Cuban Journal of Agricultural Science, 50(2): 205-213, 2016, ISSN: 2079-3480

 

ORIGINAL ARTICLE

 

The productive efficiency of rearing herds in Pastaza, Ecuador

 

La eficiencia productiva de rebaños de cría en Pastaza, Ecuador

 

 

D.G. Benítez,^I,III Verena Torres,^II J.C. Vargas Burgos,^III Sandra Soria,^III

^IInstituto de Investigaciones Agropecuarias “Jorge Dimitrov”, Carretera Bayamo-Manzanillo, km 16 ½, Bayamo CP 85100, Granma, Cuba.
^IIInstituto de Ciencia Animal, Apartado Postal 24, San José de las Lajas, Cuba.
^IIIUniversidad Estatal Amazónica, km. 2½, vía Puyo - Tena (Paso Lateral), Ecuador.

 

 

---

ABSTRACT

In order to identify the factors determing the productive efficiency in the rearing- fattening system in Pastaza province, located in the Ecuadorian Amazonia, a non-experimental design was used which controlled the effects of the climatic areas and height levels. For the information processing the Statistical Model of Impact Measuring (MEMI) was applied. It was found that the factors which determine the efficiency of meat production in cattle rearing were reproduction, land relief and looses in the herd, these factors explain 85.54% of the system accumulated variance. These factors are related with the productive process efficiency, relief characteristics, environmental degradation and animals looses. The rearing- fattening systems are classified in four groups, differentiated by the herd size which exploit, the relief where are located, the production process efficiency and the impact they have on the environment. The productive efficiency is low and it correspond with the widespread exploitation alternatives, which are not fit to the environment demands, and with the ability to use the land on which these production processes are developed. It is possible to implement sustainable alternatives of meat production from cattle rearing-fattening systems, if the production systems are fit to the environments demands where these systems are developed.

Key words: animal husbandry, impact model, productive chain, Amazonia.

---

RESUMEN

Para identificar los factores que determinan la eficiencia productiva en el sistema cría-ceba en la provincia de Pastaza, ubicada en la Amazonia ecuatoriana, se utilizó un diseño no experimental que controló los efectos de piso climático y rangos de altura. Para el procesamiento de la información se aplicó el Modelo Estadístico de Medición de Impacto (MEMI). Se encontró que los factores que determinan la eficiencia en la producción de carne en el ganado de cría fueron la reproducción, el relieve del terreno y las pérdidas en el rebaño, que explicaron en conjunto 85.54% de la varianza acumulada del sistema. Estos factores se relacionan con la eficacia del proceso reproductivo, las características del relieve, la degradación del entorno y las pérdidas de animales. Los sistemas cría-ceba se tipifican en cuatro grupos, diferenciados por el tamaño del rebaño que explotan, el relieve donde se ubican, la  eficacia del proceso de producción y el impacto que provocan en el entorno. La eficiencia productiva es baja y se corresponde con las alternativas de explotación generalizadas, que no se adecuan a las exigencias del entorno, y con la capacidad de uso de los suelos donde se desarrollan estos procesos productivos. Es posible implementar alternativas sostenibles de producción de carne a partir de los sistemas ganaderos cría-ceba, si se adecuan los programas de producción a las exigencias del entorno donde se desarrollan dichos sistemas.

Palabras clave: ganadería, modelo impacto, cadena productiva, Amazonia.

---

 

 

INTRODUCTION

The potential for agricultural production of the Ecuadorian Amazon Region (EAR) is limited, due to the edaphoclimatic characteristics of this area. Only a few crops can be easily adapted to extreme climatic conditions and poor agricultural potential of soils (Nieto & Caicedo 2011, Vargas et al. 2015a). From the 413 000 ha declared as agricultural frontier, 85% is used in livestock systems, with growth in the last 13 years of 45 620 ha, representing increases of 70.9% with respect to the surface in livestock use in 2000. This area grows at the expense of the existing forests areas in that year, with impacts that tend to accentuate the environmental deterioration of the EAR, which has a marked influence on the global stability of the planet climate (Vargas et al. 2015b).

