Technical and environmental characterization of dual-purpose cattle farms and ways of improving production: A case study in Colombia

Abstract

There are few reports on dual-purpose cattle systems characterization in Latin America and Colombia based on large datasets. This limits our understanding of their dynamics, and the establishment of public policies and government programs to improve their productive performance, promotion and rural development. This study aimed to characterize very small, small, medium, and large dual-purpose farms in Colombia from technical and environmental perspectives. The data analysed were obtained from the Ganadería Colombiana Sostenible and the LivestockPlus projects, which gathered information from a total of 1313 dual-purpose farms in Colombia. Farms were classified as being either very small (1 to 30 bovines), small (31 to 50 bovines), medium (51 to 250 bovines), or large farms (more than 251 bovines). Numerical and categorical variables were distributed into five components: (1) General Farm Information, (2) Herd Composition and Management, (3) Pasture Management, (4) Production Information, and (5) Environmental Information. Each component was analysed using the factorial analysis of mixed data (FAMD) method. According to FAMD, for the components General Farm Information, Herd Composition and Management, Pasture Management, and Production Information, the distribution of variables led to a spatial separation of the centroid from each category of producers. For the component Environmental Information, there was no separation of the centroid. In general, medium-sized and large farms showed better infrastructure, better machinery and equipment, and better reproductive practices; however, this was not reflected in a significant improvement of productive parameters, except for a lower mortality rate. Larger livestock producers need to plan their livestock husbandry activities properly, based on their better available infrastructure and livestock management practices, with the purpose of increasing productivity. The main features identified for each livestock producer category can be the basis to guide and establish policies and programmes for their technological development. The development of better livestock management practices and the implementation of technology, as well as technical assistance, should focus on small- and medium-sized livestock producers, which could lead to reaching a better productive and reproductive performance of dual-purpose systems.

The risk of unintended deforestation from scaling sustainable livestock production systems

“…Our results show that the dairy and beef (cattle) production systems in the Colombian Amazon are geographically dispersed. However, they are linked through the provision of inputs (fattening animals) from one to the other (Gonz alez- Quintero et al, 2020). Therefore, substantial changes to one could affect the other and possibly the entire livestock sector and their value chains.…”

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

“…Dual-purpose, cow-calf and fattening systems in Colombia are low input farms, with little use of machinery and equipment, and infrastructure adoption, as was also reported by Gonzalez-Quintero et al (2020b, 2020c, 2020a. Despite this, in these three productive orientations, the groups of best farms showed technological indexes considerably higher than the groups of farms operating below potential.…”

“…DPS are usually located in the low tropics (<1,200 m.a.s.l), are marked as pasture-based feeding systems (Ruiz-Guevara et al, 2008), and its milk yield, on an area and animal basis, is substantially lower than in specialized dairy systems. (Cortés-Mora et al, 2012;González-Quintero et al, 2020a). Specialized dairy systems are defined as those where cows are milked without nursing calves, and cows and calves are typically separated few days after birth (Holmann et al, 2003).…”

“…The variables used in the FAMD exercise were both qualitative and quantitative and based on previous studies characterizing cattle farms in Latin America (Albarrán-Portillo et al, 2015;Cuevas-Reyes and Rosales-Nieto, 2018;González-Quintero et al, 2020a, 2020bRangel et al, 2020). The qualitative variables captured pasture management practices, e.g., the existence of improved pastures and silvopastoral systems, type of pastoral system (alternate, rotational, in strips) and weeding method (chemical, manual, mechanical, mixed), fertilization, application of amendments to soils.…”

Exploring the Clinical Characteristics of COVID-19 Clusters Identified Using Factor Analysis of Mixed Data-Based Cluster Analysis

“…Our study aimed to identify the subtypes of COVID-19 by using an unsupervised classifier. Factor analysis of mixed data (FAMD)-based cluster analysis was used to identify COVID-19 subtypes based on clinical symptoms, laboratory tests and demographic characteristics (13). Three COVID-19 subtypes were identified in our study, and the differences among the COVID-19 subtypes would contribute to our understanding of COVID-19 clinical characteristics.…”