Cow-calf management practices in Mexico: dual-purpose cattle

Cow-calf management practices in Mexico: dual-purpose cattle | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cow-calf management practices in Mexico: dual-purpose cattle Arantzatzu Lassala, Miguel Ángel Alonso-Díaz, Manuel Dionisio Corro-Morales, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2945183/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aimed to characterise management practices of dual-purpose (DP) cattle production systems across Mexico through a structured questionnaire answered by 996 farmers. The predominant type of cattle found in DP operations was European dairy x Zebu crossbreeds (54.7%). These cattle were most popular in the tropics with 78% and 56% for the humid and dry tropics, respectively. In contrast, temperate climate farmers prefer European beef x Zebu crossbreeds (63.1%). Weaned calves and dairy products were the primary goods of DP systems. More operations sell raw milk in temperate climates than in arid and tropical climates. Ninety one percent of DP farms milk their cows manually, whilst only 8.6% use mechanical milking. Cows are milked once daily in 93% of farms. The main calf-rearing system is by allowing the calf to suckle (95.1%), with only 4.9% of operations using artificial rearing methods. Milk letdown was most frequently induced by the calf (73.2%), but 13.9% of operations used oxytocin stimulation. Only 6.3% of operations have milk cooling systems. Regarding sanitary practices, 73.5% of farms reported cleaning the teats prior to milking. Teat dipping after milking was generally low (10.5%), owing to the calf feeding on remanent milk. In addition, only 18% of DP operations routinely use mastitis diagnosis tests. Given the importance of dual purpose for local economies, improvements in market integration, technical assistance, and technology appropriation are paramount for the future development of this sector. cattle farming manual milking oxytocin market integration technology appropriation 1. Introduction Dual-purpose cattle farming is a production system in which both milk and calves are generated simultaneously, primarily under grazing conditions. While this is a less productive and efficient system than specialised milk or beef operations (Ruiz-Guevara et al. 2008 ; González-Quintero et al. 2020 ), it has a significant socioeconomic importance due to its low-investment requirements and flexibility (Rojo-Rubio et al, 2009 ). In Latin America and the Caribbean, dual-purpose farms are often run by smallholders and are prevalent in rural areas (FAO. 2023a). Indeed, up to 95% of the milk and its derivatives produced on DP farms are destined for self or local consumption, benefiting the microeconomy and playing an important role in food security and supply (FAO, 2023a ). In Mexico and Colombia, dual-purpose cattle farms account for 12.2% and 35% of the national cattle herds respectively (INEGI, 2019 ; Fedegan, 2022). Moreover, the FAO estimates that up to 90% of the milk produced in developing countries could come from dairy and dual-purpose smallholders (FAO, 2023b ). Challenges for farmers include restricted access to markets, inadequate infrastructure, low productivity, and limited utilisation of veterinary services (Hemme and Otte, 2010 ). Studies on dual-purpose cattle management systems have assessed the implementation of strategic practices to enhance productivity and sustainability and improve the livelihoods of farmers. Researchers found that the adoption of technology to advance herd management, nutrition, controlled breeding, genetic selection, mechanical milking, and animal health can improve milk and meat production, reduce production costs, and ameliorate the quality of products (Rojo-Rubio et al., 2009 ; Espinosa Garcia et al., 2018 ). These findings indicate that continued research and implementation of appropriate management practices are crucial to enhancing productivity. They also suggest that appropriate institutional support and policies are needed to improve producer income while reducing the environmental footprint of dual-purpose livestock production. Previous studies that investigated the adoption of desirable practices highlight the diverse nature of dual-purpose operations in Mexico. Nonetheless, they are limited in their reach as they have primarily focused on farms located in the humid (Gulf region) or dry (Pacific region) tropical environments (Cuevas Reyes and Rosales-Nieto 2018; Granados-Rivera et al., 2018 ; Rangel et al., 2020 ; Aguilar-Jiménez et al., 2023 ). Therefore, the present work aimed to address this gap by characterising management practices of dual-purpose cattle production systems across all climatic and geographical regions of Mexico. The goal was to better understand the strengths and weaknesses of the production system, as well as the opportunities, needs and preferences of farmers. 2. Materials and Methods Management practices and use of technology in grazing cattle production units in Mexico were characterized by a structured questionnaire. This instrument gathered descriptive information related to farm organization, herd management, occurrence of infrastructure, feeding practices, health and well-being, environmental management practices, reproductive management, dual-purpose systems, and a section devoted to specialized dairy production in pasture. Results of this work comprise characterization of management practices of dual-purpose operations. The methods and questionnaire are described in González-Padilla et al. ( 2019 ). Briefly, the questionnaire was adapted from the one used by the United States Department of Agriculture (USDA, 2008) to characterise beef-calf management practices, with adjustments and suggestions from experienced academics, practitioners, and farmers from different regions of Mexico. The sample size was calculated with a 95% confidence level, with a probability (p) of 50% and an estimated error (d) of 5%. The calculated number of questionnaires to be administered was 3158 (González-Padilla et al., 2019 ). A total of 3311 questionnaires were completed, with 31 being discarded due to answer discrepancies. The final number of surveyed dual purpose (DP) operations was 996. Statistical analyses Each option within a question was considered as a binary variable. For questions that specified that a single response should be chosen, the frequency of a management practice was analyzed by REML (Genstat 22nd ed.; VSN international, 2022 ). For questions that allowed more than one answer, each selection was analyzed separately by univariate analysis. The results are presented as least square means with the standard error of the difference (sed). Differences were considered significant at p < 0.05. Fixed variables were considered as follows: - Herd size: Herds were classified as small (up to 35 cows), medium (36 to 100 cows), or large (over 100 cows). - Region: The country was divided in five regions based on similarity of agro-ecological characteristics and geographical proximity: North (Baja California, Baja California Sur, Chihuahua, Coahuila, Durango, Nuevo Leon, Sonora and Zacatecas); Center (Aguascalientes, Estado de Mexico, Guanajuato, Hidalgo, Puebla, Queretaro, San Luis Potosi and Tlaxcala); Pacific (Chiapas, Colima, Guerrero, Jalisco, Michoacan, Morelos, Nayarit, Oaxaca and Sinaloa); Gulf (Tabasco, Tamaulipas and Veracruz), and Peninsula (Campeche, Quintana Roo and Yucatan). - Climate: Climates were classified as arid-semiarid, temperate, dry tropics and humid tropics, according to García ( 2004 ). -Poverty levels: Poverty levels were defined using municipal categories set by the National Population Council (CONAPO, 2013 ) as very low, low, medium, high, or very high. -Land-tenure: Land-tenure type was declared by the producer as communal land, ejido or private property. 3 Results Dual-purpose cow-calf production units were found to be distributed across the country. The predominant type of cattle used in these operations is European dairy x Zebu crossbreeds (54.7%). These cattle were most popular in the tropics with 78% and 56% for the humid and dry topics, respectively (Table 1 ). In contrast, in temperate climates, European beef x Zebu crossbreeds were the most frequent cattle type (63.11%) (Table 1 ). Moreover, the Gulf and Peninsula regions had the highest proportion of dairy x Zebu crossbred cattle, while in the Center and North regions, European beef cattle and their crosses with Zebu predominated (Table 1 ). The frequency of farms that declared having pure specialized dairy breeds, European beef, pure Zebu, or criollo were found to be under 6%. Table 1 Cattle breed prevalence in dual-purpose operations in the different regional and climate environments in Mexico (% of Dual-purpose operations *). European Beef.Zebu European Beef Zebu Criollo European Dairy.Zebu Dairy Sed Population mean 31.0 5.7 2.7 3.3 54.7 5.6 1.5 Climate Arid and Semi-Arid 38.1 8.5 3.7 5.8 42.3 5.8 Temperate 63.1 3.9 0.0 4.8 20.4 9.7 Dry Tropic 28.5 5.5 3.8 2.5 56.0 5.3 Humid Tropic 15.9 4.4 0.9 2.2 78.0 4.0 Sed 3.0 Region North 29.8 21.3 0.0 6.4 36.2 12.8 Pacific 33.5 5.1 3.9 2.9 52.5 4.3 Center 45.3 9.5 2.0 6.8 33.1 7.4 Gulf 19.9 2.4 1.2 2.0 71.7 6.4 Peninsula 13.8 0.0 3.4 0.0 86.2 0.0 Sed 4.6 * The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Farm products and marketing Weaned calves (aged 6 to 12 months) and dairy products were the two primary products of DP systems (Table 2 ). However, a higher proportion of operations in tropical (dry and humid) climates sell dairy products compared to those in arid and temperate climates. Additionally, a larger percentage of production units in temperate climates sell finalized cattle (14.6% vs . 