Introduction
A smallholder farming system is considered as a set of resources organized, managed, and adopted by farmers that involves selection of crops, livestock, agricultural, and non-agricultural businesses. These systems in developing countries are facing challenges in adapting to new circumstances and incorporating new technologies on the farms (Kuivanen et al., Reference Kuivanen, Alvarez, Michalscheck, Adjei-Nsiah, Descheemaeker, Mellon-Bedi and Groot2016).
More than 750 million people around the world are dedicated to small-scale dairy production. This activity contributes to creating jobs and reducing poverty and hunger in developing countries (FAO, 2019). Thus, small-scale dairy systems have been considered as rural development option in rural areas (Espinoza-Ortega et al., Reference Espinoza-Ortega, Espinosa-Ayala, Bastida-López, Castañeda Martínez and Arriaga-Jordan2007). These systems have specific infrastructure, technical and economic constrains that can limit their capacity to adopt new technologies (Bernués and Herrero, Reference Bernués and Herrero2008); however, farmers with the biggest farms were better able to support risks and were more likely to try new technologies (Espinoza-Ortega et al., Reference Espinoza-Ortega, Espinosa-Ayala, Bastida-López, Castañeda Martínez and Arriaga-Jordan2007).
Mexico, with an annual production of approximately 11 billion liters of milk per year, ranks 8th compared to other nations of the world (SIAP, 2019). The small-scale dairy systems contribute with 35% of the national milk supply and represent over 78% of dairy farms (Sainz-Sánchez et al., Reference Sainz-Sánchez, López-González, Estrada-Flores, Martínez-García and Arriaga-Jordán2017). These systems are generally situated in rural areas and also share some limitations such as low access to credits, low technological level, low availability of land, and lack of professional training (Kuivanen et al., Reference Kuivanen, Alvarez, Michalscheck, Adjei-Nsiah, Descheemaeker, Mellon-Bedi and Groot2016). As a result, farmers have distinct skillsets and ambitions, leading to high variability and heterogeneity in the characteristics of production systems (Makate and Mango, Reference Makate and Mango2017). Therefore, the lack of similarity among production systems further limits the adoption and dissemination of relevant technologies (Martínez-García et al., Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a). In addition, there is a gap in knowledge of the importance and the role of information and communication technologies (ICTs) in rural zones and especially in small-scale dairy production systems.
Studies (Makate and Mango, Reference Makate and Mango2017; Makate et al., 2018; Martínez-García et al., Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a) have focused on the characterization of production systems, using multivariate statistics with the aim of grouping farms with similar characteristics. Therefore, the characterization is considered to be a useful tool that enables the design of strategies for the extension services, communication and dissemination of technologies, taking into account the key characteristics, and needs of each identified group (Martínez-García et al., Reference Martínez-García, Dorward and Rehman2012). The aforementioned studies considered variables that describe the farmers, family unit, farm, participation in governmental programs, and level of technology use; however, no studies have taken into account the use of ICTs, which play an important role in developed countries such as Germany in the adoption of smartphone apps in crop protection (Bonke et al., Reference Bonke, Fecke, Michels and Musshoff2018) and the management of dairy farms (Michels et al., Reference Michels, Bonke and Musshoff2019). In developing countries such as India, the implementation of ICTs, mainly in rural areas, is barely emerging (Rathod et al., Reference Rathod, Chander and Bangar2016). Small-scale dairy farmers have also begun to implement ICTs to improve farm-related activities, for which the following question emerges: What is the importance and role of ICTs in small-scale dairy production systems? Some studies (Borchers and Bewley, Reference Borchers and Bewley2015; Martínez-García et al., Reference Martínez-García, Dorward and Rehman2016; Schaak and Musshoff, Reference Schaak and Musshoff2018) have indicated that farmers’ perception of the importance of a technology plays an important role in its use and adoption. Therefore, the objective of the study was to characterize small-scale dairy production systems to identify the technological preferences according to the farmer and farm characteristics and to analyze the importance and role of ICTs in the dissemination of information related to management and livestock activities.
