Area and study universe

The study area was constituted by the Centre of Mexico Region, comprising six states: Guerrero, Hidalgo, State of Mexico, Morelos, Puebla and Tlaxcala; and it provides about a quarter of the national maize production. The interviewed 490 corn growers attended by technicians MasAgro 2012 program, and distributed in 69 municipalities in the region.

Information collection instrument

The survey of producers consisted of three sections: features producer and unit production, technologies or innovations and learning resources of each of the innovations. In the first section, data for identifying the producer asked: name, age, education, water regime, surface, yields, among others. The second refers to the set of 29 innovations for better performance or high impact on corn production; classified into six categories: agronomic management, nutrition, health, machinery and equipment, financing and organization. The third section focused on analyzing the links learning or information sources of the producer with the other actors in the system, such buyers, professional service providers, government institutions.

With the information gathered from surveys to producers built a database in Excel^® and Notepad with the links between the actors. The notepad file was imported directly into the NetDraw 2.083^© and Ucinet 6.211^©, for the identification and analysis of innovation system actors in the region.

Indicators used

To assess the degree of adoption of innovations producers, the following indicators were calculated:

Rate of adoption of innovations (InAI). It is the average of practices carried out by the producer, for each of the producers is the average of the values of the rate of adoption of innovations by category (IAIC), and is constructed by the following expression percentage (^{Muñoz et al., 2007}):

Where: InAI_i= rate of adoption of innovations i-th producer; IAIC_ik= adoption rate of i-th producer in the k-th category; and K= total number of categories.

Rate of adoption of innovations (TAI). Percentage of Adopters producers of each innovation (^{Rogers, 2003}), is calculated using the formula:

Where: nPA= number of adopters producers of innovation; and nTP= total number of producers.

Analysis of the information

Statistical analysis of data was processed in the SAS software v. 9.0. To observe the differences or similarities regarding the characteristics of the producer and production units, as well as its level of innovation a comparison of means was performed using ANOVA analysis. For the analysis of the actors involved in the innovation system corn graphical analysis it was used by NetDraw 2.083 software. The Pearson's correlation with existing or no relationship between the links of the different actors sources of innovation that keeps the producer of corn was assessed. Finally, with a linear regression model the degree of influence of each type of link on the adoption of innovations by the producer was measured.

Features producer and unit production

The corn farmers in the Central Region of Mexico are mostly elderly, with the state of Hidalgo which has the highest average 53 years, nine years longer than the producers of Puebla, the youngest 44 years. Although states differ in the age of their producers they were not statistically significant. Regarding the level of schooling, it highlights the state of Morelos with an average of 11 years of schooling equivalent to second year of high school level, schooling status high above other states. It is followed by Tlaxcala with 7.6 years of schooling, which is equal to the first year of secondary education their average differs from the other states except Hidalgo, with which no statistically significant differences. Producers who have a lower level of education are the states of Puebla, Guerrero and Mexico State, on average schooling it is equivalent to incomplete primary. It is noteworthy that these two characteristics of users are important, as they are a determining factor that could influence their decision to use certain technologies (^{Perez and Terron, 2004}).

Another important feature is the area sown with maize crop, producers of Tlaxcala have an average of six hectares planted with maize cultivation, average statistically different from the state of Puebla and Guerrero, who have a lower surface with 2.8 and 2.3 ha respectively. Farm size could be an obstacle to innovation (^{Didier and Brunson, 2004}) because if it is small could be unprofitable introduce certain practices. On average yield per hectare of Puebla, Hidalgo and Tlaxcala states had the lowest yields in 2011. The state of Morelos had a mean achievement in their statistically different from the other producers. In the case of the State of Mexico its average was 1.7 t ha^-1, and this showed no statistically significant differences with Guerrero and the three states with the lowest averages.

In general, the states of Puebla, Hidalgo and Mexico State showed the lowest averages in schooling, planted with corn and yields per hectare surface. In Guerrero although producers have low education levels and lower planted area, occupied the second place in yields in the previous cycle with 2.54 t ha^-1, which could point to a more intensive type of production. Tlaxcala producers have increased plantings and a higher degree of schooling, but their yields are lower.