6% in other climate regions). Although weaned calves are the main product sold, production units in temperate climates tend to keep their calves on pasture for longer periods. Table 2 Farm products declared as the most important for dual-purpose farmers of different climate conditions in Mexico (% of dual-purpose operations *). Weaned calves Dairy Products Back- grounders Fattened animals Breeding stock Pregnant cows Sed Population mean 84.0 66.5 13.7 6.9 3.6 0.9 1.4 Climate Arid and Semi-Arid 77.3 57.1 14.3 5.8 3.7 0.5 Temperate 80.6 43.7 23.3 14.6 2.9 0.0 Dry Tropic 88.9 70.7 9.4 6.1 3.8 1.3 Humid Tropic 80.9 75.7 17.8 6.1 3.5 0.9 Sed 3.0 * The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Regarding marketing of milk production, a higher proportion of operations in temperate climates sell raw milk compared to those in arid and tropical climates (Table 3 ). Dairy products, following in-farm milk processing, are sold by 32.5% of DP farmers. However, differences were observed according to climate region (Table 3 ). In arid and semi-arid climates, milk is processed more frequently (66%), followed by production units located in the temperate climate (49%). Conversely, farms in the dry and humid tropics process their milk less frequently. In general, fluid milk is primarily sold to local cheese makers (49.8%), which is particularly apparent in the Gulf and Peninsula regions (Table 3 ), whilst the lowest frequency is observed in the northern region. Retail sale of raw milk was declared as the third more common form of milk marketing in DP farms (23.6%), with this practice being more common in the temperate climates and central region of the country. Moreover, less than 6% of producers acknowledged selling milk to dairy cooperatives and pasteurization plants (Table 3 ). Finally, only 6.3% of operations have milk cooling systems. Table 3 Dairy product marketing in dual-purpose operations in different regional and climate regions in Mexico Dairy Products Cheese maker Fluid milk Co-op Sed Population mean 32.5 49.8 23.6 5.2 2.0 Climate Arid and Semi-Arid 66.3 21.5 22.7 5.2 Temperate 49.4 27.2 43.2 0.0 Dry Tropic 24.5 58.6 22.1 4.8 Humid Tropic 14.4 64.1 19.6 8.1 Sed 4.3 Region North 63.9 22.2 27.8 5.6 Pacific 42.0 39.1 28.4 4.9 Center 22.7 52.6 35.1 3.1 Gulf 14.5 71.4 10.8 6.6 Peninsula 13.6 81.8 0.0 4.6 Sed 7.1 * The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Milk Production Process Ninety one percent of DP operations milk their cows manually, whilst only 8.6% use mechanical milking, half of which use portable units. Private operations are four times more likely to have automatic milking systems (13.9%) than ejidos or those using communal land for grassing. Similarly, milking machines are found twice as often in medium and large operations compared to small farms (Table 4 ). Additionally, 19% of DP production units located in municipalities with very low poverty level reported using mechanical milking systems, indicating a three-fold higher frequency than farms in areas with higher poverty levels (Table 4 ). Table 4 Proportion of dual-purpose operations that milk the cows manually or by mechanical, fixed or portable, milking systems, according to herd size, land tenure type and poverty level in Mexico. Mechanical Milking Manual Fixed unit Portable unit Sed Population mean 91.4 4.3 4.4 1.1 Herd Size Small 94.8 3.3 2.1 Medium 88.8 4.6 6.2 Large 88.2 5.9 5.9 Sed 2.1 Land Tenure Ejido 95.6 1.7 2.8 Communal 98.8 0.0 1.3 Private 86.0 7.4 6.6 Sed 2.4 Poverty level Very Low 82.0 10.0 9.0 Low 92.7 2.1 5.2 Medium 92.1 4.1 3.8 High 91.3 4.6 3.7 Very High 96.5 0.9 2.7 Sed 2.7 * The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Milking frequency was declared to be once a day in 93% of dual-purpose farms, with only 7% of operations stating to milk twice a day. Operations located in very low poverty municipalities reported milking more frequently than DP farms located in other poverty groups (Table 5 ). Table 5 Proportion of dual-purpose farms milking the cows once or twice daily according to poverty level of the municipality where they operate. Once a day Twice a day Sed Population mean 93.2 6.9 2.7 Poverty level Very Low 79.0 21.0 Low 93.6 6.3 Medium 94.7 5.3 High 94.9 5.5 Very High 97.3 2.7 Sed 6.5 * The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Roughly half of the DP operations declared measuring milk production daily. However, the survey did not distinguish whether this measurement was done in bulk or per cow. Since milk gets sold every day due to the lack of refrigeration infrastructure, there is a need to measure production at least in bulk, but no cow information is registered by farmers for selection or for record keeping purposes. As milk production in DP cattle typically decreases after six months of lactation, low productivity was reported as the main reason for drying the cows. Drying due to advanced pregnancy, and thus advanced lactation, was declared as a management practice in 27.5% of DP operations. Calf rearing The main calf rearing system used by DP farms is allowing the calf to suckle (95.1%), with artificial rearing reported in only 4.9% of operations. The most common rearing practice is to reserve all the milk from one quarter of the udder for the calf (65%), followed by leaving residual milk after milking (20.7%). The practice of leaving one quarter of the udder for the calf to suckle is twice as frequent in dry and humid tropical climates compared to arid and temperate climates (Table 6 ). Table 6 Number of udder quarters left for the calf to suckle. One Qrt. Two Qtrs. Three Qtrs. Residual milk Sed Population mean 65.1 13.4 1.4 20.8 1.8 Climate Arid and Semi-Arid 44.4 15.4 2.5 37.7 Temperate 43.2 33.8 0.0 23.0 Dry Tropic 70.8 7.8 1.6 20.3 Humid Tropic 80.4 14.7 0.5 6.0 Sed 3.9 * The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Eighty four percent of operations reported weaning their calves between 6 months and one year of age. Of the remaining operations, almost one percent weaned their animals at less than 5 days old, whilst 7% ablactated calves when they reached over a year old. The most frequent declared method for weaning was by the sudden separation of calves and cows, followed by gradual separation (16.8%) and the use of a nose flap (12.6%). Milk letdown stimulation in cows before milking was most frequently induced by the presence of the calf (73.2%) in DP farms. Pure conditioning ( i.e. no stimuli or manual stimuli) without the use of external aids was reported as a management practice in 15% of operations. The use of oxytocin was reported in 13.9% of DP production units. Moreover, the use of oxytocin treatment was higher in dry and humid tropical regions and in large herds (Table 7 ). Table 7 Prevalence of the stimuli used in dual purpose operations in Mexico to induce milk let-down at milking according to herd size and climate regions. None Calf Manual Oxytocin Sed Population mean 8.7 73.2 6.4 13.9 1.6 Climate Arid and Semi-Arid 16.1 64.9 19.0 2.3 Temperate 1.2 95.2 3.6 0.0 Dry Tropic 9.2 75.4 3.6 14.7 Humid Tropic 4.7 66.8 2.8 27.5 Sed 3.6 Herd Size Small 9.2 73.5 8.5 10.4 Medium 8.4 74.5 4.4 14.9 Large 6.7 71.9 4.4 20.7 Sed 3.0 * The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference Sanitary practices in the milking process Regarding sanitary practices, 73.5% of farms reported cleaning the teats of the udder prior to milking (Table 8 ). Teat cleansing was less common in the humid tropics than in other climate regions. Teat dipping after milking is generally low in dual purpose operations (10.5%), with a slight increase in frequency in farms located in municipalities with low poverty levels. In addition, only 18% of DP operations routinely use mastitis diagnosis tests and, as with teat dipping, this practice increases in low poverty municipalities (Table 8 ). Table 8 Prevalence of sanitary practices in the milking process of dual-purpose operations in Mexico according to climate and geographic regions, and poverty level. Teat cleansing Sed Teat dipping Sed Mastitis tests Sed Population mean 73.5 10.5 18.0 2.1 1.5 1.9 Climate Arid and Semi-Arid 83.3 12.6 18.7 Temperate 84.5 2.4 9.6 Dry Tropic 73.0 9.6 15.7 Humid Tropic 61.5 13.9 25.6 Sed 4.8 3.4 4.2 Region North 77.8 13.9 11.1 Pacific 84.3 10.4 16.4 Center 72.0 3.0 3.0 Gulf 48.9 13.9 28.9 Peninsula 86.4 4.6 18.2 Sed 7.4 5.5 6.8 Poverty level Very Low 86.0 27.0 31.6 Low 64.6 10.5 13.7 Medium 64.6 10.7 21.2 High 68.2 6.0 12.2 Very High 85.5 3.6 10.8 Sed 5.3 3.6 4.6 * The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. Sed -Standard error of the difference 4. Discussion Results from this study show that dual purpose farmers declare weaned calves as the main product of their enterprise, followed by dairy products. The prevailing livestock genotype in production units varied between regions, with preferences leaning towards European Dairy x Zebu crosses in tropical climates, and European beef x Zebu in temperate climates. Milk is mainly drawn once a day manually, with the calf used as an aid for milk letdown. Obtained milk is mostly sold at retail or to local cheese factories. Dual purpose cattle farmers typically have crossbred animals obtained by mating locally existing cattle ( i.e. cattle adapted and homegrown for generations) with exotic improved breeds. This crossbreeding practice has resulted in increased milk yield and offspring fitness (McDowell, 1985 ). European dairy x Zebu crossbreeds are the predominant genotype found in tropical climates (54.7%), benefiting from the resilience of Zebu cattle to harsh environmental conditions (increasingly exacerbated by climate change) and the ability of European breeds to produce milk or meat. This genetic mixture has been shown to increase milk and meat yield under heterogeneous systems (Rangel et al., 2020 ). Indeed, heterosis when Zebu and dairy cattle are crossbred allows for better milk production in the characteristically higher parasite load, elevated temperature-humidity index (THI), and low pasture quality conditions that prevail in tropical climates (Magaña-Monforte et al ., 2008). In contrast, Zebu-type cattle are crossbred in a greater proportion to European beef-type cattle in temperate climate regions (63%). Moreover, European dual-purpose breeds are frequently chosen for crossbreeding. However, the survey questions were not designed to discern between European dual-purpose or European beef breeds. Furthermore, male calves sired by a dairy bull typically sell at lower prices than those sired by a beef European bull. Hence, the use of beef European breeds for dual-purpose systems in temperate climates may obey to the demand of beef-type calves from feedlots that deliver to the export market in central and northern regions of Mexico (González-Padilla et al., 2019 ). Whilst this study was not designed to determine the proportion of Zebu vs European blood (dairy or beef) in animals found in dual-purpose herds, others have shown that the advantages obtained by crossbreeding are greatest in the first generation (F1), but gains are partially lost thereafter. In fact, besides F1 offspring (50% exotic genetics), the more stable production performance is achieved at 62.5% (between 50 to 75%) of exotic genetics (McDowell, 1985 ). However, the introduction of exotic breeds, regardless of the genetic background of the local herd, has been shown to have a beneficial effect on productive parameters (McDowell, 1985 ). Nevertheless, there has been a lack of breeding guidelines (set either by the government or by farmer organisations) to establish how to attain and maintain an ideal percentage of exotic vs . native genetics within herds to enhance productivity. In addition, breeding programmes for crossbred cattle need to operate within the country´s developing goals and are often contingent to long-term policies and financial support. González-Padilla et al. ( 2019 ) reported that the prevalence of pure Zebu and criollo cattle in Mexico has decreased to a third