Elsevier

Agricultural Systems

Volume 195, January 2022, 103303
Agricultural Systems

Research paper
Yield gap analysis to identify attainable milk and meat productivities and the potential for greenhouse gas emissions mitigation in cattle systems of Colombia

https://doi.org/10.1016/j.agsy.2021.103303Get rights and content

Highlights

  • Cattle are responsible for 21% of Colombian GHG emissions, identifying sustainable strategies for its mitigation is crucial.

  • Yield gap analysis is useful for exploring opportunities to increase yields by identifying factors constraining production.

  • This study calculated the yield gaps for Colombian cattle systems, their carbon footprints, and proposed mitigation options.

  • Substantial cattle yield gaps were found, hence there is a considerable scope to improve milk and meat yields in Colombia.

  • Closing the yield gaps by increasing cattle productivity is an important mitigation strategy of climate change in Colombia.

Abstract

CONTEXT

Colombia has a total of 27.2 million heads of cattle, ranking fourth among the Latin American countries. Identifying sustainable strategies to mitigate greenhouse gas emissions (GHGE) will help the Colombian government meet their goal of a 51% reduction in national emissions by 2030. Estimation of yield gaps for identifying the potential to improve cattle farms productivity and efficiency in Colombia help on reducing the GHGE intensities from the cattle sector.

OBJECTIVE

This paper aims to calculate the gap between attainable and actual milk and meat yields for specialized dairy, dual-purpose, cow-calf, and fattening production systems in 3 agro-ecological zones (AEZ) in Colombia; to identify the main aspects that restrict the meat and milk yields in these production systems; and analyze how closing yield gaps affect the carbon footprint (CF) of meat and milk production.

METHODS

The most suitable AEZs for cattle activities were identified by considering environmental, climatic, edaphic, and land characteristics. From a dataset of 1505 surveyed farms, a yield gap benchmarking analysis for estimating the potential to increase meat and milk yields in each of the identified AEZ was applied. The most productive farms were included in the “best farms” while the rest of the farms belonged to the “farms operating below potential”. A “cradle to farm-gate” Life Cycle Assessment was used to calculate the CF. Three scenarios were proposed for closing the yield gaps by 50, 75, and 100%, between the two groups of farms.

RESULTS AND CONCLUSIONS

Three AEZs likely to support cattle activities in Colombia were identified. Average milk production from the farms operating below potential was 45–50% of potential production, and meat was 34–51%, indicating that a potential to achieve increases in milk and meat productivity exists. CFs of 1 kg milk or meat were lower in the groups of best-performing farms than in the groups of farms operating below potential. Yield gaps for milk and meat production can be closed by improving cattle management practices and better technologies. As a general trend, closing the yield gaps decreases the CFs.

SIGNIFICANCE

Our findings contribute to understand the farms' current productive performance and provides key insights into the possible technological and managerial changes for improving the productivity of cattle systems in Colombia. In addition, the study showed how milk and meat CFs can be lowered with the adoption of proper cattle management practices, and better technologies.

Introduction

By 2050, the world population is expected to increase by 2 billion people, reaching a total of 9.7 billion. (United Nations, 2019). In the past 50 years, animal-based production has increased around 400% at a worldwide level (Vranken et al., 2014). In addition, during the last 30 years, the consumption of milk and meat has grown 3 times more in developing countries than in developed ones (FAO, 2009). The increase in the human population, incomes, and urbanization in developed countries is expected to drive a continuous increase in meat and milk consumption, and in developing countries, it is expected to increase twice during the following 40 years (Herrero et al., 2016a; Rao et al., 2015). From an environmental perspective it is therefore essential that, to fulfill the future demand of animal-based food, increases in animal production rates go hand-in-hand with improved efficiency and sustainability of livestock systems (Anderson et al., 2016).

At the moment, livestock and crop activities contribute between 10 and 12% to global greenhouse gas emissions (GHGE) and are considered one of the major sources of anthropogenic emissions (Mbow et al., 2019). In Latin America, livestock activities generate around 1889 GtCO2eq yr−1, about 25% of the global GHGE of the Agriculture, Forestry and Other Land Use (AFOLU) sector (FAO, 2019). In Latin America, cattle systems are considered a crucial source of income. Cattle production systems range from low productivity grazing based systems to more intensive and specialized systems with high production rates (Arango et al., 2020; Herrero et al., 2013). Intensification of cattle production, defined as increased production per animal and per area, through higher quality of feed and better cattle management practices, could be a key for improving meat and milk yields, and household incomes in the Latin American region (Rao et al., 2015) while at the same time increasing production efficiency.

In developed countries the cattle sector has shown a general trend towards production intensification, increasing animal production per animal and per unit land area used (Bava et al., 2014; Gerssen-Gondelach et al., 2017; Styles et al., 2018). Nevertheless, in Latin America increases in production rates have not been made through increases in productivity, but rather through expanding the agricultural frontier (González-Quintero et al., 2015). This has led to negative environmental impacts such as increases in GHGE, deforestation and biodiversity loss, among others (Gerber et al., 2013; Smith et al., 2013). Considering this, there is an important potential in the Latin American region for increasing the cattle yields and reducing the environmental burdens through sustainable intensification of the cattle production model, as well as by adopting better cattle management practices. However, which improved management practices are attractive for farmers is still largely unknown. The identification of the main constraints of cattle production is required to establish the feasible technological changes necessary and possible to increase the productivity of these systems.

