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The main purpose of this work was analyzing how an innovation platform can foster and provide a basis for multi-actor collaboration in order to enable climate-smart agriculture (CSA) implementation at the local level. Using a mix of social (interactions between stakeholders, knowledge changes, adoption of practices) and technical indicators (income, fulfillment of caloric requirements of the household, farm resource use, planned biodiversity or greenhouse gas emission changes), we monitored the collaboration between an NGO, local civil authorities, associations, and farmers that aimed to achieve a common goal linked to the participatory and contextualized development of CSA in Colombia. We found that multiple stakeholder engagements led to improved interactions between members of the platform and their local environment, a proactive participation in the platform meetings and a significant increase in farmer knowledge levels on the challenges posed by climate change and the resultant extreme events. The platform also facilitated the adoption of best-bet practices that contribute towards CSA when farmers both diversify their production and decrease the use of mineral fertilizers. Our findings suggest that innovation platforms can facilitate the collective understanding and use of CSA options corresponding to local conditions and priorities. [ABSTRACT FROM AUTHOR]

Most smallholder farming areas of Zimbabwe have low soil fertility and low rainfall, which has continually decreased over the past years. In recent years, most of the smallholder farming areas have experienced perennial droughts, poor rainfall distribution and crop failures and these have been attributed to climate change and variability. Cultivation of dambos, which are seasonal wetlands, presents a climate change and variability adaptation option for smallholder farmers. This synthesis analyses the role of dambo cultivation in climate change and variability adaptation and discusses future directions for sustainable dambo utilization. The data on current dambo farming practices were collected from literature, surveys and field observations. The results showed that farmers grow crops in dambos as an adaptive strategy to climate change and variability and have largely abandoned upland fields where yields are <1 t ha−1in preference of dambos where yields average 2–3 t ha−1. Dambo cultivation offers a buffer against crop failures and has resulted in improved household food security. We conclude that dambo cultivation is a potentially beneficial farmer-driven climate change and variability adaptation strategy. However, if not properly designed and managed, dambo cultivation may result in their degradation hence there is need for further research to evaluate options for sustainable dambo utilization as intensification of dambo agriculture is important for food security. [ABSTRACT FROM PUBLISHER]

Nitrous oxide emissions from a network of agricultural experiments in Europe and Zimbabwe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logården in Sweden, Maulde in Belgium, Paulinenaue in Germany, Harare in Zimbabwe and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Gödöllö in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-Nha-1 yr-1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important determinant of emissions, accounting for 15% of the variance (using linear regression) in the data from the arable sites (p < 0.0001), and 77% in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission factors. Variability in N2O within sites that occurred as a result of manipulation treatments was greater than that resulting from site to site and year to year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation. [ABSTRACT FROM AUTHOR]

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 (R 2 , 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%), R 2 (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 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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jaramillo-Botero, Colorado, Quimbaya, Rebolledo, Lorieux, Ghneim-Herrera, Arango, Tobón, Finke, Rocha, Muñoz, Riascos, Silva, Chirinda, Caccamo, Vandepoele and Goddard.)

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 (N 2 O) emissions from excreta patches. However, how this forage affects methane (CH 4 ) or carbon dioxide (CO 2 ) 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 N 2 O and CH 4 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 CO 2 and cumulative CH 4 emissions during the driest conditions. However, no significant effect of the forage genotype was found on mitigating N 2 O emissions from dung. We attribute the absence of a significant BNI effect on N 2 O emissions to the limited incorporation of dung-N into the soil and rhizosphere where the BNI effect occurs. The average N 2 O EFs was 0.14%, close to the IPCC 2019 uncertainty range (0.01-0.13% at 95% confidence level). Moreover, CH 4 EFs per unit of volatile solid (VS) averaged 0.31 g CH 4  kgVS -1 , slightly lower than the 0.6 g CH 4  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., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The purpose of this study was to determine the in vitro fermentation and methane (CH 4 ) 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 CH 4 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 CH 4 /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 CH 4 at 48 h. Supplementing livestock feed with legume forages and pods allows improves the nutritional quality of the diet and the fermentation patterns.

Methane (CH 4 ) 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 CH 4 emissions. Specifically, the inclusion of feeds with high digestibility and nutritional value have been reported to be a viable option for reducing CH 4 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 CH 4 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), CH 4 emissions were measured using the polytunnel technique with four zebu steers housed in individual chambers. The CH 4 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 CH 4 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 CH 4 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 CH 4 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., (Copyright © 2020 Gaviria-Uribe, Bolivar, Rosenstock, Molina-Botero, Chirinda, Barahona and Arango.)

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., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

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 (N 2 O) 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 N 2 O emissions from simulated cattle urine patches were quantified with closed static chambers and gas chromatography. At the regional level, rainy season cumulative N 2 O emissions (3.31 versus 1.91 kg N 2 O-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 N 2 O emissions from grazed pastures.

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.