SciELO - Scientific Electronic Library Online

 
vol.52 issue2Physical-chemical and microbiological performance of Siboney de Cuba cows milkBromatological characterization of coffee (Coffea arabica L.) pulp for animal feeding purposes author indexsubject indexarticles search
Home Pagealphabetic serial listing  

My SciELO

Services on Demand

Journal

Article

Indicators

  • Have no cited articlesCited by SciELO

Related links

  • Have no similar articlesSimilars in SciELO

Share


Cuban Journal of Agricultural Science

Print version ISSN 0864-0408On-line version ISSN 2079-3480

Cuban J. Agric. Sci. vol.52 no.2 Mayabeque Apr.-June 2018  Epub June 22, 2018

 

Animal Science

Determinant factors of livestock production in a rural community in the southwest of Holguín, Cuba

Y. F. Peña-Rueda1  * 

D. Benítez2 

J. V. Ray2 

Yulien Fernández-Romay3 

1Centro de Estudio para Agroecosistemas Áridos, Universidad de Holguín. Avenida de los Libertadores # 287. Código Postal 80100. Gaveta Postal 57, Holguín, Cuba

2Instituto de Investigaciones Agropecuarias “Jorge Dimitrov”. Carretera Central. km 16 Vía Manzanillo. Código postal 85100. Gaveta postal 2140. Bayamo, Granma, Cuba

3Universidad Politécnica del Chimborazo. Panamericana Sur km 1 ½. Riobamba - Ecuador

Abstract

The objective of this research was to analyze the determinant factors of livestock production in a rural community in the southwest of Holguín province. Edaphoclimatic information was obtained from spatial data of the region and from the production of 21 farms through the variables annual milk production, herd size, productivity, body condition, natural grass area and number of paddocks. Factorial analysis was carried out and the statistical model of impact measurement was applied. The historical annual precipitation is 1073 mm and gives a dry character to the region, where vertisols, fersialitic and humic sialitic predominate, with limitations in drainage and tendency to salinization. The determining factors are production, feeding and management, which explain 78.9 % of the variance and allowed to determine the impact of agroecosystems on the farms (two of them with a positive impact on production and different breeding systems). In the environmental situation of the southwest of Holguín, the precipitations do not advise the development of milk production systems; however, the rural livestock deploys them. It is recommended to mitigate the impact of the agroecosystem to work for a dual-purpose zootechnical flow, with regionalized species under rotational methods, making sure to concentrate all the activities seasonally and maintain the key processes indispensable and at a minimum level in the dry period. In addition, researchers must evaluate social aspects of farms through extension practices to increase social and collective learning, by virtue of an environmental and productive education.

Key words: dual-purpose livestock; dry agroecosystem; rearing system; Cauto basin

Knowing the factors that influence on livestock activity allows us to discriminate between those that are really determining and those that do not, and in this way distribute resources, improve sales, adopt technologies, apply policies, perform actions to preserve the environment or simply simplify the decision-making processes. In Cuba, several studies have analyzed the organizational and ecological technological processes in dual- purpose farms (Benítez et al. 2002). Likewise, livestock has been characterized in the mountainous area of Granma province, with emphasis on the effects of height and slope (Benítez et al. 2008), and productive indicators, feeding and grassland management have been studied in milk production (Martínez-Melo et al. 2013).

The results indicate the need to reorder the resources or the activity as a whole to improve the efficiency of a certain geographical area. However, in most cases these alternatives are fitted to the linear model of technology transfer, and it is necessary to recognize changes in specific environments that require the management of innovation processes at the local level (Rodríguez et al. 2009).

The largest hydrographic basin in Cuba is formed by the Cauto river and its affluent. It is located in the western center of the eastern region, and occupies 9542 km2. Of these, 80.7 % are plains with dry environments. The southwest part of Holguín province is in this ecosystem, where the soils are clayey and are dedicated to the cultivation of sugarcane and minor fruits, although due to their limitations, extensive areas are destined to the rearing and fattening of mestizo or Cebu cattle. Annual rainfall does not exceed 1100 mm and the average annual temperature is 26 ºC (Oquendo 2006).

The Calixto García municipality, located in this region, has 15.9 thousand hectares in agricultural use. Of these, 70.5 % is used in animal production. The cattle herd is approximately 55 996 heads, of which 56.4 % belong to the farmers. There are 14 Basic Productive Entities. Two are Cooperatives for Agricultural Production (CPA) and eight Credit and Service Cooperatives (CCS), and the rest corresponds to the state sector. The 67.3 % of the population lives in rural areas, 1/3 works in farms (ONEI 2016). The rural sector has a great impact on the local economy, and is also the one that depends completely on natural resources and climate.