of what it was in the late 1970’s. Despite this decline, the input of Zebu type cattle remains high and continues to form the basis of dual-purpose herds. Dual-purpose operations are widespread throughout Mexico but are predominantly comprised of small holders who are scarcely technified and have a low organizational information and record keeping culture (González-Padilla et al., 2019 ). As a result, systematic genetic evaluation of dual-purpose cattle is limited and mainly conducted in research stations ran by government agencies or universities. Zebu progeny evaluations are scarce, albeit purebred Zebu cattle associations working under tropical conditions are producing genetic information for productive and fitness parameters. The advent of genomic selection strategies, in concert with traditional genetic methods, can potentially accelerate selection and highlight elite genetics evaluated under specific environmental conditions (Mrode et al., 2019 ). However, to fully utilize these technologies, the cow-calf system must overcome its poor record keeping culture (González-Padilla et al, 2019 ) and further the use of reproductive technologies such as artificial insemination (Lassala et al., 2020 ). In this study, over eighty percent of farmers declared the calf as one of the two main products of their operation. Indeed, Albarrán-Portillo et al. ( 2015 ) estimated that calves represent 30 to 50% of the annual income of the farm, cashed once or twice a year, providing a source of savings that can be allocated to investments in other inputs or activities. Most weaned calves from DP farms are sold domestically to brokers or middlemen who deliver animals to backgrounding or feedlot systems throughout the country. As a result, the producer remains detached from finalizing the calf and thus from the potential economic benefits of marketing this end product. In addition, the prize of the calf can be influenced by intrinsic traits (such as breed, gender, age, body condition score, weight, coat color, etc.) that may impact the quality of the meat, and by factors such as distance from the point of sale to feedlots, as well as economic circumstances and market perception linked to the elasticity of the demand (Martínez et al., 2019 ). The second most reported product for DP units was raw milk and dairy products. Interestingly, over 30% of producers did not consider milk as a primary product of their operation, even when milk production provides a stable income that allows DP operations to cover daily costs, supplying cash flow that families rely upon. Nonetheless, most DP operations are integrated into their local market through the sale of retailed raw milk and cheese, stimulating the regional economy. Overall, the main route for DP farm milk marketing across Mexico is as fluid milk, sold either to local cheese factories (49.8%), as in-house processed dairy products (32.5%) or as retailed raw milk (23.6%). As a highly perishable food, milk must be processed almost immediately after milking and can only be stored for a few days (when cooling technology is available). Nonetheless, this study shows that only 6% of Mexican DP operations have milk cooling systems. This reveals deficiencies in infrastructure that hinder the maximisation of benefits that more organised and technified producers can harvest. The use of infrastructure acquired by farmer associations or producer cooperatives may be an alternative to individually owned equipment. Nonetheless, less than 6% of producers declared to sell milk to a cooperative. While large- and small-scale specialised milk production systems are regularly well integrated for the commercialization of dairy products such as cheese, cream, yogurt, and processed milk (pasteurized, ultra-pasteurized, UHT) (Secretaría de Economía, 2012 ), the formation of integrated commercialization channels by organizations of DP smallholders is challenged by heterogenicity in technological, agro-ecological and socioeconomic conditions (Loera and Banda, 2017 ; Rangel et al., 2020 ). Therefore, access to cooling equipment and milk marketing undoubtedly remain amongst the main challenges to be solved by DP operations. Manual milking was declared by DP producers as the main method for obtaining milk from their cows (91.4%). As local poverty levels decrease and farm size increases, the use of mechanical milking becomes more frequent. This study also shows that DP operations are characterized by milking cows once a day (93%), typically with the presence of the calf to stimulate milk letdown (73%). In fact, similar management practices for the dual-purpose system have been described over time in Mexico (Magaña-Monforte et al ., 2008; Juárez-Barrientos et al., 2015 ), giving the appearance of little development in terms of technological input in DP operations (Pulido–Albores, 2001). This may partially stem from the fact that cattle farming remains a deeply traditional activity, where most producers grew up learning management practices that have remained virtually unchanged for generations (González-Padilla et al., 2019 ). Other factors such as market integration, instability in prices and inputs, poverty level, and farm size could also limit the adoption of technologies that have been proven to advance productivity and product quality on farms. Manual milking is in and of itself a risk factor to increase microbial contamination, which can be exacerbated by deficient hygienic practices and lack of infrastructure. A high proportion of farmers (over 75%) in Mexican DP operations (except for the Gulf region) reported performing teat cleansing prior to milking. In contrast, the implementation of teat dipping after milking and mastitis testing was very low (10.5% and 18%, respectively). The limited use of these two mastitis preventive measures could seem puzzling and give the appearance of obliviousness or disinterest by farmers in mastitis prevention. This, however, is not the case. In almost all operations (95.1%), calf rearing is done by allowing calves to suckle directly from the dam, where either one quarter of the mammary gland or residual milk is left for the calf to feed on. Typically, the cow and calf are joined immediately after the morning milking has taken place, and remain together for several hours, until they are separated again in the afternoon or early evening to allow for the cow to be milked again the following morning. Hence, use of a dipping solution interferes with the appropriate feeding of the calf since it remains on the skin of the teat and may contaminate the milk consumed by the calf. The importance of allowing the calf to feed after milking in decreasing mastitis presentation stems from the fact that all remaining milk in the udder is emptied by the suckling throughout the day (González-Sedano et al., 2010 ). Indeed, observational and experimental studies on tropical cattle have demonstrated a relationship between calf rearing systems and the occurrence of mastitis. Cross-sectional studies have identified the practice of residual calf sucking as a protective risk factor against subclinical mastitis (SM) (Kivaria et al., 2004 ; Mdegela et al., 2004 ; Karimuribo et al., 2006 ). Experimental studies have also reported that cows subjected to restricted suckling (when compared to cows on artificial calf rearing) had a lower incidence of subclinical (SM) (Margerison et al., 2002 ; Fröberg et al., 2007 ) and clinical mastitis (CM) (Mejía et al., 1998 ). Similarly, González-Sedano et al. ( 2010 ) reported higher prevalence of SM and CM in non-residual calf sucklers, compared to animals that continue to nurse their calves. The number of bacterial colony-forming units (including both mesophilic and coliforms) is also reduced when residual milk is consumed by the calf (González-Sedano et al. 2010 ). Few (4.41%) DP cattle farms in this study reported artificial calf feeding as a calf rearing system. While milk production increases when the calf is separated from its dam, this practice is only economically viable when the price of surplus milk exceeds the increased cost associated with labor, calf handling facilities and feeding. Special emphasis should be given to implementing good milking practices in DP units, as well as improving raw milk handling and methods for monitoring milk quality to encourage retail prices based on milk quality characteristics. Leaving residual milk or a quarter of the mammary gland for the calf to suckle can conversely have a negative impact on reproductive performance. The inhibitory effect of calf nursing on the reproductive parameters of cows is well known. Galina et al. ( 2001 ) reported that the presence of calves before/after milking delays the resumption of ovarian activity (i.e. lengthens post-partum anestrus). Therefore, management practices such as restricted suckling or partial/ temporary weaning can improve reproductive performance (Galina et al., 2001 ; Rojo-Rubio et al., 2009 ). As mentioned above, nearly 95% of dual-purpose operations rear their calves by allowing them to feed on the dam until weaning, and restricted suckling is used by only 13% of operations. Therefore, there is an opportunity to improve reproductive parameters by implementing calf-rearing and weaning strategies that minimize the negative impact of calf suckling on reproductive performance of dams. Improving cattle reproductive efficiency could also be one of the proven methods to increase milk production in the short to medium term. Technification of dual-purpose operations aiming to increase marketable milk, necessarily forces changes in the milking process with knock-on effects on other management practices. Cattle temperament and milking ease are important considerations for the employment of management practices. As mentioned, over 70% or producers use the calf as a stimulus to initiate milk letdown during milking. Having calves on-site during the milking process imposes management conditions that undermine mechanization and hygienic handling of milk. As an alternative oxytocin can be used to induce milk let-down. This study shows that only 14% of producers nationwide employ oxytocin, albeit its use is twice as prevalent in large farms (21%) and in humid tropical regions (27%). However, the daily use of oxytocin in DP cattle is controversial, since it could affect the length of the estrous cycle and pregnancy rate, due to its function as a regulator of corpora lutea regression at the end of diestrus (McCracken et al., 1999 ). Indeed, several authors report no effect of daily oxytocin administration on the length of the diestrus phase, or reproductive performance, while others describe that the use of oxytocin does not increase milk production and negatively affects reproductive parameters (Lammoglia et al. , 2014). It is possible that differences in these studies are influenced by