The conducting of traditional production alternatives, not suited to the Amazon Biome, when interact with the ecosystems fragility of the province, lead to low production efficiency, a decrease of economic results and the increase of the negative impact of this economic activity in the environment. The alternatives of generalized production are based on tethering grazing. In this type of grazing, the animals stay confined in a certain area, controlled by a rope, which material varies according to the producer possibilities, but it should always be resistant to animals traction during their movement to the fresh grass twice a day and to the permanent humidity conditions  which are subject to. A reduced amount of producers used electrical fences for controlling the animals, and a grass surface per animal similar to the one used in tethering grazing is established.

As grass complement, balanced or concentrates are used which are provided without a rational pattern. The intake frequency of these concentrates varies, from two to three times a week, even once a day. Providing minerals is considered a necessity. Popular formulas in the market are used for this purpose, which design does not consider soil limitations and environmental characteristics of Amazonia.

Pastaza province has 5.9% of the bovine mass from the EAR. The rearing- fattening herds represent 42.6 % of existing farms in the province. It is estimated that has a herd higher to 20.000 heads, they annually produce 1400 calves for fattening and 1020 heads of replacement females, suitable for reproduction (ESPAC 2014).

The objective of this research was to identify the factors which determine the productive efficiency in the primary link of the meat production chain in the rearing – fattening systems in Pastaza, Ecuador.

 

MATERIALS AND METHODS

Pastaza, province from the Republic of Ecuador, is located in the center of the Ecuadorian Amazon Region, between the coordinates 1º 10´ SL and 78º 10 WL and 2º 35´ SL, and 76º 40´ WL. It has 29.773 km² of surface, equivalent to 25.5 % of the EAR and 12 % of national territory. It is characterized by having 81 % of its territory occupied with non intervened woods, which have in their ecosystems an extraordinary richness of natural resources and biodiversity. Due to the nature of its relief, climate and edaphic formation of its woods, it is considered as a fragile territory, especially opposed to the use of economical activities that affect its woods and ecosystems (ATPA 2014).

Diagnosis and survey. A survey with 40 variables was used to evaluate the performance in the productive environmental and economic dimensions of cattle rearing –fattening systems in Pastaza. This tool was applied according to a non-experimental design, which controlled the effects of climatic areas and height levels. These effects determine differences in the edaphoclimatic performance of the territory located in the agricultural frontier of the province, that modify the productivity of cattle rearing ecosystems and animal performance.

Sample size. Farms having a herd of more than 10 cattle heads, and more than five years of consecutive activity were considered as population of this study. The sample size was determined from the 850 farms existing in this territory under the rearing –fattening system(INEC 2015).The maximum variance criterion was applied (Torres 1987, 2015, Snedecor & Cochran 1989) to guarantee an adequate sample size for all the variables to measure. The sample value of s² was considered as 31.2 muestral was considered with 3 % of prefixed error and 95 % of reliability level. The estimated sample size was 170 farms.

The field work demonstrated that in specific sectors the amount of existing farms decreased, due to different causes, associated to the change of productive activity, loss or sale of herds because of the effect of devastating diseases or lack of profitability leading to farm abandonment. The amount of visited farms was reduced to 120 due to these conditions. From the calculated variance for the real sample obtained, the statistics were calculated again and the validity of the sample was demonstrated for the research purpose.

Creation of a data matrix. The surveys information was tabulated in a data matrix organized in Excel. The visited cattle rearing systems were located in lines and the study object variables were located in columns. Each database was strictly examined and those farms that lacked of relevant information were removed, because the survey taker did not specified with precision the section. Besides, the cases in which appeared atypical values or those not having more than five years of consecutive activity and a minimal amount of animals of ten or more cattle heads were eliminated. As a result it was a sample size of 86 farms, which is big enough to endure the evaluation validity of cattle rearing –fattening system in Pastaza province.

Determing factors in the productive efficiency. To identify the variables and indicators which define the main changes in the productive and environmental dimensions, The Statistical Model of Impact Measuring (SMIM) was used (Torres et al. 2013), it also allows to typify the performance of livestock units. The identified groups and the variables of interest that influence on productive efficiency, the negative environmental effect of cattle rearing in the environment and risks associated to sustainability of meat production from the rearing cattle in Pastaza were combined. The data was processed by the statistical software IBM-SPSS 22 (IBM Corporation 2012).