The objective of this research was to analyze the determinant factors of livestock production in a rural community from the southwest of Holguín province, located in the northern Cauto river basin, in order to facilitate innovation processes for beef production.

Materials and Methods

The study was carried out in Sabanaso, a rural community in the southwest of Holguín, located in the northern region of Cauto river basin, in Calixto García municipality, Holguín, Cuba.

The historical performance of temperatures and rainfall of the region was examined through the option Data climate point of the free software DIVA GIS ver. 7.5.0.0 (Hijmans et al. 2012) from the climatic data of the period 1967-2000, offered by Hijmans et al. (2005) in WorldClim ver.1.4.

The characteristics of texture, drainage class (assuming slope less than 0.5 %), predominant properties, clay content (%) and salinity of the upper soil horizon (dS/m) were obtained from the harmonized soil database of the world contained in the free software HWSD Viewer ver. 1.21 (Verelst & Wiberg 2012).

The existence of a Credit and Services Cooperative (CCS) in the area was used to raise awareness among the Junta Directiva and the Asamblea de Asociados with the objectives of this research. A universe of 54 farms was created, dedicated to livestock, with dissimilar productions and diversity in its spatial distribution. The sample was of 21 farms. Its size was determined for a limit unit, with a confidence interval of 95 % of the mean farm area (expressed in ha) and standard deviation of 1,075. The size of the preliminary sample was 30 % of the population, according to Di Rienzo et al. (2005) formula:

Where:

n

- sample size

T

- quantile of the T de Student distribution for degrees of freedom (n-1);(1-α/2)

α

- error probability

S

- standard deviation of the sample

c

- limit units of the range of confidence interval

From a survey that contained general data of the farm and its processes, quantitative variables of variance non- zero were extracted, which allowed obtaining the following indicators directly or by calculation: annual milk production (kg), herd size (UGM), productivity (kg of live weight weaned. breeding-1. year-1), body condition of the breeding (points), natural grass area (ha) and number of paddocks.

The indicators were subjected to principal component analysis, with orthogonal Varimax rotation, and none were excluded due to their weight factor. The components of Eigen values higher than the unit were used to explain the existence of determinant biotic factors. These received the name from the processes in which the variables that gave rise to it participate.

To establish differences between the farms, the statistical model for measuring the impact of innovation or technology transfer in the agricultural sector was used (Torres et al. 2008). The two farms with higher factorial scores in the first component were selected to describe, from point estimates, selected aspects from the survey (quantitative and qualitative), as well as management alternatives in the agroecosystem.

The statistical techniques were applied through the proprietary program IBM SPSS Statistics ver. 22 (IBM 2013).

Results and Discussion

The climatic seasonality of the region (figure 1), establishes historical average annual precipitation of 1073 mm, with accumulated of 67.4 % for the rainy period and 32.6 %, for the dry season. The minimum and maximum average temperatures are 19.7 and 31.5 ºC, respectively.

Figure 1 Monthly performance of precipitations and temperatures in Sabanaso community, obtained from the data of Hijmans et al. (2005). 

Drought is a phenomenon that occurs when rainfalls are considerably lower than the normal recorded levels.

According to Cutié and Lapinel (2013), the percentile distribution of annual rainfall accumulations in Holguín province shows that 30 % are less than 1087 mm, which places the Calixto García municipality at that percentile.

The soils have fine texture, with bad to moderately good drainage, with mostly vertic properties, and prevalence of the clayey fraction. The average salinity is 0.1 dS/m

Table 1 Main groupings and characteristics of the soils in Sabanaso community 

Source: Taken from Verelst & Wiberg (2012)

According to Verelst and Wiberg (2012), the predominant clusters are vertisols, luvisols and phaeozems, which due to their characteristics correspond to the vertisols, fersialitic and humic sialytics of the New Version of Genetic Classification of Soils of Cuba (Hernández et al. 2003). In these soils, the variables drainage class, vertic properties and clay in surface soil, are responsible for the limitations to evacuate the superficial and temporal over-humidification, as well as the tendency to salinization of these soils (Hernández et al. 2015).

In the agroecosystem, the elements that determine the abiotic environment do not appear isolated. Soil capacity, rainfall and climatic variables, water infiltration data and the physical potential and productive potential of the agricultural landscape are key characteristics to consider in order to determining the suitability of an area to be rehabilitated for a specific purpose (FAO and CLD 2015).