Colombia has a total of 27.2 million heads of cattle, ranking fourth among the Latin American countries. In 2020, the annual beef production corresponded to 889 million kg carcass, while the milk production reached 7393 million liters (Fedegan, 2020). The GHGE from cattle activities (animals and pastures) account for 21% of national emissions inventory (IDEAM, 2018). As the Colombian government committed to lower 51% of national GHGE by 2030 (Ministerio de Ambiente y Desarrollo Sostenible, 2020), identifying sustainable cattle strategies for mitigating emissions is of paramount importance. In support of this endeavor, in this study we used the yield gap analysis for identifying the potential to improve the productivity of beef and dairy cattle farms in Colombia, and its influence on reducing the GHGE.

A yield gap is defined as the difference between the attainable and current productivity for an agricultural product (Herrero et al., 2016b; van der Linden et al., 2015). Yield gap analysis is useful for estimating and exploring opportunities to increase agricultural production by identifying factors constraining production. Typically, yield gap analyses are used in cropping systems for determining differences between current and maximum attainable productivities in specific agro-ecological characteristics for a certain region, to explore possibilities for improving land productivity (Hoffmann et al., 2017; Lobell et al., 2009; Monteiro et al., 2020; Van Ittersum et al., 2013; Woittiez et al., 2017). In recent years, the application of yield gap analyses in livestock systems has been used, mainly in developing countries which are characterized by low productive performance and therefore great potential for its increase (Cortez-Arriola et al., 2014; Henderson et al., 2016; Mayberry et al., 2017; van der Linden et al., 2015). However, to our knowledge, in Colombia, no yield gap studies in cattle farms have been developed, which restricts the knowledge of the real potential for increasing the productivity of these systems.

Different metrics have been proposed for standardize GHGE intensities. The carbon footprint (CF), also known as the global warming potential (GWP100), is a metric usually used in Life Cycle Assessment (LCA) studies in cattle systems for expressing GHGE intensities. The CF is defined as “the quantity of GHGs expressed in terms of carbon dioxide equivalents (CO2-e) according to the global warming potential of individual gases, emitted into the atmosphere by an individual, organization, process, product, or event from within a specified boundary” (Pandey et al., 2011).

The present paper aims to (1) calculate the gap between attainable and actual milk and meat yields for specialized dairy, dual-purpose, cow-calf, and fattening production systems in 3 agro-ecological zones (AEZs) in Colombia; (2) to identify the main aspects that restrict the meat and milk yields in these production systems; and (3) analyze how closing yield gaps affect the carbon footprint of meat and milk production.

Section snippets

Methodology

Environmental, climatic, edaphic and land characteristics from 1505 farms in Colombia were used to identify AEZs. A yield gap benchmarking analysis for estimating the potential to increase meat and milk yields in each of the identified AEZ was applied. Farms were divided into the “best farms” and the “farms operating below potential”. Each group was analyzed to recognize its potential to increase productivity with respect to the “best farms”. Moreover, carbon footprint was calculated in the

Agro-ecological cattle zones

Three AEZs were identified (Fig. 1b). The “AEZ North zone” grouped 689 farms and was characterized for the highest mean annual temperature (27.7 °C) and soil pH (6.42) among agro-ecological zones, and the lowest annual precipitation rate (1348 mm), soil organic carbon content (21.4%), and land slope (1.61%). In “AEZ central zone” 623 farms were identified, with a mean annual temperature of 20.5 °C, the annual precipitation rate corresponded to 1919 mm, the soil pH was 5.54, and the soil organic

Discussion

Several studies of yield gaps in the agronomy field have been reported, however, yield gaps studies in the livestock sector are few, and to our knowledge, in the Latin America Region only one study has been performed in smallholder dairy cattle farms in Mexico (Cortez-Arriola et al., 2014). The estimation of yield gaps in livestock systems is a relatively recent approach, and a standard method for its development has not been established yet (Mayberry et al., 2017). Therefore, using the yield

Conclusions

We describe the main characteristics of 3 AEZs that support cattle activities in Colombia. Through a yield gap analysis for cattle systems located in each AEZ, we identified key differences in farm management practices between best farms and farms operating below potential that impact the productivity of the systems. The best farms showed better implementation and adoption of: infrastructure, machinery and equipment, and feed, reproductive, and pasture management practices.

The results of our

Funding

This work was supported by the Government of the United Kingdom, the Global Environmental Fund (GEF), CGIAR Fund Donors and through bilateral funding agreements (for details please visit https://ccafs.cgiar.org/donors and https://livestock.cgiar.org/).

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.

Acknowledgements

This study was funded by the CGIAR Research Program (CRP) on Climate Change, Agriculture and Food Security (CCAFS) and the Livestock CRP. We thank all donors that globally support the work of the CRP programs through their contributions to the CGIAR system. We are thankful to the Colombian Sustainable Cattle Ranching project implemented by the Federación Colombiana de Ganaderos (FEDEGAN-FNG), the Fundación Centro para la Investigación en Sistemas Sostenibles de Producción Agropecuaria (CIPAV),

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