Materials and Methods
Study area
The study was carried out in nine dairy-producing localities of the municipality of Aculco in the north-western area of the State of Mexico, Mexico. The region started to produce milk in the 1950s; however, during the 1980s, a professional working group emerged among small-scale dairy farmers, milk collectors, and producers of artisanal-type cheese (Espinoza-Ortega et al., Reference Espinoza-Ortega, Espinosa-Ayala, Bastida-López, Castañeda Martínez and Arriaga-Jordan2007). Aculco has around 900 small scale-dairy farms, where milk sales represent the main source of family income (Sainz-Sánchez et al., Reference Sainz-Sánchez, López-González, Estrada-Flores, Martínez-García and Arriaga-Jordán2017). They are characterized by an average farm size of 4.6 ha, with a herd size of 13 cows, of which 6 were in production. Average milk production was 13 l per cow, with a production period of 240 days (Martínez-García et al., Reference Martínez-García, Dorward and Rehman2016). Most farmers (87%) do not have contact with extension services (Martínez-García et al., Reference Martínez-García, Dorward and Rehman2012).
Survey design
A paper-and-pencil survey divided into four sections was designed. The first focused on farmer characteristics and the family unit, the second on farm characteristics, and the third on information relating to the use of technology, including the following seven groups of technologies, which were treated as cumulative variables: management, feeding, health and reproduction, agricultural, complementary, infrastructure and information, and ICTs (Table 1). Finally, the fourth section collected themes of interest to the farmer (market prices, climate, governmental supports, new technologies, diseases, livestock nutrition, crops, and purchase of equipment), means of communication and perceptions of the importance of each technology.
Table 1. Types of technology considered as cumulative variables
* In Mexico, the Program for Sustainable Livestock Production and Livestock and Apicultural Planning (PROGAN) has the objective of promoting the production and adoption of technologies. Thus, animals are identified (SIINIGA tag) and, in compliance with the official health and management regulations, are vaccinated against Brucella and tuberculosis.
Identification of farmers and collection of data
To collect data, a survey was applied face-to-face to 170 farmers during the months of August to December 2018. The farmers were selected through a non-probabilistic snowball sampling (Vogth and Johnson, Reference Vogt and Johnson2016). Farms with a herd size of 3 to 35 cows were considered.
Data analysis
Prior to multivariate analysis, descriptive statistics of the sample were calculated. To characterize the 170 farmers, a factor analysis (FA) was performed. Twenty variables were originally selected; however, only those with a communality greater than 0.5 were retained. Thus, 13 variables were considered in the final analysis (Table 2). To comply with the parsimony and interpretability criteria of the FA, it was confirmed that the value of the Kaiser–Meyer–Olkin (KMO) index was greater than 0.5 and that Bartlett’s sphericity value was significant (p < 0.05) (Field, Reference Field2013). The orthogonal rotation of maximum variance (Varimax) was used to simplify the interpretation of the obtained factors (Martínez García et al., Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a).
Table 2. Results of the factor analysis
Extraction method: principal component analysis; Rotation method: Varimax with Kaiser normalization.
* ICTs = information and communication technologies.
The factorial loads obtained from the principal component analysis (PCA) were used to carry out the hierarchical cluster analysis as recommended by Manly and Navarro (Reference Manly and Navarro2017). To measure the similarity of farms and group them, the Ward and Euclidian distance method were used. The number of groups (Figure 1) was defined based on the generated dendrogram (Martínez-García et al., Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a) and the association graph of Euclidian distances wherein the cut-off point to obtain the groups was made at the intermediate point of the largest break in distance (Kuivanen et al., Reference Kuivanen, Alvarez, Michalscheck, Adjei-Nsiah, Descheemaeker, Mellon-Bedi and Groot2016). To compare the groups with respect to the analyzed variables, a non-parametric Kruskal–Wallis test was performed. The differences among groups were identified through pairwise comparison (Field, Reference Field2013).