Degree of innovation adoption by agribusinesses

In innovations region with the highest rate of adoption they were: weed control with 69%, use of improved seed with 49%, use of organic fertilizers with 44% and 43% fractional fertilization adopter. These innovations have the characteristics of easy experimentation, visible results and low investment, attributes decisive in the decision to adopt or not the producer (^{Rogers, 2003}). Unlike other innovations whose adoption rate was less than 3% of adopters, as it was: permanent beds type of irrigation technology, use of domestic seed, ground leveling and using infrared sensors. The requirement for application expertise and investment required for their application, which could be hindering its adoption by the farmer.

Table 1. Characteristics of the producer and unit production by state. 

Regarding the adoption rate by category of innovation (InAI) producer, the highest average was obtained by the state of Morelos with 53.6% in the six categories of innovation showed statistically significant differences with other states. He followed in order of importance the state of Tlaxcala with InAI 26.4%, much favored by the categories of funding and organization. The State of Mexico, Guerrero and Puebla had the lowest adoption of innovations among its producers, mainly in the categories of machinery and equipment, organization and financing. The Hidalgo state had an average of 20% InAI, which does not differ statistically from InAI of Tlaxcala but neither of the three states with the lowest InAI.

Innovations category health on average had higher adoption by the producer in the region with 43% refers to the practical control of weeds, diseases and pests; and he was followed by the category of agricultural management with 29% which includes minimum tillage, use of cover crops, use of improved seeds, crop rotation association and innovations.

Agri-business connectivity

Analysis of the Central Region includes information from six states (Puebla, Tlaxcala, State of Mexico, Morelos, Hidalgo and Guerrero) and 69 municipalities. With the analysis of the innovation system of corn producers they were identified 1 089 players in total Region, of which 58.1% are producers or Rural Business (ER), 17% family (FAM) of these producers ( FAM) and 1.3% producer organizations (OR), which states in the region a strong tendency for corn growers to consult among themselves on innovation. An important aspect to note is the presence of actors of institutional support for innovation, as is the identification of 160 (14.7%) professional service (PS) in the area, providing technical assistance and training and a source of information innovation for corn growers. As well as the participation of 26 (2.4%) Government Institutions (IG), eight (0.7%), financial service providers (PF) and seven (0.6%) institutions of education and research (IE). In addition, the participation of input suppliers 3.9% is noted, and some actors multifunctional (FM) with 0.9% and customers (CI) with 0.3%.

Table 2. Adoption of innovations among corn producers in Mexico Centro Region. 

In the state of Guerrero information in 17 municipalities rose, includes 408 nodes or actors, among them, there are 549 technical learning relationships of different innovations. The system of sources of learning for innovation is in most in an integrated structure, there is nonetheless a subset of isolated actors and some companies off line. In the State of Mexico the information corresponds to eight municipalities, with a total of 180 actors and 197 relationships in your system. The structure is diffuse, fragmented and with a large number of single nodes, which can be explained by two reasons, the first is the geographical dispersion and the second is the possible absence of articulators actors inside. The state of Tlaxcala integrates information from 12 municipalities, the system is formed of 143 actors and 218 links, is split into six sub-groups; an important aspect is that there are no loose nodes (nodes that are not connected with others), indicating that producers recognize the importance of information shall cleave to learning related to corn production innovations.

In Puebla information was obtained 21 municipalities, has a number of relationships 257 and 222 actors. The system structure is diffuse, but inside more than ten small clusters of actors are distinguished, which could be explained by the geographical distance. Morelos information in six municipalities analyzed, 72 nodes with 199 relationships (Figure 1) were identified. The system is more cohesive part, and an important thing to note is that unite for the role five articulators actors, these actors are important in implementing projects dissemination of technologies. In the state of Hidalgo, the lowest number of surveys (25) rose in five municipalities; and therefore resulted in a number of 47 actors and 52 links. There are two isolated nodes or that do not connect to other actors and five small subgroups which shows its high fragmentation of it. This could possibly be attributed to lack of further information.

Figure 1. The system of sources of learning for innovation corn growers in the Central Region. 

In general, each system structure influences range of producers to information and knowledge for innovation; however, we can identify actors with local importance because of their number and position of links in the network. Likewise, the role of articular structures could well correspond to the different actors of institutional support, which are mainly four: institution of education and research (IE), the government institution (IG), a provider of professional services (PS) and financial service providers (PF).