In tropical areas, temperatures are close to the maximum tolerable for crops, so it is expected that in future periods the productivity will decrease to one third, due to the increase in thermal stress and the driest soils. It is also expected to increase the salinization and desertification of agricultural lands in arid zones (FAO 2014).The extensive livestock systems, due to their dependence on nature, are the most vulnerable to drought and floods, as well as to the thermal stress of cattle (Derner et al. 2017).

In the biotic environment three components were extracted, whose marginal proportion of variance, explained as a whole, is 78.9 %, and correspond to the production, feeding and management factors (table 2). The analysis showed that the Bartlett sphericity test was significant (P <0.05), and the Kaiser-Meyer- Olkin index was adequate (KMO = 0.5). This shows that the data fulfill the required assumptions (Hair et al. 2010).

Table 2 Characteristics of the main components and indicators in the livestock of Sabanaso community. 

The annual milk production and herd size have a direct relation with the first component, while productivity has an inverse relation. In the rural sector, milk constitutes a permanent and stable monetary income. With a larger herd, this may seem safer (FAO 2013). Productivity, because of its link with calf rearing, which is not the productive purpose, is differently perceived, and is at favor of calf’s individuality and maternal ability (Espasandin et al. 2016).

The body condition and the natural grass area are directly related to the second component. The first as an effect, and the second as a cause of the variations that occur in the body reserves and therefore, on the milk yield and the reproductive performance of cows in the pastoral systems, where the availability in the natural grasses area changes seasonally in quantity and quality (Pérez-Infante 2013 and Derner et al. 2017).

The number of paddocks represents the management. The number of subdivisions is often low in rural systems. In Ciego de Ávila, Martínez-Melo et al. (2013) found in the farms of the rural sector with milk livestock, mean and standard deviation of 2.95 ± 2.23 paddocks, while in the Sabanaso community it was 2.19 ± 1.21. The higher number of subdivisions is of five, and even when it is not determinant, it has a positive effect, if it is used in association with the regulation of the grazing pressure to control the stocking rate and take the necessary measures with respect to the quantity and moment of offering food during the year (Senra 2005, and Senra et al. 2005).

Martínez-Melo et al. (2013) found that in farms with milk livestock from the sector, management, production and basic foods are, in that order, the three determining factors and contribute in 55.2 % to the variability of these systems. Even when the contributions of the factors differ, the production is related to milk production indicators and the herd size; the management with variables of general surface dedicated to the feeding, and the number of paddocks with the third component, that collects the delimited surface of grasses and forages cultivated.

The indicators referred also appear in livestock of the Granma mountainous area (Benítez et al. 2008), with 58.2 % of the variance explained, and in double-purpose herds in Cauto Valley (Benítez et al. 2002), with 60. 5 %. They are also related to the productive efficiency of these herds. In the mountain conditions, the slope of the relief gives another connotation to the productive activity, as well as in the Valley the time of day, nocturnal grazing, with maximum exposure to heat, in addition to the time without water.

The detailed examination of the factors production, feeding and management in the rural farms allows determining the impact of the agroecosystem in them. Production is the most affected factor, with 60.2 % of cases with negative values. Then, food and management, both with 47.6 %, although almost a quarter of the herds shows affectation in these two factors, closely linked by the skill with which the resources and key processes of the farm are managed (figure 2) .

Figure 2 Performance of the production, feeding and management in each studied farm. 

In dry environments, management must be matched with resilience, risk reduction, degradation of natural resources, and possibilities of indebtedness and the entry of exogenous resources to achieve sustainability (Derner et al. 2017). In rural farms that do not have a commercial orientation, it is linked to the perceptions, attitudes and values established in the rural house, the economic structure of the family farm, the property regime or the conditions of the local labor market (Weltin et al. 2017).

In this community, some farms show adequate production values, such as those identified with case number three and seven, which manage production and feeding with higher assertiveness, with differences in management (table 3).

Table 3 Performance of selected aspects in two farms with different production systems 

Farm three dedicates most of the area in the sowing of forages to compensate the less efficient use of grassland with continuous grazing and use selective defoliation of the trees in the enclosure. While, farm seven rotationally exploits a grassland, where natural grasses predominate and do not use trees for feeding. There are several alternatives to be used, which satisfy the restriction of grazing in the dry season, and use supplementary grazing areas with long cycle species or offer roughage food (Senra et al. 2005).

The global stocking rate, the herd size, while they are related to feeding and technologies, influencing on the production, are conditioned by the rationality which the farm is managed to achieve adequate volumes of annual milk production and meat productivity. The differences are related to the genotypes they use (Calzadilla, 1999c), with the grazing systems (Senra et al. 2005) and the way in which they manage the indexes to control efficiency and sustainability (Senra 2005).