Figure 1. Dendogram (left) and plot of linkage distances (right).
Perception of the importance of technology
The farmers’ perception of the importance of each type of technology (management, feeding, health and reproduction, agricultural, complementary, and ICTs) was solicited by asking: How important is the use of … in your farm? The responses were measured on a five-point Likert-type scale from not important (1) to very important (5) (Martínez-García et al., Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a). To analyze the responses, the median was calculated as a measure of centrality and the interquartile range (IQR) as a measure of dispersion. The groups were compared according to farmers’ perceptions of technology using the Kruskal–Wallis test and, to identify the differences among groups, a multiple pairwise comparison test was conducted (Field, Reference Field2013).
Use, importance, and communication of information through ICTs
To compare the percentage of farmers who use each of 10 ICTs and to identify differences between them, a chi-square test was conducted at a significance level of (p < 0.10) along with a z-test and Bonferroni correction (Field, Reference Field2013). To compare groups with respect to their perception of the importance of the ICTs, the Kruskal–Wallis test was used and to identify the differences among groups, a multiple pairwise comparison test was carried out (Field, Reference Field2013). The information communicated by the ICTs was categorized into eight areas of interest to farmers: communication with other farmers, animal production, governmental services, institutional services, veterinary services, market prices, purchase and sale of products, and news.
Results
General characteristics of the small-scale dairy farms
The average farmers’ age was 52 years with primary school (34%), secondary school (35%), high-school (3%), and university (3%); however, 6% of farmers were illiterate. The average family size was five and two of these members on average carried out the farm activities. Thus, farm activities were mostly carried out by family members. Farmers have on average 30 years of farming experience. The average farm size was 5 ha and a herd size of 15 cows of which seven were in production. Average milk production was 13 l per cow per day. Most of farmers (83%) milked by hand. Most farmers (80%) did not have extension services.
Characterization of the dairy production farms
Factor analysis
Four factors were obtained (Table 2) that explained 70.93% of the variance with a KMO of 0.798 and a significant Bartlett’s test (p < 0.001), confirming the reliability of the analysis. Factor 1 described the technological level; that is, the more the use of technologies the more the technological diversity on the farm. Factor 2 described the production level. Therefore, a higher level of infrastructure and herd size was associated with a greater sale of milk and income per day in the farm. In Factor 3, a positive association was evidenced between topics of interest and means of communication, suggesting that the topics can be communicated by smartphones or personal. Lastly, Factor 4 outlines a negative relationship between the variables: farmer experience and use of ICTs, that is, the lower the years of farmers’ experience the greater the use of ICTs.
Characteristics of the four identified groups
The dendrogram (left) showed several solutions to grouping the farms; however, the plot of linkage distances (right) was used to determine the cut-off point for selecting the groups. The cut-off point was placed at the central point of the largest Euclidian distance (between 22 and 30). A dashed line extending from this point was used to determine the four groups (Figure 1).
The characteristics of each group are presented in Table 3. Of the 13 analyzed variables, 12 showed significant differences (p < 0.05) among the four groups. Group 1 was formed by 48 farmers with a primary level of schooling, age of 60 years, and greater experience as milk farmers. These farmers have an average of 5 ha and the largest herd size, with six cows in production, which is similar to Groups 2, 3, and 4. However, this group holds second place in quantity of milk sold and income per day. The production of milk is considered the main source of income.
Table 3. Characteristics of the groups obtained in the hierarchical grouping
* p value of the Kruskall–Wallis test.
† IQR = interquartile range.
‡ 1 USD = 19.45 MXN on average during the study period.
§ Means of communication, 1 = personal, 2 = smartphone, and 3 = both.
¶ ICTs = information and communication technologies.
a,b,cDifferent superscripts indicate differences between pairs according to the pairwise comparison test (p < 0.05).