experimental design, breed, type of calf rearing system, period, and dose of oxytocin use. Thus, possible differences in negative effects of daily oxytocin injections should not be overlooked. In conclusion, dual-purpose cattle farming is an important economic and social activity in Mexico. Weaned calves and milk are the main products, but most farmers remain detached from the benefits of the final product. Farmer integration into cooperatives could be an alternative for commercialization and addressing deficient infrastructure. However, this shift is hindered by socioeconomic, agro-ecological, and technological operation heterogeneities. Hence, marketing remains a challenge to be solved by DP farms. Crossbreeding of local cattle with specialised dairy breeds has been the genetic strategy to improve milk production. However, this strategy faces the difficulty of maintaining hybrid vigor and productivity beyond the initial crosses. Genomic selection could aid in the development of breeding indexes tailored for local environmental conditions. Although, this approach is technically the way forward, it requires long term commitments from farmers and, in most instances, government institutions. Calf rearing and milking, although central to the productive process, remain largely untechnified, with milking machines and cooling systems absent from the great majority of operations (94%). Implementing changes in the milking process would demand changes in cattle management (particularly the current need for the calf presence during milking) and farm economy. In the meantime, emphasis should be placed on implementing good milking practices, and calf-rearing and weaning strategies. Declarations Acknowledgements. Authors wish to thank field professional personnel that administered the question­naires and captured data. Statements and Declarations Funding . This research was commissioned and supported by Secretaría de Agricultura, Ganadería, Pesca y Alimentación (SAGARPA), México, project No. 32239-1463-2- VIII-12. Conflict of interest . The authors declare no competing interests. Data Availability. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Authors´ contributions . Lassala, Arantzatzu: Methodology design, data collection, curation and analysis, preparation, edition and writing of the final manuscript. Alonso-Díaz, Miguel Ángel: preparation, editing and writing of the final manuscript. Corro-Morales, Manuel: preparation, editing and writing of the final manuscript. González-Padilla, Everardo: Formulation and supervision of the project, preparation, editing and writing of the final manuscript. Gutiérrez, Carlos G: Formulation and supervision of the project and methodology design; data curation and analysis, preparation, editing and writing of the final manuscript. References Aguilar-Jiménez, J.R., Aguilar-Jiménez, C.E., Hernández, F.G., Galdámez, J.G., Aguilar, F.B., Arias, M.A., Camacho, H.O., Acero, M.A., Toral, J.N., 2023. Classification and characterization of family cattle farming systems of the Frailesca region of Chiapas, Mexico, considering the contribution of cattle raising to family income, Tropical and Subtropical Agroecosystems, 26, 1–12. Albarrán-Portillo, B., Rebollar-Rebollar, S., García-Martínez, A., Flores-Najera, G., García-Vázquez, Z., 2015. Socioeconomic and productive characterization of dual-purpose farms oriented to milk production in a subtropical region of Mexico, Tropical Animal Health and Production, 47, 519–523. CONAPO. Índice de marginación municipal. In: Consejo Nacional de Población. 2013. http://www.conapo.gob.mx/es/CONAPO/Indices_de_ Marginacion_Publicaciones . Accessed 8th August, 2022. Cuevas-Reyes, V., Rosales-Nieto, C., 2018. Caracterización del sistema bovino doble propósito en el noroeste de México: productores, recursos y problemática, Revista MVZ Córdoba, 23, 6448–6460. Espinosa Garcia, J.A., Veléz Izquierdo, A., Cuevas Reyes, V., Góngora González, S.F., V|azquez Gómez, R., Rivera Maldonado, J.A., 2018. Evaluation of impact on productivity and profitability of technology in the bovine system of double purpose of the Mexican tropic, Tropical and Subtropical Agroecosystems, 21, 261–272. FAO. Livestock production in Latin America and the Caribbean. In: Regional Office for Latin America and the Caribbean. FAO. 2023a https://www.fao.org/americas/priorities/produccion-pecuaria/ar/ . Accessed on May 11th, 2023. FAO. Gateway to dairy production and products. In: FAO. 2023b. https://www.fao.org/dairy-production-products/production/production-systems/en/ . Accessed on 11th May, 2023. Fedegan. Inventario ganadero 2022. In: Federación Colombiana de Ganaderos. 2023. https://www.fedegan.org.co/estadisticas/inventario-ganadero . Accessed on 11th May, 2023. Fröberg, S., Aspegren-Güldorff, A., Olsson, I., Marin, B., Berg, C., Hernández, C., Galina, C.S., Lidfors, L., Svennersten-Sjaunja, K., 2007. Effect of restricted suckling on milk yield, milk composition and udder health in cows and behaviour and weight gain in calves, in dual-purpose cattle in the tropics, Tropical Animal Health and Production, 39, 71–81. Galina, C.S., Rubio, I., Basurto, H., Orihuela, A., 2001. Consequences of different suckling systems for reproductive and productivity of cattle in tropical conditions, Applied Animal Behaviour Science 72, 255–262. García, E., 2004. Modificaciones al Sistema de clasificación climática de Koppen. 5ª ed. Instituto de Geografía, UNAM, México. González-Quintero, R., Barahona-Rosales, R., Bolívar-Vergara, D.M., Chirinda, N., Arango, J., Pantévez, H.A., Correa-Londoño, G., Sánchez-Pinzón, M.S., 2020. Technical and environmental characterization of dual-purpose cattle farms and ways of improving production: A case study in Colombia, Pastoralism, 10, 1–14. González-Padilla, E., Lassala, A., Pedernera, M., Gutierrez, C.G., 2019. Cow-calf management practices in Mexico: Farm organization and infrastructure, Veterinaria México, 6, 1–17. González-Sedano, M., Marín-Mejía, B., Maranto, M.I., Leme de Magalhães-Labarthe, A.C., Alonso-Díaz, M.A., 2010. Effect of residual calf suckling on clinical and sub-clinical infections of mastitis in dual-purpose cows: Epidemiological measurements, Research in Veterinary Science, 89, 362–366. Granados-Rivera, L.D., Quiroz-Valiente, J., Maldonado-Jáquez, J.A., Granados-Zurita, L., Díaz-Rivera, P., Oliva-Hernández, J., 2018. Caracterización y tipificación del sistema doble propósito en la ganadería bovina del Distrito de Desarrollo Rural 151, Tabasco, México, Acta Universitaria, 28, 47–57. Hemme, T., Otte, J. Status and prospects for smallholder milk production: A global perspective. In: Pro-Poor Livestock Policy Initiative, Rome, FAO. 2010. http://www.fao.org/3/i1522e/i1522e.pdf . Accessed on 11th May, 2023. INEGI. Ganadería. Existencias de bovinos por función y actividad zootécnica. In: INEGI, Economía y sectores productivos. 2019. https://www.inegi.org.mx/temas/ganaderia/#Tabulados ; and https://www.cuentame.inegi.org.mx/economia/primarias/gana/default.aspx?tema=e . Accessed on April 25th, 2023. Juárez-Barrientos, J.M., Herman-Lara, E., Soto-Estrada, A., Ávalos-de la Cruz, D.A., Vilaboa-Arroniz, J., Díaz-Rivera, P., 2015. Tipificación de sistemas de doble propósito para producción de leche en el Distrito de Desarrollo Rural 008, Veracruz, México. Revista Científica, 25, 317–323. Karimuribo, E.D., Fitzpatrick, J.L., Bell, C.E., Swai, E.S., Kambarage, D.M., Ogden, N.H., Bryant, M.J., French N.P., 2006. Clinical and subclinical mastitis in smallholder dairy farms in Tanzania: risk, intervention and knowledge transfer, Preventive Veterinary Medicine, 74, 84–98. Kivaria, F.M., Noordhuizen, J.P.T.M., Kapaga, A.M., 2004. Risk indicators associated with subclinical mastitis in smallholder dairy cows in Tanzania, Tropical Animal Health and Production, 36, 581–592. Lammoglia, M. A., Mancera, B. D., Alarcón, M. A., Cabrera, A., Daniel, A.I., 2015. Effects of routinely oxytocin injection to induce milk ejection on some reproductive parameters of crossbred cows in the tropics of Veracruz, Annual Research & Review in Biology, 297–303. Lassala, A., Hernández-Cerón, J., Pedernera, M., González-Padilla, E., Gutierrez, C.G., 2020. Cow-calf management practices in Mexico: Reproduction and breeding, Veterinaria México, 7, 1–15. Loera, J. and Banda, J., 2017. Industria lechera en México: parámetros de la producción de leche y abasto del mercado interno, Revista de Investigaciones Altoandinas 19, 419–426. Magaña-Monforte J, Ríos- Arjona G, Martínez- González JC. 2006. Los sistemas de doble propósito y los desafíos en los climas tropicales en México, Archivos Latinoamericanos de Producción Animal, 14, 105–114. Margerison, J.H., Preston, T.R., Phillips, J.C., 2002. Restricted suckling of tropical dairy cows by their own calf or other cows’ calves, Journal of Animal Science, 80, 1663–1670. Martínez LD, Caamal Cauich I, Pat Fernández LA, Pérez Fernández A, Torres GP, Tello, Anguebes Franceschi FP. 2019. Impacto de los cambios en el ingreso sobre la demanda de carnes en México, Revista Mexicana de Ciencias Agrícolas, 10, 511–523. McCracken, J.A., Custer, E.E., Lamsa, J.C., 1999. Luteolysis: a neuroendocrine-mediated event, Physiological Reviews, 79, 263–323. McDowell, R.E., 1985. Crossbreeding in tropical areas with emphasis on milk, health, and fitness, Journal of Dairy Science 68, 2418–2435. Mdegela, R.H., Kusilika, L.J.M., Kapaga, A.M., Karimuribo, E.D., Turuka, F.M., Bundala, A., Kivaria, F., Kabula, B., Manjurano, A., Loken, T. and Kambarage, D.M., 2004. Prevalence and determinants of mastitis and milk-borne zoonoses in smallholder dairy farming sector in Kibaha and Morogoro districts in Eastern Tanzania, Journal of Veterinary Medicine B, 51, 123–128. Mejía, C.E., Preston, T.R., Fajersson, P., 1998. Effects of restricted suckling versus artificial rearing on milk production, calf performance and reproductive efficiency of dual purpose Mpwapwa cattle in a semi-arid climate, Livestock Research for Rural Development 10. Mrode, R., Ojango, J. M. K., Okeyo, A. M., Mwacharo, J. M. 2019. Genomic selection and use of molecular tools in breeding programs for indigenous and crossbred cattle in developing countries: Current status and future prospects, Frontiers in genetics, 9 , 694. Pulido-Albores, A.R., 2001. Evaluation of the impact of a technology transfer programme on dual purpose cattle production systems in Veracruz, Mexico. PhD. Thesis. Imperial College London, University of London. Rangel, J., Perea, J., De-Pablos-Heredero, C., Espinosa-García, J.A., Toro Mujica, P., Feijoo, M., Barba, C., García, A., 2020. Structural and technological characterization of tropical smallholder farms of dual-purpose cattle in Mexico, Animals, 10, 86. Rojo-Rubio, R., Vázquez-Armijo, J.F., Pérez-Hernández, P., Mendoza-Martínez, G.D., Salem, A.Z., Albarrán-Portillo, B.E., González-Reyna, A.R., Hernández-Martínez, J., Rebollar-Rebollar, S.A., Cardoso-Jiménez, D.A., Dorantes-Coronado, E.J., Gutiérrez-Cedillo, J.G., 2009. Dual Purpose cattle production in Mexico, Tropical Animal Health and Production, 41, 715–721. Ruiz-Guevara, C., Hernández, L.A.G, Bello, C.H.A., Pérez, L.B., 2008. Sustentabilidad financiera: el caso de una empresa ganadera de bovino de doble propósito, Revista Mexicana de Agronegocios, 22, 503–515. Secretaría de Economía. 