Evaluation of a Model (RUMINANT) for Prediction of DMI and CH4 from Tropical Beef Cattle.

Simulation models represent a low-cost approach to evaluating agricultural systems. In the current study, the precision and accuracy of the RUMINANT model to predict dry matter intake (DMI) and methane emissions from beef cattle fed tropical diets (characteristic of Colombia) was assessed. Feed intake (DMI) and methane emissions were measured in Brahman steers housed in polytunnels and fed six forage diets. In addition, DMI and methane emissions were predicted by the RUMINANT model. The model's predictive capability was measured on the basis of precision: coefficients of variation (CV%) and determination (R2, percentage of variance accounted for by the model), and model efficiency (ME) and accuracy: the simulated/observed ratio (S/O ratio) and slope and mean bias (MB%). In addition, combined measurements of accuracy and precision were carried out by means of mean square prediction error (MSPE) and correlation correspondence coefficient (CCC) and their components. The predictive capability of the RUMINANT model to simulate DMI resulted as valuable for mean S/O ratio (1.07), MB% (2.23%), CV% (17%), R2 (0.886), ME (0.809), CCC (0.869). However, for methane emission simulations, the model substantially underestimated methane emissions (mean S/O ratio = 0.697, MB% = -30.5%), and ME and CCC were -0.431 and 0.485, respectively. In addition, a subset of data corresponding to diets with Leucaena was not observed to have a linear relationship between the observed and simulated values. It is suggested that this may be related to anti-methanogenic factors characteristic of Leucaena, which were not accounted for by the model. This study contributes to improving national inventories of greenhouse gases from the livestock of tropical countries.

The ÓMICAS alliance, an international research program on multi-omics for crop breeding optimization.

The OMICAS alliance is part of the Colombian government's Scientific Ecosystem, established between 2017-2018 to promote world-class research, technological advancement and improved competency of higher education across the nation. Since the program's kick-off, OMICAS has focused on consolidating and validating a multi-scale, multi-institutional, multi-disciplinary strategy and infrastructure to advance discoveries in plant science and the development of new technological solutions for improving agricultural productivity and sustainability. The strategy and methods described in this article, involve the characterization of different crop models, using high-throughput, real-time phenotyping technologies as well as experimental tissue characterization at different levels of the omics hierarchy and under contrasting conditions, to elucidate epigenome-, genome-, proteome- and metabolome-phenome relationships. The massive data sets are used to derive in-silico models, methods and tools to discover complex underlying structure-function associations, which are then carried over to the production of new germplasm with improved agricultural traits. Here, we describe OMICAS' R&D trans-disciplinary multi-project architecture, explain the overall strategy and methods for crop-breeding, recent progress and results, and the overarching challenges that lay ahead in the field.

Greenhouse gas emissions from cattle dung depositions in two Urochloa forage fields with contrasting biological nitrification inhibition (BNI) capacity.

Grazing-based production systems are a source of soil greenhouse gas (GHG) emissions triggered by excreta depositions. The adoption of Urochloa forages (formerly known as Brachiaria) with biological nitrification inhibition (BNI) capacity is a promising alternative to reduce nitrous oxide (N2O) emissions from excreta patches. However, how this forage affects methane (CH4) or carbon dioxide (CO2) emissions from excreta patches remains unclear. This study investigated the potential effect of soils under two Urochloa forages with contrasting BNI capacity on GHG emissions from cattle dung deposits. Additionally, the N2O and CH4 emission factors (EF) for cattle dung under tropical conditions were determined. Dung from cattle grazing star grass (without BNI) was deposited on both forage plots: Urochloa hybrid cv. Mulato and Urochloa humidicola cv. Tully, with a respectively low and high BNI capacity. Two trials were conducted for GHG monitoring using the static chamber technique. Soil and dung properties and GHG emissions were monitored in trial 1. In trial 2, water was added to simulate rainfall and evaluate GHG emissions under wetter conditions. Our results showed that beneath dung patches, the forage genotype influenced daily CO2 and cumulative CH4 emissions during the driest conditions. However, no significant effect of the forage genotype was found on mitigating N2O emissions from dung. We attribute the absence of a significant BNI effect on N2O emissions to the limited incorporation of dung-N into the soil and rhizosphere where the BNI effect occurs. The average N2O EFs was 0.14%, close to the IPCC 2019 uncertainty range (0.01-0.13% at 95% confidence level). Moreover, CH4 EFs per unit of volatile solid (VS) averaged 0.31 g CH4 kgVS-1, slightly lower than the 0.6 g CH4 kgVS-1 developed by the IPCC. This implies the need to invest in studies to develop more region-specific Tier 2 EFs, including farm-level studies with animals consuming Urochloa forages to consider the complete implications of forage selection on animal excreta based GHG emissions.