The age and weaning weight, as well as the time the calf stays with the cow, also show different management. The calf rearing is one of the most important aspects of livestock production, since it is the starting point for different purposes, for the production of milk as meat (Calzadilla 1999a). In this sense, the birth rate contributes to the viability, the herd growth and the production of meat via dairy herd.

In both farms, the corporal condition of the breeder is decisive to face the interpartal period, the parturition and the puerperium; as well as age and weight at first parturition, which represent the morphofunctional maturity for reproduction. It is convenient to achieve the incorporation as quickly as possible and take into account the genotype used, without compromising the future development of the animal. It is recommended that the heifers be inseminated at approximately 18 months of age, weighing 70 % of the adult weight (Calzadilla 1999b).

The main differences between both production systems are given by the way in which they order the farm to contribute to the feeding, the genotypes that prevail and the grazing method. These systems do not follow a pre-existing pattern, so in these communities the promotion of innovation and business spirit of farmers is likely to encourage a wider range of farms to diversify (Weltin et al. 2017).

The results indicate that, in the circumstances of the farms located in the southwest of Holguín, the edaphoclimatic conditions, mainly the limited precipitations, do not advise their dedication to milk production. However, the rural livestock emphasis in this purpose, and is conditioned by the characteristics of production, feeding and management, which explain 78.9 % of the total variance of these rearing systems.

To mitigate the impact of the agroecosystem, it is recommended that works in the improvement of processes associated with these three factors by securing a dual-purpose zootechnical flow, with feeding supported by regionalized species that are more productive and with low rotational methods. This ensures the concentration of all activities, in a seasonal manner, and the maintenance of the essential key processes and at a minimum level during the dry season.

It is recommended to emphasize in the evaluation of social aspects of the management of rural farms, as their primary orientation is not commercial. This demands the use of extension practices that elevate social and collective learning, by virtue of an environmental and productive education.

References

Benítez, D., Ramírez, A., Guevara, O., Pérez, B., Torres, V., Díaz, M., Pérez, D. & Guerra, J., Miranda, M. & Ricardo, O. 2008. Factores determinantes en la eficiencia productiva de fincas ganaderas de la zona montañosa de la provincia Granma, Cuba. Rev. Cub. Cienc. Agric., 42(3), 247-253, ISSN:0034-7485. [ Links ]

Benítez, D., Ray, J. V., Torres, V., Ramírez, A., Viamontes, M. I., Tandrón, I., Díaz, M., Guerra, J. & Pérez, D. 2002. Factores determinantes en la eficiencia productiva de los rebaños de fincas ganaderas en sistemas de doble propósito en el Valle del Cauto (Granma), Cuba. Rev. Cub. Cienc. Agric ., 36(3), 217-223, ISSN:0034-7485. [ Links ]

Calzadilla, D. 1999a. Crianza del ternero. Generalidades. In: Calzadilla, D., Soto, E., Hernández, M., González, M., García, L., Campos, E., Suárez, M. A., Castro, A. & Andrial, P. (Eds.), Ganadería tropical, 1st ed., La Habana: Editorial Felix Varela, pp. 91-147, ISBN:959-258-068-5. [ Links ]

Calzadilla, D. 1999b. Manejo de la hembra en desarrollo. In: Calzadilla, D., Soto, E., Hernández, M., González, M., García, L., Campos, E., Suárez, M. A., Castro, A. & Andrial, P. (Eds.), Ganadería tropical, 1st ed., La Habana: Editorial Felix Varela , pp. 148-165, ISBN:959-258-068-5. [ Links ]

Calzadilla, D. 1999c. Características morfológicas y razas del ganado vacuno lechero. In Calzadilla, D., Soto, E., Hernández, M., González, M., García, L., Campos, E., Suárez, M. A., Castro, A. & Andrial, P. (Eds.), Ganadería tropical, 1st ed., La Habana: Editorial Felix Varela , pp. 66-90, ISBN:959-258-068-5. [ Links ]

Cutié, V. & Lapinel, B. 2013. La Sequía en Cuba, un texto de referencia 1st ed., La Habana AMA Sello Editorial, 357 p. [ Links ]

Derner, J. D., Hunt, L., Filho, K. E., Ritten, J., Capper, J. & Han, G. 2017. Livestock Production Systems. In Briske, D. D. (Ed.), Rangeland Systems, 1st ed., Oxford: Springer. 26 p. [ Links ]