2012. Análisis del sector lácteo en México. Dirección General de Industrias Básicas, pp. 1–29. https://www.economia.gob.mx/files/comunidad_negocios/industria_comercio/informacionSectorial/analisis_sector_lacteo.pdf . Accessed on 12 May, 2023. USDA. Beef Cow-calf Management Practices in the United States. Beef 2007-08. In: Animal and Plant Health Inspection Service. U.S. Department of Agriculture. 2008. https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/monitoring-and-surveillance/nahms/nahms_beef_cowcalf_studies . Accessed on 2008. VSN International. 2022. Genstat for Windows 22nd Edition. VSN International, Hemel Hempstead, UK. 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Introduction","content":"\u003cp\u003eDual-purpose cattle farming is a production system in which both milk and calves are generated simultaneously, primarily under grazing conditions. While this is a less productive and efficient system than specialised milk or beef operations (Ruiz-Guevara et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gonz\u0026aacute;lez-Quintero et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), it has a significant socioeconomic importance due to its low-investment requirements and flexibility (Rojo-Rubio et al, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In Latin America and the Caribbean, dual-purpose farms are often run by smallholders and are prevalent in rural areas (FAO. 2023a). Indeed, up to 95% of the milk and its derivatives produced on DP farms are destined for self or local consumption, benefiting the microeconomy and playing an important role in food security and supply (FAO, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Mexico and Colombia, dual-purpose cattle farms account for 12.2% and 35% of the national cattle herds respectively (INEGI, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fedegan, 2022). Moreover, the FAO estimates that up to 90% of the milk produced in developing countries could come from dairy and dual-purpose smallholders (FAO, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Challenges for farmers include restricted access to markets, inadequate infrastructure, low productivity, and limited utilisation of veterinary services (Hemme and Otte, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies on dual-purpose cattle management systems have assessed the implementation of strategic practices to enhance productivity and sustainability and improve the livelihoods of farmers. Researchers found that the adoption of technology to advance herd management, nutrition, controlled breeding, genetic selection, mechanical milking, and animal health can improve milk and meat production, reduce production costs, and ameliorate the quality of products (Rojo-Rubio et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Espinosa Garcia et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These findings indicate that continued research and implementation of appropriate management practices are crucial to enhancing productivity. They also suggest that appropriate institutional support and policies are needed to improve producer income while reducing the environmental footprint of dual-purpose livestock production.\u003c/p\u003e \u003cp\u003ePrevious studies that investigated the adoption of desirable practices highlight the diverse nature of dual-purpose operations in Mexico. Nonetheless, they are limited in their reach as they have primarily focused on farms located in the humid (Gulf region) or dry (Pacific region) tropical environments (Cuevas Reyes and Rosales-Nieto 2018; Granados-Rivera et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rangel et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Aguilar-Jim\u0026eacute;nez et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the present work aimed to address this gap by characterising management practices of dual-purpose cattle production systems across all climatic and geographical regions of Mexico. The goal was to better understand the strengths and weaknesses of the production system, as well as the opportunities, needs and preferences of farmers.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eManagement practices and use of technology in grazing cattle production units in Mexico were characterized by a structured questionnaire. This instrument gathered descriptive information related to farm organization, herd management, occurrence of infrastructure, feeding practices, health and well-being, environmental management practices, reproductive management, dual-purpose systems, and a section devoted to specialized dairy production in pasture. Results of this work comprise characterization of management practices of dual-purpose operations.\u003c/p\u003e \u003cp\u003eThe methods and questionnaire are described in Gonz\u0026aacute;lez-Padilla et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Briefly, the questionnaire was adapted from the one used by the United States Department of Agriculture (USDA, 2008) to characterise beef-calf management practices, with adjustments and suggestions from experienced academics, practitioners, and farmers from different regions of Mexico. The sample size was calculated with a 95% confidence level, with a probability (p) of 50% and an estimated error (d) of 5%.\u003c/p\u003e \u003cp\u003eThe calculated number of questionnaires to be administered was 3158 (Gonz\u0026aacute;lez-Padilla et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A total of 3311 questionnaires were completed, with 31 being discarded due to answer discrepancies. The final number of surveyed dual purpose (DP) operations was 996.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEach option within a question was considered as a binary variable. For questions that specified that a single response should be chosen, the frequency of a management practice was analyzed by REML (Genstat 22nd ed.; VSN international, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For questions that allowed more than one answer, each selection was analyzed separately by univariate analysis. The results are presented as least square means with the standard error of the difference (sed). Differences were considered significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eFixed variables were considered as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- Herd size: Herds were classified as small (up to 35 cows), medium (36 to 100 cows), or large (over 100 cows).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Region: The country was divided in five regions based on similarity of agro-ecological characteristics and geographical proximity: North (Baja California, Baja California Sur, Chihuahua, Coahuila, Durango, Nuevo Leon, Sonora and Zacatecas); Center (Aguascalientes, Estado de Mexico, Guanajuato, Hidalgo, Puebla, Queretaro, San Luis Potosi and Tlaxcala); Pacific (Chiapas, Colima, Guerrero, Jalisco, Michoacan, Morelos, Nayarit, Oaxaca and Sinaloa); Gulf (Tabasco, Tamaulipas and Veracruz), and Peninsula (Campeche, Quintana Roo and Yucatan).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Climate: Climates were classified as arid-semiarid, temperate, dry tropics and humid tropics, according to Garc\u0026iacute;a (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-Poverty levels: Poverty levels were defined using municipal categories set by the National Population Council (CONAPO, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) as very low, low, medium, high, or very high.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-Land-tenure: Land-tenure type was declared by the producer as communal land, ejido or private property.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003eDual-purpose cow-calf production units were found to be distributed across the country. The predominant type of cattle used in these operations is European dairy x Zebu crossbreeds (54.7%). These cattle were most popular in the tropics with 78% and 56% for the humid and dry topics, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, in temperate climates, European beef x Zebu crossbreeds were the most frequent cattle type (63.11%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Moreover, the Gulf and Peninsula regions had the highest proportion of dairy x Zebu crossbred cattle, while in the Center and North regions, European beef cattle and their crosses with Zebu predominated (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The frequency of farms that declared having pure specialized dairy breeds, European beef, pure Zebu, or criollo were found to be under 6%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCattle breed prevalence in dual-purpose operations in the different regional and climate environments in Mexico (% of Dual-purpose operations *).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean Beef.Zebu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEuropean Beef\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZebu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCriollo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEuropean Dairy.Zebu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDairy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCenter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeninsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFarm products and marketing\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWeaned calves (aged 6 to 12 months) and dairy products were the two primary products of DP systems (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, a higher proportion of operations in tropical (dry and humid) climates sell dairy products compared to those in arid and temperate climates. Additionally, a larger percentage of production units in temperate climates sell finalized cattle (14.6% \u003cem\u003evs\u003c/em\u003e. 6% in other climate regions). Although weaned calves are the main product sold, production units in temperate climates tend to keep their calves on pasture for longer periods.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFarm products declared as the most important for dual-purpose farmers of different climate conditions in Mexico (% of dual-purpose operations *).