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

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ricardo González-Quintero ◽  
Rolando Barahona-Rosales ◽  
Diana María Bolívar-Vergara ◽  
Ngonidzashe Chirinda ◽  
Jacobo Arango ◽  
...  
Keyword(s):  
Management Practices ◽  
Environmental Information ◽  
Mixed Data ◽  
Categorical Variables ◽  
Pasture Management ◽  
Dual Purpose ◽  
Livestock Management ◽  
Dual Purpose Cattle ◽  
Cattle Systems ◽  
Large Farms

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.

scholarly journals Technical and environmental characterization of Colombian beef cattle-fattening farms, with a focus on farm size and ways of improving production

2019 ◽  
Vol 49 (2) ◽  
pp. 153-162 ◽  
Author(s):  
Ricardo González-Quintero ◽  
María Solange Sánchez-Pinzón ◽  
Diana María Bolívar-Vergara ◽  
Ngonidzashe Chirinda ◽  
Jacobo Arango ◽  
...  
Keyword(s):  
Rural Communities ◽  
Production Systems ◽  
Spatial Separation ◽  
Environmental Information ◽  
Mixed Data ◽  
Farm Size ◽  
Categorical Variables ◽  
Pasture Management ◽  
Livestock Sector ◽  
Large Farms

In Colombia, cattle-fattening farms account for 20.7% of the Colombian cattle herd and play an important role in terms of economic and social benefits for rural communities. However, few characterization studies have been conducted on these production systems, which limit our understanding of their production dynamics and environmental impacts. This study aimed to characterize very small, small, medium, and large cattle-fattening farms from technical and environmental perspectives. The data analyzed were obtained from the Ganadería Colombiana Sostenible and the LivestockPlus projects, which gathered information from a total of 2618 farms, classified according to their cattle production orientation. From those, 275 cattle-fattening farms were classified as being either very small (1–30 bovines), small (31–50 bovines), medium (51–250 bovines), or large farms (more than 251 bovines). Numerical and categorical variables were distributed into five components: (1) general farm information, (2) composition and management of the herd, (3) pasture management, (4) production information, and (5) environmental information. Each component was analyzed 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, 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. Better infrastructure, machinery and equipment, better pasture management, and better productive parameters and practices were observed in larger farms. This suggests that those public policies aimed at improving productive and environmental performance of the livestock sector should give priority to small- and medium-sized livestock producers considering their farm characteristics.

scholarly journals Variation and adaptation in limpograss (Hemarthria altissima)

1995 ◽  
pp. 49-53
Author(s):  
P.W. Woods ◽  
J.N. Couchman ◽  
H.A. Barlow
Keyword(s):  
Morphological Variation ◽  
Morphological Traits ◽  
Management Practices ◽  
Pasture Management ◽  
Plant Survival ◽  
Hemarthria Altissima ◽  
Plant Morphological Traits ◽  
Cattle Systems ◽  
Future Work

Persistent and productive cultivars of limpograss (Hemarthriu altissima (Poir.) Stapf et C.E. Hubb.) are required if the species is to be useful in Northland cattle systems. A study was undertaken to investigate plant morphological traits, adaptation and persistence of 8 accessions. A series of abandoned research sites was revisited to determine long-term persistence and adaptation. Trials were established at 4 new sites throughout the northern North Island to assess morphological variation and plant survival. There was considerable variation in morphological traits assessed and plant survival, allowing scope for future selection. Bigalta used in earlier research trials had largely failed to persist under normal pasture management practices. Future work should use the cultivar Floralta. Keywords: adaptation, flowering, Hemarthria altissima, leaf, morphological variation, persistence, seed, stolon

scholarly journals Reproductive management strategies to reduce postpartum anestrus in dual-purpose cattle

2021 ◽  
Author(s):  
Juan González-Maldonado ◽  
Miguel J. García-Winder ◽  
Jaime Gallegos-Sánchez ◽  
Camelia A. Herrera-Corredor ◽  
Gustavo Sosa-Pérez ◽  
...  
Keyword(s):  
Management Practices ◽  
Production Systems ◽  
Management Strategies ◽  
Reproductive Potential ◽  
Productive Efficiency ◽  
Weight Changes ◽  
Dual Purpose ◽  
Reproductive Management ◽  
Dual Purpose Cattle ◽  
Postpartum Weight

