Study area

The study was conducted in the municipalities of Marcos Castellanos, Sahuayo, Briseñas, Villamar and Jiquilpan, belonging to DDR 089 Sahuayo, in the state of Michoacan.

The aforementioned municipalities comprising the area of influence of the GGAVATT study. This DDR provided little more than 23% of the volume of production of bovine milk in the state of Michoacan; the average volume for the period 2002-2011 amounted to 759 539 thousand liters (^{SIAP, 2012}).

Case study. Milk producers Cienega Chapala region, Michoacán

The subjects considered in the context of the case study are agro-entrepreneurs producers cooperating milk with GGAVATT Michoacan state, because in the state, the dairy chain is short and, considering the technology used, undeveloped. Of the total milk produced in the state, 60% is marketed by Shoemakers, 38% processed and sold by pasteurizing plants and the other 2% by dairies, it is considered that the consumption of "raw milk" is still important in the state (^{Bello, 2009}). The total of the surveys totaled 95 and for purposes of this study, data from 81 dairy farmers only resumed (by problems of insecurity, failed to realize the visits UP 14 farmers), obtained through interviews and monitoring of the adoption of innovations inUP.

Design and development of data collection instrument

The design and formulation of data collection instrument, was conducted jointly by farmers, decision makers, consultants, research and innovations proposed by the INIFAP resumed. Paragraphs considered were: i) general data of agro-entrepreneur and GGAVATT group; ii) dynamic activity, which refers to the municipality and village location, area for the production, marketing channel; iii) dynamics of innovation, where from the development and integration of a technology package (proposed by INIFAP) was the respondent asked whether practical or not given innovation, if you practice this innovation are asked the year of adoption thereof and learning source, characterized depending on the type of actor and iv) the type of links with the network of actors, and these kinds of social, innovation and production leaders.

Sampling model

The Ministry of Rural Development (SEDRU), with offices in Morelia, Michoacan provided databases of livestock discharged until 2012 depending on the variable "number of animals", for stratified samples with which to work.

The pattern provided by the SEDRU, and municipalities where covered by the study, amounting to a total of 934 milk producers, of which 253 belong to stratum I, 286 to II, 314 to III and only 81 farmers to IV; strata were formed depending on the variable "number of heads"; for stratum I, here everyone livestock that has 1 to 25 animals, for the II of 26-50 animals, 51-100 III, and IV with more than 101 animals (Table 1) it is grouped. The following sampling model was used.

Table 1 Sample size per stratum. 

Fuente: elaboración con datos de 2012, proporcionados por la SEDRU de Morelia y aplicando la fórmula del modelo de muestreo.

Stratified sampling is the sampling unit’s conglomerar groups called strata. The sample size was calculated with the following expression:

Where: n= number of players to be surveyed; N= total number of players in the population; d= precision (expressed in percentage): 10% = 0.1; Z = reliability: 90% = 1.64; S ² p= weighted variance of the population; and μ= mean of the sampling variable.

Formulation and shaping technology package

The GGAVATT model proposed by the INIFAP brings together a total of 22 innovations sorted by categories with the following distribution: i) management/organization / market five innovations; ii) breeding and genetics four innovations; iii) facilities/hygiene four innovations; iv) nutrition four innovations; and v) health five innovations.

Table 2 Total surveys conducted in each municipality, according stratum. 

Fuente: elaboración con datos de 2012, proporcionados por la SEDRU de Morelia.

Capture field data

The questionnaires were applied in 2012 and 2013; employing, the perspective of innovation networks. The data capture process is divided into two parts, the first comprising the following sections: i) general data; ii) dynamic activity; iii) dynamics of innovation; captured in a spreadsheet of Microsoft Office Excel 2007, whereas paragraph; and iv) types of links, was captured in Microsoft Notepad version 6.1 condition using the DL protocol and edgelist format, not without first forming a catalog that accounts for the identifiers (ID) used by each node or interviewed actor and referral and chord profile (Table 3) al. The edgelist format allowed capture the relational links between the actors identified in the innovation network of milk producers in the state of Michoacan and the generated file in Notepad (word processor) was plotted in NetDraw 2 098 (^{Borgatti, 2002}).

Table 3 Catalog actors. 

Fuente: ^{Rendón (2007)}.

Indicators used

Grade: the grade is the number of relationships that an actor possesses. An actor with a high degree is one that shows high number of relationships. The degree (G) is equal to the sum of the relations between on the actor (i) and the rest (j) and is calculated as follows (^{Wasserman and Faust, 1994}):

Specifically, the degree of entry indicates the number of relationships with other actors say keep the actor in question (n) and is calculated as follows:

While the level of output represents the number of relationships that the actor claims to have analyzed the rest (n), calculated as follows:

The data generated (input and output degrees) were analyzed with a completely random statistical design, through analysis of variance with the GLM procedure; means were compared with Tukey test with α to the 0.05.

Closeness: is the ability of a node to access the rest of the players on the network using the geodesic distance; that is, the shortest distance between two nodes considering the number of relationships, so that an actor with high closeness shows the ability to access much of the network efficiently or by few relationships. In this sense, it is considered that an actor is "close" to the extent that its strategic position in the network structure allows you to link up with as many players in the same network, and therefore is able to obtain and send information. The expression of closeness is:

Where: K is a node and Dgeodk is the sum of the geodesic distances K node to all other nodes connected and "n" is the number of actors in the network; ^{Faust and Wasserman(1994)}; ^{Rendon et al. (2005)}. The data obtained (closeness) were analyzed with a completely random statistical design, through analysis of variance with the GLM procedure; means were compared with Tukey test with α to the 0.05.