Additionally, Group 1 presented the highest level of technology use (similar to Group 2). The most adopted technologies were feeding, health and reproduction, and agricultural technologies. Group 1 also had the highest number of areas of interest (similar to Groups 2 and 4). Farmers of this group expressed that they prefer to face-to-face communication with other farmers and governmental institutions regarding topics related to dairy production (similar to the farmers of Groups 3 and 4). In total, 69% of the farmers did not have contact with an extension services. Finally, a low use of ICTs was observed (similar to Groups 3 and 4).
Group 2 was formed by 48 farmers with secondary school, age of 46 years, and the second lowest level of experience in milk production. Farms have on average 2 ha. Farmers make a considerable use of technologies despite having a lower herd size and milk sales. Farmers have the second lowest income per day; however, 65% of farmers received income outside of the farm. Most of farmers (81%) did not have contact with an extension service. Group 2 makes the greatest use of ICTs and prefers to communicate about topics of interest through smartphones.
Group 3 was integrated by 37 farmers with primary school and 47 years of age. The farmers of this group have on average 2 ha. They also obtained the lowest milk sales and income per day. For 70% of farmers, milk is the main source of income. Most farmers (89%) in Group 3 reported no contact with an extension service. This group presented a low use of technologies, although health and reproduction technologies were those most used by farmers. Notably, this group had the lowest number of topics of interest.
Group 4 was formed by 37 farmers with, on average, a primary education level and age of 53 years. The farmers of this group have the second highest level of experience. Also, farmers have on average 1.8 ha. All farmers (100%) consider milk production to be the main source of income. This group had the highest level of production and income from milk sales despite using the least amount of technology and having a level of infrastructure similar to that of Groups 1, 2, and 3. In total, 81% of the farmers did not have contact with an extension service.
Perception of the importance of use of each group of technologies
Table 4 indicates significant differences (p < 0.05) among the four groups with respect to the farmers’ perception of the importance of use of each group of technologies. Group 1 indicated that management technologies are slightly important, although for Groups 2, 3, and 4, these were not important. Feeding technologies were considered as fairly important and very important by Groups 1 and 2, respectively. Groups 3 and 4 considered them important. Health and reproduction technologies were considered fairly important and important by Groups 1 and 2, respectively; however, these were slightly important for the farmers of Groups 3 and 4.
Table 4. Perception of farmers of the importance of use of each group of technologies
Degree of importance: 1 = not important, 2 = slightly important, 3 = important, 4 = fairly important, 5 = very important.
* p value of the Kruskall–Wallis test.
† IQR = interquartile range.
a,b,cDifferent superscripts indicate differences between groups in the pairwise comparison test (p < 0.05).
Groups 1 and 2 considered agricultural technologies as very important, whereas for the Groups 3 and 4, they were slightly important. Complementary technologies were considered as important by Groups 1 and 2. ICTs were considered as not important by Groups 1, 3, and 4 and were slightly important to the farmers of Group 2.
Use of the ICTs by small-scale dairy farmers
Table 5 indicates the percentage of farmers that make use of the 10 ICTs considered in the study. Significant differences (p < 0.10) were observed in the percentage of farmers that make calls using mobile phone, send messages (SMS), and make landline calls. In all cases, low proportion of farmers uses landlines at their farm. The farmers of Group 2 used the latter three technologies to a greatest extent; however, the mobile phone was the ITC of greatest use in all four groups.
Table 5. Use of the ICTs by small-scale dairy farmers
Different superscripts between percentages (a, b, and c) indicate differences among groups according to the z-test with a Bonferroni correction (p < 0.10).
* p value resulting from the chi-squared test (p < 0.10).
† ICTs = Information and communication technologies.
Group 1 is characterized by the indirect use of ICTs (similar to Group 4), as farmers stated that they make calls using the mobile phone of a close family member such as their son, daughter, niece, nephew, and grandchild. The most common use of smartphones in the four groups is for sending text messages (SMS). The ICTs that require the internet such as WhatsApp, Facebook, computer, and e-mail were used at a low rate within the four groups (Table 5). Meanwhile, Group 2 is characterized by the direct use of ICTs. The majority of the farmers in this group prefer communication over smartphones. Group 3 is characterized by a low but direct use of ICTs. Group 4 has scarce indirect access to ICTs and uses these technologies to the lowest extent.