Objective: To share technical aspects and recommendations to improve the reproductive and productive efficiency of dual-purpose cattle. Design/Methodology/Approach: A review of scientific articles published in journals was carried out to show the importance of some factors that limit reproduction, as well as to identify management strategies to increase the reproductive potential in dual-purpose cows. Results: The duration of postpartum anestrus is reduced by weaning calves at a few days or weeks of age, restricting suckling to short periods of the day, delaying suckling, and exposing cows to a bull during postpartum. On average, the combined effect of delayed suckling and exposure of cows to a bull reduces postpartum anestrus to less than 50 d and the calving-conception interval to 84 days. Milk production and calf weight gain also are improved without affecting postpartum weight changes in cows. Study Limitations/Implications: Extensive management of dual-purpose cattle reduces the intensive use of some reproductive biotechnologies commonly applied in other animal production systems. Findings/Conclusions: Improvement in the reproductive efficiency of dual-purpose cattle can be achieved by reducing the postpartum anestrus by using reproductive management strategies and minor modifications to common management practices.

scholarly journals Seroprevalence and risk factor associated with respiratory viral pathogens in dual-purpose cattle of Aguachica, Rio de Oro, and La Gloria municipalities in Cesar department, Colombia

2019 ◽  
Vol 12 (7) ◽  
pp. 951-958 ◽  
Author(s):  
Juan Carlos Pinilla León ◽  
Wilson Diaz ◽  
María Cristina Vasquez ◽  
Julio Cesar Tobón ◽  
Alfredo Sánchez ◽  
...  
Keyword(s):  
Risk Factor ◽  
Management Practices ◽  
Clinical Signs ◽  
Significant Risk ◽  
Enzyme Linked Immunosorbent Assay ◽  
Statistical Association ◽  
Viral Pathogens ◽  
Dual Purpose ◽  
Diarrhea Virus ◽  
Dual Purpose Cattle

Aim: The research was conducted to determine the seroprevalence and risk factor associated with respiratory viral pathogens in dual-purpose cattle of Aguachica, Rio de Oro and La Gloria municipalities in Cesar department, Colombia. Materials and Methods: The seroprevalence study was done from the random sampling (n=1000) of blood collected from 29 dual-purpose herds, located in three municipalities (Aguachica, Rio de Oro, and La Gloria) of Cesar department. The presence of antibodies against bovine herpesvirus type 1 (BHV-1), bovine respiratory syncytial virus (BRSV), bovine viral diarrhea virus (BVDV), and bovine parainfluenza-3 virus (BPI-3V) in the samples was detected by indirect enzyme-linked immunosorbent assay. Epidemiological data were obtained using a questionnaire administered to the owner or manager of each herd. Results: The overall highest seroprevalence was observed for BHV-1 (94.7%), followed by BRSV (98.6%), BVDV (35.2%), and BPI-3V (47.1%). Regarding the seroprevalence by municipalities, there was a statistical association (p<0.05) for BVDV; however, for BRSV, BHV-1, and BPI-3V, no statistical association was found (p>0.05) between seropositive values and the municipalities, indicating that animal was seropositive in similar proportions in the three municipalities. Female sex and older animals (>24 months) were a significant risk factor for BHV-1 and BPI-3V infection. Regarding the clinical signs, there was a statistical association (p<0.05) between the seropositive values of BVDV and most of clinical signs observed, except for abortion. Conclusion: This research confirms the high seroprevalence of the respiratory viral pathogens in nonvaccinated cattle within the study areas. Therefore, appropriate sanitary management practices and routine vaccination programs should be adopted to reduce the seroprevalence of these infectious agents.

scholarly journals Carbon footprint, non-renewable energy and land use of dual-purpose cattle systems in Colombia using a life cycle assessment approach