 

RESULTS AND DISCUSSION

The 14% of the territory of Pastaza province is part of the agricultural frontier, 85% of this is used in livestock. The 38% of the land dedicated to livestock systems is located in areas not conducive to the grazing development, increasing conflicts caused by this anthropic activity in an area that must be used to the development of protective forests and forestry.

From the view that the eigenvalue was higher than one, three factors that determine the productive efficiency of livestock systems dedicated to cattle rearing (table 1) were identified. The first component, which is the reproduction, is related to management indicators that define the reproductive efficiency, and contributes 44.75% of the accumulated variance explaining the fitted model.

The reproduction is the livestock process that defines the herd structure, the relative production potential that is expected to be obtained, the feeding program set up to ensure high and stable productions, the health system modeling, the expected sales volume, the insurance which should provide for the farm management and production practices that must be set for the optimal system performance (Benítez 2010, Moreno et al. 2011, FAO & FIL 2012). It also defines part of the productive potential of the farm, as it determines the number of calves sold or used for the fattening process in the beef production, which is associated in turn with the birth of herds or the number of births that are obtained for every hundred females in reproduction for a certain period (Benitez 2010, Viamonte 2010).

Reproductive efficiency is determined, in turn, by the method used to serve female reproducers, by the body condition of herds, which reflects the feeding program and the sire quality. The 75. 6% of rearing herds are served by the mating system. In 82.6% of these cases the reproductive method of intensive reproduction is used to gestate the female reproducers, which is proven if quality sires are maintained and it is efficiently conducts the sire management (Viamonte 2010).

With the relief land component is explained up to 66.93 % of the accumulated variance by the fitted model. This component is related to variables that indicate the environmental situation of these livestock systems. The land slope, the rainfall pattern, the maximum intensity of rains that fall during the rainy season, the infiltration capacity of soil and the land covering conditions the erosion danger, which expressed by gullies or furrows which are forms perpendicular to the slope in the grazing lands. The extension and intensity of the erosion increase as the land slope increases. With the land slope exponentially increases the speed of drainage, the rain erosive ability and land degradation associated to these natural phenomena (FAO 2000, Murgueitio et al. 2006, Ibrahim et al. 2007).

The degradation by erosion is also related to the area percentage considered adequate for grazing, which are those with slopes lower than 30 %. In Pastaza, 38 % of the area in livestock use are in slopes not recommended for grazing, and 45 % on slopes ranging between 15 and 30 %. These land characteristics exacerbate the erosion danger of a territory whose rainfall pattern varies from over 5000 mm per year on the climate areas Montano Bajo until 3500 mm annual near the Amazon plain (Benitez 2015).

The third component, which corresponds to losses in the herd, is related to deaths occurring during the year in all existing categories and deaths caused by accidents. This phenomenon occurs when the animals which are subjected to tethering on rough slopes try to reach fresh grasses and fall, breaking his spine. Accidents represent 86.5 % of the losses in livestock rearing from Pastaza province (INEC 2015). With this component is explained 85.54 % of the accumulated variance of the model.

Figure 1 shows the impact of these components on each farms evaluated in the rearing-fattening system, where each farm represented on the x axis obtains three indicators in a scale of values that indicates their relative situation regarding the rest of the evaluated farms, which are represented by colored bars in the y-axis. Figure 2 shows the hierarchical cluster obtained by grouping farms from the impacts of the identified components and when selecting a differences index of 55.43. Table 2 shows the rearing-fattening systems classification in Pastaza.

The first group constitutes 43% of the evaluated systems. It consists of farms that are located 855± 239 mo.s.l on slopes of 21 ± 11 %. They cover an area in animal husbandry of 22.4 ± 12.9 ha, with 79 % of own area for grazing and has 13 ± 10.3ha of forest and 0.8 ± 0.9 ha in crops. The herd is 19 ± 11 heads, of which 42 % are cows. The birth rate is 63 ± 22% and the stocking rate 1.2± 1.4UGM.ha^-1, higher than the capacity supported by the system, so that producers are forced to lease an area, equivalent to 9.3% of the exploit area, to complete the biomass deficit of their respective livestock systems.