Perception of the importance of use of ICTs
The farmers’ perceptions of the importance of use of ICTs are outlined in Table 6. Group 2 showed significant differences (p < 0.05) in comparison with Groups 1, 3, and 4. Farmers in Group 2 indicated that calls and messages (SMS) through smartphones were fairly important and that WhatsApp was important for communicating with other farmers. The farmers of Groups 1 and 3 indicated that calls through smartphones were important. Finally, the farmers of Groups 1, 3, and 4 indicated that messages (SMS) and WhatsApp were slightly important. Television, radio, internet, computer, and e-mail were considered as slightly important by the four groups. Landline and Facebook were not important for communication among farmers in the four groups.
Table 6. Perception of the importance of use of ICTs
* p value of the Kruskall–Wallis test.
† ICTs = information and communication technologies. Degree of importance: 1 = not important, 2 = slightly important, 3 = important, 4 = fairly important, 5 = very important.
‡ IQR = interquartile range.
a,bDifferent superscripts indicate differences between groups according to the pairwise comparison test (p < 0.05).
Communication of information through ICTs
The main areas of interest and corresponding ICTs used to communicate information are described in Table 7. The four groups presented significant differences (p < 0.10). Groups 3 and 4 had the lowest percentage of farmers that use ICTs. Seven of the eight themes of interest were communicated through calls and messages (SMS) via smartphones, mainly in Groups 1 and 2. Additionally, smartphones were the preferred medium for making calls with other farmers and soliciting veterinary services. Finally, television and radio were the ICTs of greatest preference for farmers to find out about relevant news, mainly in Groups 1 and 2.
Table 7. Communication of information through ICTs
* ICTs = information and communication technologies.
† p value resulting from the chi-squared test (p < 0.10). Different superscripts between percentages (a, b, and c) indicate differences between groups according to the z test with the Bonferroni correction (p < 0.10).
Discussion
Characterization of the dairy production systems
Given the differences in work strategies, information and communication strategies, and level of technology adopted by farmers in rural areas (Kuivanen et al., Reference Kuivanen, Alvarez, Michalscheck, Adjei-Nsiah, Descheemaeker, Mellon-Bedi and Groot2016; Makate and Mango, Reference Makate, Makate and Mango2018), the characterization of farms has been considered as a useful tool for decision making and the proposal of extension services (Martínez-Garcia et al., Reference Martínez-García, Dorward and Rehman2012, Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a). The results highlighted four groups of farms defined by their level of technology use and production, characteristics of the farm, and use of ICTs.
Martínez-García et al. (Reference Martínez-García, Dorward and Rehman2012) found that farmers who consider milk production as the main source of family income make a greater incorporation and use of technologies, as observed with the farmers in Group 1. In contrast, Group 4 had the highest production of milk and income despite employing the lowest level of technology. This can be attributed to the farmers’ experience and the technologies used in their farms, such as feeding technologies that take advantage of maize silage, pastures for cutting, and grazing pastures. Prospero-Bernal et al. (Reference Prospero-Bernal, Martínez-García, Olea-Pérez, López-González and Arriaga-Jordán2017) indicated that these technologies increased the economic sustainability of small-scale dairy farms. Therefore, extension programs should be created to promote the most efficient and profitable feeding technologies in the all four groups of farms identified in the research.