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeaned calves\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDairy Products\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBack- grounders\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFattened animals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBreeding stock\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePregnant cows\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding marketing of milk production, a higher proportion of operations in temperate climates sell raw milk compared to those in arid and tropical climates (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Dairy products, following in-farm milk processing, are sold by 32.5% of DP farmers. However, differences were observed according to climate region (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In arid and semi-arid climates, milk is processed more frequently (66%), followed by production units located in the temperate climate (49%). Conversely, farms in the dry and humid tropics process their milk less frequently. In general, fluid milk is primarily sold to local cheese makers (49.8%), which is particularly apparent in the Gulf and Peninsula regions (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), whilst the lowest frequency is observed in the northern region. Retail sale of raw milk was declared as the third more common form of milk marketing in DP farms (23.6%), with this practice being more common in the temperate climates and central region of the country. Moreover, less than 6% of producers acknowledged selling milk to dairy cooperatives and pasteurization plants (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Finally, only 6.3% of operations have milk cooling systems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDairy product marketing in dual-purpose operations in different regional and climate regions in Mexico\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDairy Products\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCheese maker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFluid milk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCo-op\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCenter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeninsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eMilk Production Process\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNinety one percent of DP operations milk their cows manually, whilst only 8.6% use mechanical milking, half of which use portable units. Private operations are four times more likely to have automatic milking systems (13.9%) than ejidos or those using communal land for grassing. Similarly, milking machines are found twice as often in medium and large operations compared to small farms (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Additionally, 19% of DP production units located in municipalities with very low poverty level reported using mechanical milking systems, indicating a three-fold higher frequency than farms in areas with higher poverty levels (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportion of dual-purpose operations that milk the cows manually or by mechanical, fixed or portable, milking systems, according to herd size, land tenure type and poverty level in Mexico.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMechanical Milking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eManual\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFixed unit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePortable unit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHerd Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLand Tenure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEjido\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery Low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMilking frequency was declared to be once a day in 93% of dual-purpose farms, with only 7% of operations stating to milk twice a day. Operations located in very low poverty municipalities reported milking more frequently than DP farms located in other poverty groups (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportion of dual-purpose farms milking the cows once or twice daily according to poverty level of the municipality where they operate.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnce a day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eTwice a day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e93.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery Low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e79.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e93.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e94.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e97.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, as the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRoughly half of the DP operations declared measuring milk production daily. However, the survey did not distinguish whether this measurement was done in bulk or per cow. Since milk gets sold every day due to the lack of refrigeration infrastructure, there is a need to measure production at least in bulk, but no cow information is registered by farmers for selection or for record keeping purposes. As milk production in DP cattle typically decreases after six months of lactation, low productivity was reported as the main reason for drying the cows. Drying due to advanced pregnancy, and thus advanced lactation, was declared as a management practice in 27.5% of DP operations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCalf rearing\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe main calf rearing system used by DP farms is allowing the calf to suckle (95.1%), with artificial rearing reported in only 4.9% of operations. The most common rearing practice is to reserve all the milk from one quarter of the udder for the calf (65%), followed by leaving residual milk after milking (20.7%). The practice of leaving one quarter of the udder for the calf to suckle is twice as frequent in dry and humid tropical climates compared to arid and temperate climates (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of udder quarters left for the calf to suckle.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOne Qrt.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTwo Qtrs.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThree Qtrs.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eResidual milk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEighty four percent of operations reported weaning their calves between 6 months and one year of age. Of the remaining operations, almost one percent weaned their animals at less than 5 days old, whilst 7% ablactated calves when they reached over a year old. The most frequent declared method for weaning was by the sudden separation of calves and cows, followed by gradual separation (16.8%) and the use of a nose flap (12.6%).\u003c/p\u003e \u003cp\u003eMilk letdown stimulation in cows before milking was most frequently induced by the presence of the calf (73.2%) in DP farms. Pure conditioning (\u003cem\u003ei.e.\u003c/em\u003e no stimuli or manual stimuli) without the use of external aids was reported as a management practice in 15% of operations. The use of oxytocin was reported in 13.9% of DP production units. Moreover, the use of oxytocin treatment was higher in dry and humid tropical regions and in large herds (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of the stimuli used in dual purpose operations in Mexico to induce milk let-down at milking according to herd size and climate regions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eManual\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOxytocin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHerd Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSanitary practices in the milking process\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRegarding sanitary practices, 73.5% of farms reported cleaning the teats of the udder prior to milking (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Teat cleansing was less common in the humid tropics than in other climate regions. Teat dipping after milking is generally low in dual purpose operations (10.5%), with a slight increase in frequency in farms located in municipalities with low poverty levels. In addition, only 18% of DP operations routinely use mastitis diagnosis tests and, as with teat dipping, this practice increases in low poverty municipalities (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of sanitary practices in the milking process of dual-purpose operations in Mexico according to climate and geographic regions, and poverty level.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTeat cleansing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTeat dipping\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMastitis tests\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eSed\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArid and Semi-Arid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHumid Tropic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCenter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGulf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeninsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery Low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e* The sum of the proportions in a given row can differ from 100%, since the presented values correspond to minimum quadratic means and/or because more than one answer was possible. \u003cem\u003eSed\u003c/em\u003e-Standard error of the difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eResults from this study show that dual purpose farmers declare weaned calves as the main product of their enterprise, followed by dairy products. The prevailing livestock genotype in production units varied between regions, with preferences leaning towards European Dairy x Zebu crosses in tropical climates, and European beef x Zebu in temperate climates. Milk is mainly drawn once a day manually, with the calf used as an aid for milk letdown. Obtained milk is mostly sold at retail or to local cheese factories.\u003c/p\u003e \u003cp\u003eDual purpose cattle farmers typically have crossbred animals obtained by mating locally existing cattle (\u003cem\u003ei.e.