Corrigendum: The ÓMICAS alliance, an international research program on multi-omics for crop breeding optimization.

[This corrects the article DOI: 10.3389/fpls.2022.992663.].

Environmental impact of primary beef production chain in Colombia: Carbon footprint, non-renewable energy and land use using Life Cycle Assessment.

In Colombia, the beef production chain accounts for approximately 11.6 million cattle heads and annually produces 933 million kg of the beef carcass. There are no life cycle assessment (LCA) studies that have evaluated the environmental performance of Colombian beef systems. The present study aimed to estimate the carbon footprint (CF), non-renewable energy use, and land use of 251 cow-calf and 275 fattening farms in Colombia. The study also aimed to identify the main hotspots of adverse environmental impacts and propose possible mitigation options and their cost-effectiveness. The impact categories were estimated using the 2006 IPCC and the 2019 Refinement to 2006 IPCC guidelines, databases, and locally estimated emission factors. The functional units used were 1 kg fat and protein corrected milk (FPCM) and 1 kg live weight gain (LWG), leaving the farm gate. Three methods of allocating environmental burdens to meat and milk products were applied: economic, energy, and mass allocation. The adoption of improved pastures was considered a mitigation measure, and an economic assessment was performed to estimate the relative cost-effectiveness of its establishment. A principal component multivariate analysis and a Hierarchical Clustering on Principal Components were performed. The economic allocation method assigned a greater environmental burden to meat (83%), followed by energy content (80%) and mass production (73%). The largest sources of GHG emissions were enteric fermentation and manure deposited on pasture. Both cow-calf and fattening systems had a cluster of farms with better productivity, pasture and cattle management practices, and environmental performance. The CF for meat could be reduced by 33 to 56% for cow-calf and 21 to 25% for fattening farms, by adopting improved pastures. Therefore, our results suggest that GHG emissions can be reduced by adopting improved pastures, better agricultural management practices, efficient fertilizer usage, using the optimal stocking rate, and increasing productivity.

Nutritional Quality, Voluntary Intake and Enteric Methane Emissions of Diets Based on Novel Cayman Grass and Its Associations With Two Leucaena Shrub Legumes.

Methane (CH4) emissions from enteric fermentation in cattle are an important source of greenhouse gases, accounting for about 40% of all agricultural emissions. Diet quality plays a fundamental role in determining the magnitude of CH4 emissions. Specifically, the inclusion of feeds with high digestibility and nutritional value have been reported to be a viable option for reducing CH4 emissions and, simultaneously, increase animal productivity. The present study aimed to evaluate the effect of the nutritional composition and voluntary intake of diets based on tropical forages upon CH4 emissions from zebu steers. Five treatments (diets) were evaluated: Cay1: Urochloa hybrid cv. Cayman (harvested after 65 days of regrowth: low quality); Cay2: cv. Cayman harvested after 45 days of regrowth; CayLl: cv. Cayman + Leucaena leucocephala; CayLd: cv. Cayman + Leucaena diversifolia; Hay: Dichantium aristatum hay as a comparator of common naturalized pasture. For each diet representing different levels of intensification (naturalized pasture, improved pasture, and silvopastoral systems), CH4 emissions were measured using the polytunnel technique with four zebu steers housed in individual chambers. The CH4 accumulated was monitored using an infrared multigas analyzer, and the voluntary forage intake of each animal was calculated. Dry matter intake (DMI, % of body weight) ranged between 0.77 and 2.94 among diets offered. Emissions of CH4 per kg of DMI were significantly higher (P < 0.0001) in Cay1 (60.4 g), compared to other treatments. Diets that included Leucaena forage legumes had generally higher crude protein contents and higher DMI. Cay1 and Hay which had low protein content and digestibility had a higher CH4 emission intensity (per unit live weight gain) compared to Cay2, CayLl and CayLd. Our results suggest that grass consumed after a regrowth period of 45 days results in lower CH4 emissions intensities compared to those observed following a regrowth period of 65 days. Diets with Leucaena inclusion showed advantages in nutrient intake that are reflected in greater live weight gains of cattle. Consequently, the intensity of the emissions generated in the legume-based systems were lower suggesting that they are a good option for achieving the emission reduction goals of sustainable tropical cattle production.