With respect to the topics of interest for farmers the majority of the groups (1, 3, and 4) expressed a preference for direct and face-to-face communication with other farmers or with personnel who provide extension services. Martínez-García et al. (Reference Martínez-García, Janes-Ugoretz, Arriaga-Jordán and Wattiaux2015a) found that small-scale dairy farmers preferred to attend courses and talks on themes related to dairy production within their own community or on nearby farms, because travel to neighboring communities or the municipal capital can be time-consuming. Most notably, the farmers of Group 2 presented the greatest use of ICTs and preferred to communicate about topics of interest through smartphones, which may be attributed to their young age and high education level. Thus, extension services should direct their efforts toward creating digital infographics on topics of interest for farmers from Group 2 that can be distributed by smartphones in order to facilitate the communication of information to farmers. However, for farmers from Groups 1, 3, and 4, a face-to-face extension approach need to be conducted to disseminate information.
Perception of the importance of use of each group of technologies
The farmers’ perception of the importance of technology plays an important role in decision making regarding the use and adoption of new technologies (Martínez-García et al., Reference Martínez-García, Dorward and Rehman2016; Schaak and Mubhoff, Reference Schaak and Musshoff2018). In the study, the farmers’ perception of the importance of the analyzed technologies is directly related with their availability and use on their farms. Borchers and Bewley (Reference Borchers and Bewley2015) indicated that farmers select technologies that can satisfy their needs for several years considering financial and demographic factors and expert advisory. For example, feeding technologies were considered to be importance by the four groups. This can be attributed to the importance that farmers placed on finding new feeding strategies that decrease production costs, especially considering that it was estimated that 70% of production costs in small-scale dairy farms corresponded with feeding costs (Martínez-García et al., Reference Martínez-García, Rayas-Amor, Anaya-Ortega, Martínez-Castañeda, Espinoza-Ortega, Prospero-Bernal and Arriaga-Jordán2015b).
The technologies were rated as not important when the farmers were unable to count on them in their farms. Michels et al. (Reference Michels, Bonke and Musshoff2019) mentioned that the adoption is low when the technologies do not satisfy needs and do not resolve a determined problem. Therefore, extension and training programs should be developed to promote the technologies considered as important by farmers, since it is most likely that farmers can participate in training and adopt the technologies, for example, health and reproduction technologies can be promoted in Groups 1, 2, and 3, since these technologies could improve the health and fertility of cows, which are important for the productive and economic efficiency of farms (Shalloo et al., Reference Shalloo, O’Donovan, Leso, Werner, Ruelle, Geoghe-Gan, Delaby and O’leary2018).
Use of ICTs by small-scale dairy farmers
In developed countries, the use of ICTs is increasing given the availability of smartphones applications for dairy herd management (Michels et al., Reference Michels, Bonke and Musshoff2019). However, in developing countries, the use of smartphones in rural areas is barely emerging (Rathod et al., Reference Rathod, Chander and Bangar2016). Similar results were observed for the use of ICTs by small-scale dairy farmers, as these were adopted at low but varying rates in the four groups according to the age of farmers, level of education, lack of smartphones signal or internet, and knowledge of their use and management within farms. In this last regard, farmers are generally unable to imagine the practical utility of ICTs in the farm. Therefore, extension services should be created to encourage the development of abilities and knowledge regarding the daily use and integration of ICTs on farms. It would also be possible to disseminate infographics on feeding technologies (maize silage and planted pastures) through smartphones and WhatsApp, which are the emerging technologies most used by farmers in Group 2. The smartphones can be adapted to the working routines of farmers because of their mobility. Thus, the promotion and training on the use of smartphone applications could be one alternative for improving herd management (Michels et al., Reference Michels, Bonke and Musshoff2019).
It is also important to note that the farmers of greater age without skills or knowledge of ICTs tend to use these technologies indirectly (Groups 1 and 4) by using family members’ smartphones. These farmers could be considered as passive users of the ICTs. On the other hand, the younger farmers made the direct use of ICTs and had the most knowledge of their use (Groups 2 and 3). These farmers could be considered digital migrants since they were born before the ICT’s boom; however, they have slowly adapted to the use of these technologies (Autry and Berg, Reference Autry and Berge2011).