\u003c/em\u003e cattle adapted and homegrown for generations) with exotic improved breeds. This crossbreeding practice has resulted in increased milk yield and offspring fitness (McDowell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). European dairy x Zebu crossbreeds are the predominant genotype found in tropical climates (54.7%), benefiting from the resilience of Zebu cattle to harsh environmental conditions (increasingly exacerbated by climate change) and the ability of European breeds to produce milk or meat. This genetic mixture has been shown to increase milk and meat yield under heterogeneous systems (Rangel et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Indeed, heterosis when Zebu and dairy cattle are crossbred allows for better milk production in the characteristically higher parasite load, elevated temperature-humidity index (THI), and low pasture quality conditions that prevail in tropical climates (Maga\u0026ntilde;a-Monforte \u003cem\u003eet al\u003c/em\u003e., 2008). In contrast, Zebu-type cattle are crossbred in a greater proportion to European beef-type cattle in temperate climate regions (63%). Moreover, European dual-purpose breeds are frequently chosen for crossbreeding. However, the survey questions were not designed to discern between European dual-purpose or European beef breeds. Furthermore, male calves sired by a dairy bull typically sell at lower prices than those sired by a beef European bull. Hence, the use of beef European breeds for dual-purpose systems in temperate climates may obey to the demand of beef-type calves from feedlots that deliver to the export market in central and northern regions of Mexico (Gonz\u0026aacute;lez-Padilla et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Whilst this study was not designed to determine the proportion of Zebu vs European blood (dairy or beef) in animals found in dual-purpose herds, others have shown that the advantages obtained by crossbreeding are greatest in the first generation (F1), but gains are partially lost thereafter. In fact, besides F1 offspring (50% exotic genetics), the more stable production performance is achieved at 62.5% (between 50 to 75%) of exotic genetics (McDowell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). However, the introduction of exotic breeds, regardless of the genetic background of the local herd, has been shown to have a beneficial effect on productive parameters (McDowell, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Nevertheless, there has been a lack of breeding guidelines (set either by the government or by farmer organisations) to establish how to attain and maintain an ideal percentage of exotic \u003cem\u003evs\u003c/em\u003e. native genetics within herds to enhance productivity. In addition, breeding programmes for crossbred cattle need to operate within the country\u0026acute;s developing goals and are often contingent to long-term policies and financial support.\u003c/p\u003e \u003cp\u003eGonz\u0026aacute;lez-Padilla et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported that the prevalence of pure Zebu and criollo cattle in Mexico has decreased to a third of what it was in the late 1970\u0026rsquo;s. Despite this decline, the input of Zebu type cattle remains high and continues to form the basis of dual-purpose herds. Dual-purpose operations are widespread throughout Mexico but are predominantly comprised of small holders who are scarcely technified and have a low organizational information and record keeping culture (Gonz\u0026aacute;lez-Padilla et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a result, systematic genetic evaluation of dual-purpose cattle is limited and mainly conducted in research stations ran by government agencies or universities. Zebu progeny evaluations are scarce, albeit purebred Zebu cattle associations working under tropical conditions are producing genetic information for productive and fitness parameters. The advent of genomic selection strategies, in concert with traditional genetic methods, can potentially accelerate selection and highlight elite genetics evaluated under specific environmental conditions (Mrode et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, to fully utilize these technologies, the cow-calf system must overcome its poor record keeping culture (Gonz\u0026aacute;lez-Padilla et al, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and further the use of reproductive technologies such as artificial insemination (Lassala et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, over eighty percent of farmers declared the calf as one of the two main products of their operation. Indeed, Albarr\u0026aacute;n-Portillo et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) estimated that calves represent 30 to 50% of the annual income of the farm, cashed once or twice a year, providing a source of savings that can be allocated to investments in other inputs or activities. Most weaned calves from DP farms are sold domestically to brokers or middlemen who deliver animals to backgrounding or feedlot systems throughout the country. As a result, the producer remains detached from finalizing the calf and thus from the potential economic benefits of marketing this end product. In addition, the prize of the calf can be influenced by intrinsic traits (such as breed, gender, age, body condition score, weight, coat color, etc.) that may impact the quality of the meat, and by factors such as distance from the point of sale to feedlots, as well as economic circumstances and market perception linked to the elasticity of the demand (Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe second most reported product for DP units was raw milk and dairy products. Interestingly, over 30% of producers did not consider milk as a primary product of their operation, even when milk production provides a stable income that allows DP operations to cover daily costs, supplying cash flow that families rely upon. Nonetheless, most DP operations are integrated into their local market through the sale of retailed raw milk and cheese, stimulating the regional economy. Overall, the main route for DP farm milk marketing across Mexico is as fluid milk, sold either to local cheese factories (49.8%), as in-house processed dairy products (32.5%) or as retailed raw milk (23.6%). As a highly perishable food, milk must be processed almost immediately after milking and can only be stored for a few days (when cooling technology is available). Nonetheless, this study shows that only 6% of Mexican DP operations have milk cooling systems. This reveals deficiencies in infrastructure that hinder the maximisation of benefits that more organised and technified producers can harvest. The use of infrastructure acquired by farmer associations or producer cooperatives may be an alternative to individually owned equipment. Nonetheless, less than 6% of producers declared to sell milk to a cooperative. While large- and small-scale specialised milk production systems are regularly well integrated for the commercialization of dairy products such as cheese, cream, yogurt, and processed milk (pasteurized, ultra-pasteurized, UHT) (Secretar\u0026iacute;a de Econom\u0026iacute;a, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), the formation of integrated commercialization channels by organizations of DP smallholders is challenged by heterogenicity in technological, agro-ecological and socioeconomic conditions (Loera and Banda, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rangel et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, access to cooling equipment and milk marketing undoubtedly remain amongst the main challenges to be solved by DP operations.\u003c/p\u003e \u003cp\u003eManual milking was declared by DP producers as the main method for obtaining milk from their cows (91.4%). As local poverty levels decrease and farm size increases, the use of mechanical milking becomes more frequent. This study also shows that DP operations are characterized by milking cows once a day (93%), typically with the presence of the calf to stimulate milk letdown (73%). In fact, similar management practices for the dual-purpose system have been described over time in Mexico (Maga\u0026ntilde;a-Monforte \u003cem\u003eet al\u003c/em\u003e., 2008; Ju\u0026aacute;rez-Barrientos et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), giving the appearance of little development in terms of technological input in DP operations (Pulido\u0026ndash;Albores, 2001). This may partially stem from the fact that cattle farming remains a deeply traditional activity, where most producers grew up learning management practices that have remained virtually unchanged for generations (Gonz\u0026aacute;lez-Padilla et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Other factors such as market integration, instability in prices and inputs, poverty level, and farm size could also limit the adoption of technologies that have been proven to advance productivity and product quality on farms.\u003c/p\u003e \u003cp\u003eManual milking is in and of itself a risk factor to increase microbial contamination, which can be exacerbated by deficient hygienic practices and lack of infrastructure. A high proportion of farmers (over 75%) in Mexican DP operations (except for the Gulf region) reported performing teat cleansing prior to milking. In contrast, the implementation of teat dipping after milking and mastitis testing was very low (10.5% and 18%, respectively). The limited use of these two mastitis preventive measures could seem puzzling and give the appearance of obliviousness or disinterest by farmers in mastitis prevention. This, however, is not the case. In almost all operations (95.1%), calf rearing is done by allowing calves to suckle directly from the dam, where either one quarter of the mammary gland or residual milk is left for the calf to feed on. Typically, the cow and calf are joined immediately after the morning milking has taken place, and remain together for several hours, until they are separated again in the afternoon or early evening to allow for the cow to be milked again the following morning. Hence, use of a dipping solution interferes with the appropriate feeding of the calf since it remains on the skin of the teat and may contaminate the milk consumed by the calf. The importance of allowing the calf to feed after milking in decreasing mastitis presentation stems from the fact that all remaining milk in the udder is emptied by the suckling throughout the day (Gonz\u0026aacute;lez-Sedano et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Indeed, observational and experimental studies on tropical cattle have demonstrated a relationship between calf rearing systems and the occurrence of mastitis. Cross-sectional studies have identified the practice of residual calf sucking as a protective risk factor against subclinical mastitis (SM) (Kivaria et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Mdegela et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Karimuribo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Experimental studies have also reported that cows subjected to restricted suckling (when compared to cows on artificial calf rearing) had a lower incidence of subclinical (SM) (Margerison et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Fr\u0026ouml;berg et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and clinical mastitis (CM) (Mej\u0026iacute;a et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Similarly, Gonz\u0026aacute;lez-Sedano et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) reported higher prevalence of SM and CM in non-residual calf sucklers, compared to animals that continue to nurse their calves. The number of bacterial colony-forming units (including both mesophilic and coliforms) is also reduced when residual milk is consumed by the calf (Gonz\u0026aacute;lez-Sedano et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Few (4.41%) DP cattle farms in this study reported artificial calf feeding as a calf rearing system. While milk production increases when the calf is separated from its dam, this practice is only economically viable when the price of surplus milk exceeds the increased cost associated with labor, calf handling facilities and feeding. Special emphasis should be given to implementing good milking practices in DP units, as well as improving raw milk handling and methods for monitoring milk quality to encourage retail prices based on milk quality characteristics.