The second group corresponds to 4.7 % of the evaluated systems. They are farms that are located at 903 ± 35 77 mo.s.l on slopes  of  35± 17 %, covering an area of 42.5± 34 ha, with 33.8% of own area for grazing. They have 13 ± 11.6 ha of forest and 1.5± 1.3 ha in crops. Their herd is 55 ± 41 heads, of which 38.2 are cows. The birth rate is 67 ± 23 %, with stocking rate of 1.4±1.1 UGM.ha^-1, much higher than the capacity supported by the system, so that producers complete the biomass deficit of their systems with a surface lease equivalent to19.5 % of the exploit area. The relief characteristics and the biomass production are reflected in the body condition of the herd, which is evident in a poor feeding.

The third group consists of 43 % of the evaluated farms, which are located at 974 ± 119 mo.s.l on slopes of 47 ± 16 %, which cover with animal husbandry an area of 26.7 ± 15.4 ha, with 31.2% of own area for grazing. They have 14.6 ± 12.2 ha of forest and 1.4 ± 1.3ha in crops. The herd is 18 ± 8 cabezas, of which 33.3 % are cows. The birth rate is 73 ± 22 %, the stocking rate is 0.8 ± 0.4 UGM.ha^-1and leases the equivalent to 9 % of the area exploiting to complete the biomass lack of the livestock system. The body condition of the herd is about 2.8 units.

The fourth group is 9.3% of the evaluated farms, which are located at 897 ±268 mo.s.l on slopes of 32 ± 15%. They cover in livestock activity an area of 60.8 ± 44.4 ha, with 70.9 % of the area for grazing, they have 14.6 ± 12.2 ha of forest and 1.4± 1.3 ha in crops. Their herd is 67 ± 9 heads, of which 47.8 % are cows. The birth rate is 70 ± 22 %, the stocking rate is 2.0 ± 2 UGM.ha^-1 and leases the equivalent to 19.4 % of the area exploiting to complete the biomass deficit of their livestock systems. The body condition of the herd is about 3.4 units. By the extension of their farms, producers reach the highest sales volume of cattle.

 

CONCLUSIONS

Factors determing productive efficiency of cattle rearing fattening systems in Pastaza province, as well as the classified farms groups, are related to the effectiveness of the productive process and the characteristics of land relief, which is related to environment degradation and looses in the herd.  

The productive efficiency which is obtain in livestock rearing -fattening systems in Pastaza province is low and is related to alternatives of widespread exploitation, which do not suit to the environment needs and the capacity of soil use in which these production processes are developed.

It is possible to implement sustainable alternatives of meat production from livestock rearing-fattening systems, if production programs are adapted to the environment where these systems are developed.

 

REFERENCES

ATPA 2014. Reconversión Agroproductiva Sostenible en la Amazonía ecuatoriana. Quito: Ministerio de la Agricultura, Ganadería, Acuacultura y Pesca, p. 91, Available: <http://www.desarrolloamazonico.gob.ec/atpa-agenda-de-transformacion-productiva-amazonica-2/>, [Consulted: April 12, 2016].

Benítez, D. 2015. “Los ecosistemas en uso ganadero en Pastaza”. In: Retos y posibilidades para una ganadería sostenible en la provincia de Pastaza de la Amazonia ecuatoriana, Puyo, Ecuador: Universidad Estatal Amazónica, p. 174, ISBN: 978-9942-932-16-7.

Benítez, J. D. G. 2010. Tecnologías para la producción ganadera sostenible en ecosistemas frágiles y degradados. Cuba: Bayamo, 190 p., ISBN: 978-959-223-183-2.

ESPAC. 2014. Bases de datos. Encuesta de Superficie y Producción Agropecuaria Continua (BBD). , Available: <http://www.ecuadorencifras.gob.ec/encuestas-de-superficie-y-producción-agropecuaria-continua-bbd/>, [Consulted: November 30, 2015].

FAO 2000. Manual de prácticas integradas de manejo y conservación de suelos. vol. 8, FAO, 240 p., ISBN: 978-92-5-304417-7, Available: <https://books.google.com.cu/books/about/Manual_de_pr%C3%A1cticas_integradas_de_manej.html?id=-kZCpFv-W1EC&redir_esc=y>, [Consulted: April 4, 2016].

FAO & FIL 2012. Guía de Buenas Prácticas en Explotaciones Lecheras. (ser. Directrices FAO: Producción y Sanidad Animal, no. ser. 8), Roma, Italia: FAO, ISBN: 978-92-5-306957-6, Available: <http://www.fao.org/docrep/015/ba0027s/ba0027s00.htm>, [Consulted: April 10, 2016].