Perception of the importance of use of ICTs
The perception of the importance of the ICTs can be related with their incorporation and frequency of use by farmers. For instance, farmers mentioned (Groups 1, 2, and 3) that smartphones were considered as important, since they facilitate rapid and efficient communication with family members, farmers, veterinarians, and feed sellers, as well as during emergencies. Likewise, they can easily be used anywhere and to locate specific individuals. However, on occasions, they mentioned that lack of signal is a problem, although farmers often send messages (SMS) in this case as these are sent once the signal is re-established. Therefore, policy makers should take into account the mobile network expansion in rural areas, in order to support the communication between farmers.
The farmers of Group 2 considered messages (SMS) as fairly important and WhatsApp as important for maintaining communication with family, friends, or other farmers. It could be worthwhile to explore the social network generated by the use of smartphones in Group 2, in order to identify the dynamics and key actors that favor the communication of information. Finally, the four groups do not use the ICTs that depend on the use of internet, since farmers considered that the internet is expensive and they lack knowledge of how to use it. Lima et al. (Reference Lima, Hopkins, Gurney, Shortall, Davies, Williamson and Kaler2018) indicated that the lack of knowledge and comfort or insecurity in using a technology inhibit its acceptance and adoption by farmers. Therefore, extension and training programs should be developed to promote the ITCs considered as important (messages (SMS) and WhatsApp); since, they will be useful for communicating information between farmers as observed in Group 2.
Communication of information through ICTs
The farmers of Groups 1 and 2 mainly use smartphones to communicate seven of the eight topics of interest. Specifically, the farmers of all four groups use smartphones to stay in contact with other farmers and to request veterinary services. Therefore, since smartphones are already used by farmers in Groups 1 and 2, they could be useful tools for communicating and disseminating information about the topics of interest. Lima et al. (Reference Lima, Hopkins, Gurney, Shortall, Davies, Williamson and Kaler2018) indicated that the adoption and use of ICTs, dependent on farmers’ familiarity and level of use of these technologies. Extension services should encourage the use of ICTs and provide adequate training on them in Groups 1 and 2, in order to provide farmers with the skills and tools to obtain information relevant to dairy production and improve herd management. On the other hand, means of mass communication such as television and radio could be used to promote the use of technologies appropriate for each group of farmers or to encourage participation in governmental programs aimed at the dairy sector.
Conclusions
Four groups of farmers were differentiated by the use of agricultural and livestock technologies, farm characteristics, communication of information, and use of ICTs, so different approaches should be implemented to take into account their preferences, including those technologies considered most important. At the same time, the technologies that are promoted should be adequate to the farmers’ characteristics. For example, the farmers of all four groups were more accepting of feeding technologies, whereas those in Groups 3 and 4 were reluctant to use management technologies. Therefore, the characterization of farmers can be viewed as a tool for better understanding and designing strategies for future interventions.
It was also found that the small-scale dairy farmers have begun to incorporate ICTs into their daily routines, mainly the youngest farmers, such as those of Group 2. The use of smartphones, especially to make calls, is considered by farmers to facilitate the communication of information, areas of interest, and interaction with other farmers. However, to avoid the lack of signal in the study area, policy makers should take into account the mobile network expansion, in order to support the communication between farmers.
The ICTs that depend on the internet are slightly important and not used by the majority of farmers in the four groups since they are more expensive and require knowledge to use. For this reason, it is suggested that extension policies for the region follow two routes: First, the gap in digital knowledge should be eliminated through training seminars as well as appropriate follow-up that educate on the use of ICTs, placing emphasis on adult farmers and indirect users (Groups 1 and 4). Second, the use of technologies should be promoted through infographics disseminated through digital media such as smartphones, text messages, and WhatsApp (Group 2). Finally, more in-depth research studies should be carried out on the processes through which ICTs are appropriated by farmers as means or tools for dairy production given the large gaps in knowledge on this topic.
Acknowledgements
The authors thank the farmers who participated in the study for their hospitality and full support. The work was made possible by funding from the Consejo Nacional de Ciencia y Tecnología-CONACYT (Grant: PN-2016-1-2323).