\u003c/p\u003e \u003cp\u003eLeaving residual milk or a quarter of the mammary gland for the calf to suckle can conversely have a negative impact on reproductive performance. The inhibitory effect of calf nursing on the reproductive parameters of cows is well known. Galina et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) reported that the presence of calves before/after milking delays the resumption of ovarian activity \u003cem\u003e(i.e.\u003c/em\u003e lengthens post-partum anestrus). Therefore, management practices such as restricted suckling or partial/ temporary weaning can improve reproductive performance (Galina et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Rojo-Rubio et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). As mentioned above, nearly 95% of dual-purpose operations rear their calves by allowing them to feed on the dam until weaning, and restricted suckling is used by only 13% of operations. Therefore, there is an opportunity to improve reproductive parameters by implementing calf-rearing and weaning strategies that minimize the negative impact of calf suckling on reproductive performance of dams. Improving cattle reproductive efficiency could also be one of the proven methods to increase milk production in the short to medium term.\u003c/p\u003e \u003cp\u003eTechnification of dual-purpose operations aiming to increase marketable milk, necessarily forces changes in the milking process with knock-on effects on other management practices. Cattle temperament and milking ease are important considerations for the employment of management practices. As mentioned, over 70% or producers use the calf as a stimulus to initiate milk letdown during milking. Having calves on-site during the milking process imposes management conditions that undermine mechanization and hygienic handling of milk. As an alternative oxytocin can be used to induce milk let-down. This study shows that only 14% of producers nationwide employ oxytocin, albeit its use is twice as prevalent in large farms (21%) and in humid tropical regions (27%). However, the daily use of oxytocin in DP cattle is controversial, since it could affect the length of the estrous cycle and pregnancy rate, due to its function as a regulator of corpora lutea regression at the end of diestrus (McCracken et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Indeed, several authors report no effect of daily oxytocin administration on the length of the diestrus phase, or reproductive performance, while others describe that the use of oxytocin does not increase milk production and negatively affects reproductive parameters (Lammoglia \u003cem\u003eet al.\u003c/em\u003e, 2014). It is possible that differences in these studies are influenced by experimental design, breed, type of calf rearing system, period, and dose of oxytocin use. Thus, possible differences in negative effects of daily oxytocin injections should not be overlooked.\u003c/p\u003e \u003cp\u003eIn conclusion, dual-purpose cattle farming is an important economic and social activity in Mexico. Weaned calves and milk are the main products, but most farmers remain detached from the benefits of the final product. Farmer integration into cooperatives could be an alternative for commercialization and addressing deficient infrastructure. However, this shift is hindered by socioeconomic, agro-ecological, and technological operation heterogeneities. Hence, marketing remains a challenge to be solved by DP farms.\u003c/p\u003e \u003cp\u003eCrossbreeding of local cattle with specialised dairy breeds has been the genetic strategy to improve milk production. However, this strategy faces the difficulty of maintaining hybrid vigor and productivity beyond the initial crosses. Genomic selection could aid in the development of breeding indexes tailored for local environmental conditions. Although, this approach is technically the way forward, it requires long term commitments from farmers and, in most instances, government institutions.\u003c/p\u003e \u003cp\u003eCalf rearing and milking, although central to the productive process, remain largely untechnified, with milking machines and cooling systems absent from the great majority of operations (94%). Implementing changes in the milking process would demand changes in cattle management (particularly the current need for the calf presence during milking) and farm economy. In the meantime, emphasis should be placed on implementing good milking practices, and calf-rearing and weaning strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u003c/strong\u003eAuthors wish to thank field professional personnel that administered the question\u0026shy;naires and captured data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatements and Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThis research was commissioned and supported by Secretar\u0026iacute;a de Agricultura, Ganader\u0026iacute;a, Pesca y Alimentaci\u0026oacute;n (SAGARPA), M\u0026eacute;xico, project No. 32239-1463-2- VIII-12.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e. The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability.\u003c/strong\u003e The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026acute; contributions\u003c/strong\u003e. Lassala, Arantzatzu: Methodology design, data collection, curation and analysis, preparation, edition and writing of the final manuscript. Alonso-D\u0026iacute;az, Miguel \u0026Aacute;ngel: preparation, editing and writing of the final manuscript. Corro-Morales, Manuel: preparation, editing and writing of the final manuscript. Gonz\u0026aacute;lez-Padilla, Everardo: Formulation and supervision of the project, preparation, editing and writing of the final manuscript. Guti\u0026eacute;rrez, Carlos G: Formulation and supervision of the project and methodology design; data curation and analysis, preparation, editing and writing of the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAguilar-Jim\u0026eacute;nez, J.R., Aguilar-Jim\u0026eacute;nez, C.E., Hern\u0026aacute;ndez, F.G., Gald\u0026aacute;mez, J.G., Aguilar, F.B., Arias, M.A., Camacho, H.O., Acero, M.A., Toral, J.N., 2023. Classification and characterization of family cattle farming systems of the Frailesca region of Chiapas, Mexico, considering the contribution of cattle raising to family income, Tropical and Subtropical Agroecosystems, 26, 1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlbarr\u0026aacute;n-Portillo, B., Rebollar-Rebollar, S., Garc\u0026iacute;a-Mart\u0026iacute;nez, A., Flores-Najera, G., Garc\u0026iacute;a-V\u0026aacute;zquez, Z., 2015. 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Beef Cow-calf Management Practices in the United States. Beef 2007-08. In: Animal and Plant Health Inspection Service. U.S. Department of Agriculture. 2008. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aphis.usda.gov/aphis/ourfocus/animalhealth/monitoring-and-surveillance/nahms/nahms_beef_cowcalf_studies\u003c/span\u003e\u003cspan address=\"https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/monitoring-and-surveillance/nahms/nahms_beef_cowcalf_studies\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on 2008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVSN International. 2022. Genstat for Windows 22nd Edition. VSN International, Hemel Hempstead, UK.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cattle farming, manual milking, oxytocin, market integration, technology appropriation","lastPublishedDoi":"10.21203/rs.3.rs-2945183/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2945183/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aimed to characterise management practices of dual-purpose (DP) cattle production systems across Mexico through a structured questionnaire answered by 996 farmers. The predominant type of cattle found in DP operations was European dairy x Zebu crossbreeds (54.7%). These cattle were most popular in the tropics with 78% and 56% for the humid and dry tropics, respectively. In contrast, temperate climate farmers prefer European beef x Zebu crossbreeds (63.1%). Weaned calves and dairy products were the primary goods of DP systems. More operations sell raw milk in temperate climates than in arid and tropical climates. Ninety one percent of DP farms milk their cows manually, whilst only 8.6% use mechanical milking. Cows are milked once daily in 93% of farms. The main calf-rearing system is by allowing the calf to suckle (95.1%), with only 4.9% of operations using artificial rearing methods. Milk letdown was most frequently induced by the calf (73.2%), but 13.9% of operations used oxytocin stimulation. Only 6.3% of operations have milk cooling systems. Regarding sanitary practices, 73.5% of farms reported cleaning the teats prior to milking. Teat dipping after milking was generally low (10.5%), owing to the calf feeding on remanent milk. In addition, only 18% of DP operations routinely use mastitis diagnosis tests. Given the importance of dual purpose for local economies, improvements in market integration, technical assistance, and technology appropriation are paramount for the future development of this sector.\u003c/p\u003e","manuscriptTitle":"Cow-calf management practices in Mexico: dual-purpose cattle","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-19 20:40:39","doi":"10.21203/rs.3.rs-2945183/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4dbfe667-6870-4f59-a7e4-de4f921cfa05","owner":[],"postedDate":"September 19th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-20T01:17:37+00:00","versionOfRecord":[],"versionCreatedAt":"2023-09-19 20:40:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2945183","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2945183","identity":"rs-2945183","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}