2020 ◽  
pp. 104330
Author(s):  
Ricardo González-Quintero ◽  
Troels Kristensen ◽  
María Solange Sánchez-Pinzón ◽  
Diana María Bolívar-Vergara ◽  
Ngonidzashe Chirinda ◽  
...  
Keyword(s):  
Land Use ◽  
Life Cycle Assessment ◽  
Renewable Energy ◽  
Life Cycle ◽  
Carbon Footprint ◽  
Dual Purpose ◽  
Assessment Approach ◽  
Dual Purpose Cattle ◽  
Cattle Systems

Economic comparison of nutritional management strategies for Venezuelan dual-purpose cattle systems

1994 ◽  
Vol 72 (7) ◽  
pp. 1680-1696 ◽  
Author(s):  
C. F. Nicholson ◽  
R. W. Blake ◽  
C. I. Urbina ◽  
D. R. Lee ◽  
D. G. Fox ◽  
...  
Keyword(s):  
Management Strategies ◽  
Nutritional Management ◽  
Dual Purpose ◽  
Dual Purpose Cattle ◽  
Cattle Systems ◽  
Economic Comparison

Economic evaluation of current and alternative dual-purpose cattle systems for smallholder farms in the central Peruvian highlands

2009 ◽  
Vol 101 (3) ◽  
pp. 152-161 ◽  
Author(s):  
K. Bartl ◽  
A.C. Mayer ◽  
C.A. Gómez ◽  
E. Muñoz ◽  
H.D. Hess ◽  
...  
Keyword(s):  
Economic Evaluation ◽  
Smallholder Farms ◽  
Dual Purpose ◽  
Dual Purpose Cattle ◽  
Cattle Systems

scholarly journals Head-to-head comparison of clustering methods for heterogeneous data: a simulation-driven benchmark

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregoire Preud’homme ◽  
Kevin Duarte ◽  
Kevin Dalleau ◽  
Claire Lacomblez ◽  
Emmanuel Bresso ◽  
...  
Keyword(s):  
Hierarchical Clustering ◽  
Latent Class ◽  
Latent Class Model ◽  
Real Life ◽  
Heterogeneous Data ◽  
Mixed Data ◽  
Categorical Variables ◽  
Clustering Methods ◽  
Model Based ◽  
Partitioning Around Medoids

AbstractThe choice of the most appropriate unsupervised machine-learning method for “heterogeneous” or “mixed” data, i.e. with both continuous and categorical variables, can be challenging. Our aim was to examine the performance of various clustering strategies for mixed data using both simulated and real-life data. We conducted a benchmark analysis of “ready-to-use” tools in R comparing 4 model-based (Kamila algorithm, Latent Class Analysis, Latent Class Model [LCM] and Clustering by Mixture Modeling) and 5 distance/dissimilarity-based (Gower distance or Unsupervised Extra Trees dissimilarity followed by hierarchical clustering or Partitioning Around Medoids, K-prototypes) clustering methods. Clustering performances were assessed by Adjusted Rand Index (ARI) on 1000 generated virtual populations consisting of mixed variables using 7 scenarios with varying population sizes, number of clusters, number of continuous and categorical variables, proportions of relevant (non-noisy) variables and degree of variable relevance (low, mild, high). Clustering methods were then applied on the EPHESUS randomized clinical trial data (a heart failure trial evaluating the effect of eplerenone) allowing to illustrate the differences between different clustering techniques. The simulations revealed the dominance of K-prototypes, Kamila and LCM models over all other methods. Overall, methods using dissimilarity matrices in classical algorithms such as Partitioning Around Medoids and Hierarchical Clustering had a lower ARI compared to model-based methods in all scenarios. When applying clustering methods to a real-life clinical dataset, LCM showed promising results with regard to differences in (1) clinical profiles across clusters, (2) prognostic performance (highest C-index) and (3) identification of patient subgroups with substantial treatment benefit. The present findings suggest key differences in clustering performance between the tested algorithms (limited to tools readily available in R). In most of the tested scenarios, model-based methods (in particular the Kamila and LCM packages) and K-prototypes typically performed best in the setting of heterogeneous data.

Sign in / Sign up

Export Citation Format

Share Document