IBM Corporation 2012. IBM SPSS Statistics. version 21.0, [Windows], Multiplataforma, U.S: IBM Corporation, Available: <http://www.ibm.com> .

Ibrahim, M., Villanueva, C. & Casasola, F. 2007. “Sistemas silvopastoriles como una herramienta para el mejoramiento de la productividad y rehabilitación ecológica de paisajes ganaderos en Centro América”. Archivos Latinoamericanos de Producción Animal, 15 (Supl. 1): 74–84, ISSN: 1022-1301.

INEC, 2015. 2015. Índices de la Actividad Económica. , Available: <http://www.inec.gob.ec/estadísticas/>, [Consulted: April 12, 2016].

Moreno, S. J. A., Alcalzar, A. H. & Guzmán, G. M. 2011. Ganadería Ecológica: Manejo reproductivo de la hembra bovina. Tanijo J. C. & Cardona O. (eds.), 2011: Cieniagro, ISBN: 798-3-8442-0470-4.

Murgueitio, E., Cuellar, P., Ibrahim, M., Gobbi, J., Cuartas, C. A., Naranjo, J. F., Zapata, A., Mejía, C. E., Zuluaga, A. F. & Casasola, F. 2006. “Adopción de Sistemas Agroforestales Pecuarios”. Pastos y Forrajes, 29 (4): 365–381, ISSN: 2078-8452.

Nieto, C. C. & Caicedo, V. C. 2011. Análisis reflexivo sobre el desarrollo agropecuario sostenible en la Amazonia ecuatoriana. (ser. Publicación Miscelanea, no. ser. 405), Joya de los Sacha, Ecuador: IINIAP-EECA, 102 p.

Snedecor, G. W. & Cochran, W. G. 1989. Statistical Methods. 8th ed., Iowa State University Press, 503 p., ISBN: 978-0-8138-1561-9, Available: <http://www.amazon.com/Statistical-Methods-George-W-Snedecor/dp/0813815614>, [Consulted: April 4, 2016].

Torres, C. V. 2015. “Aspectos estadísticos a considerar en el diseño, muestreo, procesamiento e interpretación de datos en la investigación de sistemas productivos agropecuarios”. In: Retos y posibilidades para una ganadería sostenible en la provincia de Pastaza de la Amazonia ecuatoriana, Puyo, Ecuador: Universidad Estatal Amazónica, p. 174, ISBN: 978-9942-932-16-7.

Torres, V. 1987. “Método visual para estimar la disponibilidad del pasto. 2. Determinación del tamaño de muestra”. Cuban Journal of Agricultural Science, 21 (2): 117–121, ISSN: 2079-3480.

Torres, V., Cobo, R., Sanchez, L. & Raez, N. 2013. “Statistical tool for measuring the impact of milk production on the local development of a province in Cuba”. Livestock Research for Rural Development, 25 (9)ISSN: 0121-3784, Available: <http://www.lrrd.cipav.org.co/lrrd25/9/torr25159.htm>, [Consulted: April 8, 2016].

Vargas, J., Benítez, D., Bravo, C., Leonard, I., Pérez, M., Torres, V., Ríos, S. & Torres, A. 2015a. Retos y posibilidades para una ganadería sostenible en la provincia de Pastaza de la Amazonia ecuatoriana. Puyo, Ecuador: Universidad Estatal Amazónica, 174 p., ISBN: 978-9942-932-16-7.

Vargas, J. C., Benítez, D. G., Verena, T., Ríos, S. & Soria, S. 2015b. “Factores que determinan la eficiencia de la producción de leche en sistemas de doble propósito en la provincia de Pastaza, Ecuador”. Cuban Journal of Agricultural Science, 49 (1): 17–21, ISSN: 2079-3480.

Viamonte, M. I. 2010. Sistema integrado de manejo para incrementar la productividad en vacas  de la raza Criolla cubana. Ph.D. Thesis, Universidad de Granma, Bayamo, Granma.

 

 

Received: 25/11/2015
Accepted: 20/6/2016

 

 

D.G. Benítez, Instituto de Investigaciones Agropecuarias “Jorge Dimitrov”, Carretera Bayamo-Manzanillo, km 16 ½, Bayamo CP 85100, Granma, Cuba. Email: [e-mail]