - 0.36(±0.03) × CP + 0.12(±0.05) ×OM digestibility + 3.77(±0.56) × Milk fat - 3.94(±1.07) × Milk fat yield. A dataset (66 observations in total) of three in vivo experiments conducted in Italy on lactating cows in respiration chambers was built to evaluate IPCC Tier 2 equations to estimate enteric CH4 production (Experiment 3). In the dataset, the CH4 conversion factor (conversion of gross energy intake into enteric CH4 energy) was lowest for a diet based on grass and alfalfa silages (5.05%, P < 0.05), while the others values ranged between 5.41 and 5.92%. On average, energy digestibility was 69.0% across the dataset, but the diet based on hays had a lower value (64.8%, P < 0.05). The IPCC (2019) Tier 2 (conversion factor = 5.7% or 6.1% for diet with NDF concentration < 35% or >35%, respectively; digestible energy = 70%) gave, on average, a value of CH4 production not statistically different from the ones measured in vivo (382 vs. 388 g/d in vivo, P > 0.05). The IPCC (2006) Tier 2 (conversion factor = 6.5%, digestible energy = 70%) over-predicted CH4 emission (428 vs. 388 g/d in vivo, P < 0.05; μ = -1.05). The most precise models were the two considering digestible energy equal to 70% and average values of conversion factor for IPCC (2006) and IPCC (2019) (R = 0.630); the most accurate models was the one considering a conversion factor equal to 5.7% and energy digestibility measured in vivo (Cb = 0.995). Overall, the best performance among the predicting models tested was for the one based on a conversion factor equal to 5.7% and energy digestibility of 70% (CCC = 0.579 and RMPSE = 9.10%). Use of alternative protein source to conventional soybean meal The dietary inclusion of soybean silage in partial replacement of soybean meal for dairy cows was evaluated in vivo in lactating cow diets (Experiment 4). Cows were fed two diets, one with 12.4% of DM from soybean silage in substitution of 35% of the soybean meal of the control diet. The treatment did not affect DMI and milk yield (on average, 23.7 kg/d, P = 0.659, and 33.0 kg/d, P = 0.377, respectively). Cows fed the soybean silage diet had lower milk protein concentration (3.43% vs. 3.55% of the control, P < 0.001) and higher milk urea (30.5 vs. 28.7 mg/dL, P = 0.002). The soybean silage had lower nutrient digestibility than the control: DMD 65.2% vs. 68.6%, OMD 66.4% vs. 69.8%, NDFD 31.5% vs. 38.8% (respectively for soybean silage and control diet; P < 0.001 for all of them). Regarding N balance, cows fed soybean silage excreted more nitrogen in the urines (32.3 % of N intake vs. 28.9%, P = 0.005) and less in the milk (31.3% vs. 32.7%, P =0.003) than the control. When used as a protein source alternative to soybean meal, soybean silage sustained comparable milk production, but NDF digestibility and N use efficiency should be improved. The environmental impact of the use of soybean silage in comparison to a control diet with soybean meal as the main protein source was evaluated through an LCA approach (Experiment 5). In addition, two scenarios were included in the study, considering the two diets mentioned before, but with soybean meal not connected to LUC (responsible soybean meal). Regarding the single forages, soybean silage had higher global warming potential than alfalfa hay (477 vs. 201 kg CO2eq/ton DM), also when this was expressed per tonnes of protein production (2439 and 1034 kg CO2eq/ton CP, respectively), probably due to the lower contribution of the cultivation phase for alfalfa, being a multi-year crop. The scenario with soybean silage reduced the global warming potential per kg of fat and protein corrected milk (1.17 kg CO2eq) compared to the control (1.38 kg CO2eq). Responsible soybean meal reduced the global warming potential per kg of fat and protein corrected milk (1.13 kg CO2eq/kg vs. 1.38 of the scenario with the control diet). Overall, the best result per kg of fat and protein corrected milk was obtained when responsible soybean meal and soybean silage were used in combination (1.01 kg CO2eq). Also, when global warming potential was evaluated per daily fed TMR, the impact was lowest for the scenario with responsible soybean meal (13.4 kg CO2eq/d) due to the lower contribution of soybean meal to the total impact (11% vs. 43% of the control). Therefore, the two alternative protein sources tested should be preferred when considering environmental impact compared to conventional soybean meals.