Di Rienzo, J. A., Casanoves, F., Gonzalez, L. A., Tablada, E. M., Díaz, M. d. P., Robledo, C. W. & Balzarini, M. G. 2005. Estadística para las Ciencias Agropecuarias 6th ed., Córdoba, Argentina, 329 p. [ Links ]

Espasandin, A. C., Gutierrez, V., Casal, A., Graña, A., Bentancur, O. & Carriquiry, M. 2016. Modeling Lactation Curve in Primiparous Beef Cattle. Journal of Agricultural Science, 8(4), 116-125, ISSN:1916-9760, doi:10.5539/jas.v8n4p116. [ Links ]

FAO. 2013. Milk and dairy products in human nutrition. 1st ed., Roma 404 p. [ Links ]

FAO. 2014. La Alimentación y la Agricultura en América Latina y el Caribe. 1st ed., Santiago de Chile: FAO, 179 p., ISBN:978-92-5-308150-9. [ Links ]

FAO & CLD. 2015. Sustainable financing for forest and landscape restoration: Opportunities, challenges and the way forward. 114 p . [ Links ]

Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. 2010. Multivariate data analysis. A Global Perspective. Pearson Prentice Hall 760 p. [ Links ]

Hernández, A., Ascanio, M. O., Morales, M., Cabrera, A. & Medina, N. 2003. Correlación de la Nueva Versión de Clasificación Genética de los Suelos de Cuba con el World Reference Base (WRB). Nuevos aportes a la clasificación de suelos en el ambito nacional e internacional, 1st ed., La Habana, Cuba: Instituto Nacional de Ciencias Agrícolas, pp. 125-137. [ Links ]

Hernández, A., Pérez Jiménez, J. M., Bosch Infante, D. & Castro Speck, N. 2015. Clasificación de los suelos de Cuba 2015. 1st ed., San José de las Lajas, Mayabeque, Cuba: Ediciones INCA, 91 p., ISBN: 978-959-7023-77-7. [ Links ]

Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvi, A. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978, doi:10.1002/ joc.1276. [ Links ]

IBM. 2013. IBM SPSS Statistics ver. 22.0.0.0, edition of 64 bits for Windows: International Business Machines Corp. [ Links ]

Martínez-Melo, J., Torres, V., Hernández, N. & Jordán, H. 2013. Impact index for the characterization of factors affecting milk production in farms of Ciego de Ávila province, Cuba. Rev. Cub. Cienc. Agric ., 47(4), 367-373, ISSN:0034-7485. [ Links ]

ONEI. 2016. Anuario Estadístico de Holguín 2015 Calixto García. 1st ed., Holguín, 121 p. [ Links ]

Oquendo, G. 2006. Pastos y forrajes. Fomento y explotación. Álvarez, J. L. (Ed.), 2nd ed., Holguín: ACPA, 170 p. [ Links ]

Pérez-Infante, F. 2013. Ganadería eficiente. Bases fundamentales. 2nd ed., La Habana: ACPA, 234 p., ISBN:978-959-307-045-4. [ Links ]

Rodríguez, L., O, M. L., Fonseca, M., Guevara, F., Hernández, A. & Jiménez, M. 2009. Extensionismo o innovación como proceso de aprendizaje social y colectivo. ¿Dónde está el dilema?. Rev. Cub. Cienc. Agric ., 43(4): 387-394, ISSN:0034-7485. [ Links ]

Senra, A. 2005. Indices para controlar la eficiencia y sostenibilidad del ecosistema del pastizal en la explotación bovina. Rev. Cub. Cienc. Agric ., 39(1): 13-21, ISSN:0034-7485. [ Links ]

Senra, A., Martínez, R. O., Jordán, H., Ruiz, T. E., Reyes, J. J., Guevara, R. V. & Ray, J. V. 2005. Principios básicos del pastoreo rotacional eficiente y sostenible para el subtrópico americano. Rev. Cub. Cienc. Agric ., 39(1): 23-30, ISSN:0034-7485. [ Links ]

Verelst, L. & Wiberg, D. 2012. HWSD Viewer Version 1.21. Roma, Italia & Luxemburgo, Austria: FAO/ IIASA/ISRIC/ISSCAS/JRC. [ Links ]

Weltin, M., Zasada, I., Franke, C., Piorr, A., Raggi, M. & Viaggi, D. 2017. Analysing behavioural differences of farm households: An example of income diversification strategies based on European farm survey data. Land Use Policy, 62, 172-184, doi:10.1016/j.landusepol.2016.11.041. [ Links ]

Received: January 18, 2018; Accepted: June 22, 2018

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License