Density: is the percentage of relationships between possible. High densities expressed broad access to available information. The mathematical expression is:

Where the density (D) is equal to the number of relations (L) between the numbers of possible relationships g (g- 1). The density is expressed as a percentage: a density of 100% indicates that all actors are related; a density of 0% indicates that all players are loose (^{Wasserman and Faust, 1994}).

Inai: it is considered the technological level of agricultural entrepreneurs individually, depending on the type of technology developed technological package. The InAI_K is the Innovation Adoption Index in the "K" technology and was calculated as follows:

Where: Xi is innovation "i" in the "K" technology and "n" is the number of innovations in category "K" (^{Muñoz et al., 2004}).

There are two types of key players, namely diffusers and arrangers.

The diffusers are that group of nodes whose position in the network allows them to send information to the most nodes. Meanwhile, the arrangers are those that disappear if the network would remain mostly fragmented (^{Rendon et al., 2007}). Input grades showed significant differences (p> 0.05) in the five boroughs; output grades and proximity were different (p<0.05) compared to the comparison by municipalities. The comparison of the values in the output level indicator in the municipalities Briseñas vs. Villamar of 16.829 and 8.385, indicates that producers begin to look for information on other producers, professional service providers, input supplier, among others (Table 5).

Table 5 Selected network of milk producers cooperating with GGAVATT of region Cienega of Chapala, Michoacan. 

*a, b: medias con letras distintas en hileras son estadísticamente diferentes (p> 0.05 y p< 0.05).

The adoption of some of the 22 integrated in the technology package are reported as InAI, innovations evidence that tecnológicoes level of 8.04 (Villamar, municipality with lower adoption) to 12.50 (Jiquilpan, municipality with the highest adoption) innovations adopted (Figure 1). Speaking time GGAVATT model, with farmers was July 2008 to July 2011.

Figure 1 Index adoption of innovations (InAI) average per municipality of milk producers network, cooperating with GGAVATT of region Cienega of Chapala, Michoacan. 

The absence of organization, management and market niches are some of the great evils afflicting dairy farming in the study area; however, they do not see as a viable option teamwork (Figure 2). The categories of health, breeding and genetics, are those with the highest percentage of adoption; however, they are also activities that require greater financial investment. It is estimated that health and nutrition can represent 60% of the total costs of a dairy farm, and this increases when no administrative records of the UP are carried.

Figure 2 Percentage of adoption of innovations by category. 

The main problems of farmers in the study communities are: i) organization, -: not to any group that is currently running is found as such; ii) administration, -: few farmers keep records or technical accounting logs, and those who performed usually are managers or jeans, though their records are very incipient or misinformed; and iii) market, -: only those who produce large volumes of milk can sell directly to industries, however the vast majority sells to intermediaries; although climatic conditions in the region, many farmers cannot establish niche markets as their production volumes are not constant throughout the year.

To continue in the cattle activity, farmers must accept the challenge of converting traditional production systems efficient and cost-effective systems modify traditional production practices and apply management concepts, supported by the necessary investments. Therefore, for the ranches cattle breeders in the study area, both business and family farms, to ensure their long-term permanence producing and generating jobs, income and welfare, it is essential to work in an organized manner and adopt a management scheme that includes processes of planning, monitoring, technical and economic evaluation of the activities of the ranch, as regards the GGAVATT model.

One of the impacts of the model in the study communities, is seen in the number of liters of milk sold per day; thus, the average liters for farmers (of the five municipalities under study) were in a group was 215.05 liters, while for non- GGAVATT was only of 161.65 liters; the following impact is given by the selling price per liter of milk it was $ 5.23 for the GGAVATT group and only $ 5.08 for Non-GGAVATT. These two noticeable impacts between groups can be product of the number of innovations carried out farmers belonging to any group GGAVATT perform 51.55% of the proposed innovations, while non-GGAVATT only those performed in 44.89%. Technologies proposed by the INIFAP, were grouped into: health 74.15%; reproduction- genetic 66.46%; 51.22% nutrition; installation- hygiene 39.63% and 26.83% only in organization- management- market; percentage of innovations that adopt agro- entrepreneurs study (Figure 2).

The few results demonstrated in the municipalities evaluated, are due to, recorded a dynamic passive adoption, i.e., the producer is not aware of inputs (technical assistance) used in such a way that when the subsidy is suspended, invariably occurs the abandonment of innovations. In addition, there is no rationality in the dynamics of adoption, because regardless of the quality of the input subsidized, the producer uses the input just because of being subsidized, reinforcing the inefficiencies.

If innovation means the commercial application of an idea, this means that the concept covers the entire spectrum of functional activities of a company or UP, which boasts implement changes or innovations in the way of farming and livestock, both as regards the products offered, as the way in which resources are managed organized and marketed goods. As a result, when the management strategy innovation focuses only on the technological side, invariably it happens that there is no connection market that encourages innovation. Therefore, it often happens that excellent results are achieved in terms of productivity and quality, but a lousy business performance failing to find a profitable outlet for production.

In the dairy Cienega Chapala basin, Michoacan; ^{Ruiz (2007)} conducted a comparative study between two groups of farmers in the municipalities of Villamar and Venustiano Carranza, the latter at the time working with the GGAVATT model. The results of their study indicate that those farmers who work with the model recorded higher production, reproductive indicators, marketing, infrastructure and quality improvements herd. However, their study did not compare GGAVATT groups from other municipalities, such as the present where you are comparing groups of farmers who were working with the model and those who were not. So far only have these investigations and it is advisable to do more work of this type, in order to have more information how they worked the other GGAVATT groups, for species of cattle meat, dual purpose cattle, sheep, goats, pigs, birds and bees, which were operating in the state of Michoacan.