Effect of the addition of Enterolobium cyclocarpum pods and Gliricidia sepium forage to Brachiaria brizantha on dry matter degradation, volatile fatty acid concentration, and in vitro methane production.

The purpose of this study was to determine the in vitro fermentation and methane (CH4) production in the grass Brachiaria brizantha (B) alone or when mixed with Gliricidia sepium forage (G) and/or Enterolobium cyclocarpum pods (E). Theses substrates were incubated in the following proportions: B100 (B100%), B85E15 (B85% + E15%), B85G15 (B85% + G15%), B85GE15 (B85% + G7.5% + E7.5%), and B70GE30 (B70% + G15% + E15%). Dry matter degradation (DMD), volatile fatty acid (VFA) concentration, and CH4 production were measured at 12, 24, and 48 h of incubation. Experimental design was a randomized complete block. At 48-h incubation, DMD ranged between 46.5 and 51.2% (P = 0.0015). The lowest cumulative gas production (CGP) was observed in B85E15 and B85G15 (160 mL CGP/g organic matter, on average). At 48 h, B85G15 and B100 produced 28.8 and 30.2 mg CH4/g DMD, respectively, while B85E15 or the mixtures, 33.5 mg CH4/g DMD, on average (P ≤ 0.05). B85E15 and B70G30 had the highest concentration of total VFA (P ≤ 0.05). Results showed that B85E15 and B70GE30 favor DMD and increased total production of VFA and CH4 at 48 h. Supplementing livestock feed with legume forages and pods allows improves the nutritional quality of the diet and the fermentation patterns.

How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal.

There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international '4p1000' initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long-term experiments and space-for-time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.

Adequate vegetative cover decreases nitrous oxide emissions from cattle urine deposited in grazed pastures under rainy season conditions.

A decline in pasture productivity is often associated with a reduction in vegetative cover. We hypothesize that nitrogen (N) in urine deposited by grazing cattle on degraded pastures, with low vegetative cover, is highly susceptible to losses. Here, we quantified the magnitude of urine-based nitrous oxide (N2O) lost from soil under paired degraded (low vegetative cover) and non-degraded (adequate vegetative cover) pastures across five countries of the Latin America and the Caribbean (LAC) region and estimated urine-N emission factors. Soil N2O emissions from simulated cattle urine patches were quantified with closed static chambers and gas chromatography. At the regional level, rainy season cumulative N2O emissions (3.31 versus 1.91 kg N2O-N ha-1) and emission factors (0.42 versus 0.18%) were higher for low vegetative cover compared to adequate vegetative cover pastures. Findings indicate that under rainy season conditions, adequate vegetative cover through proper pasture management could help reduce urine-induced N2O emissions from grazed pastures.

Limits of agricultural greenhouse gas calculators to predict soil N2O and CH4 fluxes in tropical agriculture.

Demand for tools to rapidly assess greenhouse gas impacts from policy and technological change in the agricultural sector has catalyzed the development of 'GHG calculators'- simple accounting approaches that use a mix of emission factors and empirical models to calculate GHG emissions with minimal input data. GHG calculators, however, rely on models calibrated from measurements conducted overwhelmingly under temperate, developed country conditions. Here we show that GHG calculators may poorly estimate emissions in tropical developing countries by comparing calculator predictions against measurements from Africa, Asia, and Latin America. Estimates based on GHG calculators were greater than measurements in 70% of the cases, exceeding twice the measured flux nearly half the time. For 41% of the comparisons, calculators incorrectly predicted whether emissions would increase or decrease with a change in management. These results raise concerns about applying GHG calculators to tropical farming systems and emphasize the need to broaden the scope of the underlying data.