Institutional support actors in the innovation system

In the Central Region, the actors who dominate the innovation system corn growers are other rural agribusinesses with 50%, and are a primary source of information for innovation, which shows little diversity of sources of learning in some states. In the case of Puebla, Tlaxcala and Hidalgo states, second place is occupied by professional service providers (PSP) with 17% on average. In the state of Guerrero and Mexico State there is a strong inf luence of family on the producers concerned of innovation, with 23% and 18% respectively, and in third place are PSP with 13%.

Regarding the link that keeps the farmer with each type of actor, in the states of Morelos and Hidalgo linkage with government institutions (IG) as 36.9% and 25% of the actors mentioned relate to this category stands out; in the other states participating is between 1 and 2%. Educational institutions and research (IE) only participate in Tlaxcala with 6.5% and Guerrero with 1.1% and, indicating a low linkage with the sector although its presence should highlight its role in the development of knowledge and information on new technologies. Other institutional actors are important providers of financial services (PF), those providing insurance and financing to rural enterprises for the production of corn. However, only three of the six states producers are linked to this type of actor, with 8.3% in Tlaxcala, Puebla and Guerrero 4.4% to 0.8%.

In general, one could say that the state of Guerrero and Tlaxcala have the participation of the four types of actors of institutional support, which makes more diverse your system to generate innovation. The State of Mexico tends to a more homogeneous system due to the low participation of other actors as a source of innovative knowledge for corn producers.

In the case of Hidalgo and Tlaxcala states it has low link between producers, which makes them an unbalanced system in its internal and external sources of innovation. Guerrero state has the innovation system more balanced since almost half of its links are internal or with other producers and the other half to corresponding external agents including institutions and institutional support and IP and FM.

Association between types of links supporting actors

The links of producer statistically significant association were those of professional service and government institutions, financial producers and teaching and research, the above could be attributed to the fact that these act as intermediaries between institutions and farmer. Which suggests that closer links with the PS is more likely linked to the producer of such institutions. It is worth mentioning that although the degree of association is significant (p< 0.05) is also weak.

Linking producer with institutions Financial Products is associated with PI, PS and IE actors; that is, a greater connection with this type of major actors will be the link with any institution of credit or crop insurance. This could be for the flow of information provided by these actors about the financing options the producer. As a negative correlation between these institutions and actors found multifunction, however although significant is very close to zero which is not considered relevant.

Table 3. Diversity of links in the innovation system corn producer. 

The corn producer is linking with government institutions is related to linking with other producers (family and producer organizations) and PI. What could be explained to access some of the support granted by these institutions as it is technical assistance and training and supply of inputs, producers have to organize or linked together to access them, and also to look for options to purchase supplies.

Table 4. Association between learning links for innovation corn producer. 

Influence of each type of link to the adoption of innovations producer

In the linear regression model the contribution that the link of each type of actor institutional support in the adoption of innovations corn producer is observed. The actors proved to be most important government institutions, as each additional link to be established with any of them, the adoption of innovations corn producer will increase by 8.50 percentage points. Educational institutions and research, have great potential to become one of the main sources of knowledge and learning for farmers. However, they have little presence in the innovation system, so far there are few who perform the work of extensionism, especially institutions of higher education should play a central role in this process (^{Mungaray et al., 2011}). Institutions financial products related to the use of credit insurance and granting producer occupy the fifth position according to the value of the β coefficient. So it follows that for each additional link established producer with this type of actor degree of adoption will increase by 5.19%, mainly in the category of innovation financing.

Providers of professional services are the actors who provide advice and training to farmers, and were expected to have the highest coefficient or effect on the adoption of innovations by the producer because of its role as intermediary, to its proximity to the producer and number existing in the states. However, for each link to increase or establish the farmer with PS, adoption of innovations to increase by 4.3 percentage points.

There are other actors such as input suppliers and multiple functions that also have an important role in the adoption of innovations by the producer of corn. However, in the first case because the business relationship with the former should pay attention to the type of provides recommendations and in the second, it is understood that because of its various functions these actors play a strategic role in the system innovation. In the above sense, the important role that actors of institutional support, as other producers maintain only homophilic links among their peers or their level of innovation will be slightly favored it shows. Therefore, it is also necessary to establish links with external agents that help stimulate innovation in its production unit.

Table 5. Influence of each type of link in the adoption of innovations corn producer.