Buy Pig Farming In Thailand
In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets.
buy pig farming in thailand
Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis.
The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.
In Thailand, pig farming systems can be categorized into three groups: i) the farrow-to-finish production system, which includes breeding pigs, producing piglets and fattening pigs in the same farm; ii) the nursery system, which only raises breeding pigs to produce piglets; and iii) the finishing system, which raises weaners until they reach market weight [19, 20]. Nowadays, two groups of pig breeds are used in Thailand: the native breeds such as Raad or Ka Done, Puang, Hailum, Kwai, and wild pigs ([21, 22] and the main commercial breeds, including the Large White, Landrace, Duroc, and crosses of these [20]. Native pig breeds grow slowly and their reproduction rates are lower than those of commercial breeds. However, they are better adapted to hot and humid climates and to low-quality feed [21] and they apparently show higher resistance to endemic diseases such as Foot and Mouth Disease (FMD) and internal parasites [21]. In contrast, commercial pig breeds grow much faster, with comparatively higher feed conversion rates and their carcass and meat quality better meet supermarket needs for standardized products [2].
Previous studies demonstrated that farm-level characteristics (i.e. production systems), could be an important risk factor for different diseases in Thailand [2, 12, 23]. For examples, the movements of pigs between production stages provide significant opportunities for the transmission of diseases between herds or farms. Examples include Transmissible Gastroenteritis (TGE) and PRRS [5]. Purchasing feeder pigs from outside the farm increases the risk of introducing diseases such as PRRS, Classical Swine Fever (CSF), and FMD [2]. Farms with breeding sows are at a higher risk from PRRS [12]. The traditional farrow-to-finish system, with high levels of mixing between age groups, facilitates the exchange of a wide number of potential pathogens within the farm, especially enteric and respiratory diseases [23]. In terms of environmental impacts, the Thailand Pollution Control Department (PCD) reported that the high concentration of pig farms in the central plain caused significant water pollution in rivers, and consequently, PCD added pig farming to the list of regulated activities in 2001 [2, 24].
Over the last few years, the DLD has been undertaking regular, detailed livestock censuses throughout Thailand, thanks to a very large network of volunteers coordinated by regional, provincial, and district veterinary officers. This study aimed to analyze these very detailed census data on pig distributions in Thailand with two objectives. First, we aimed to describe the geographical patterns and trends in pig farming in Thailand in terms of pig breeds, farming systems, and farm scales. Second, we aimed to analyse the spatial distribution of these different systems in relation to spatial factors that may influence their distribution.
Decision rules identifying pig farming systems. Left side shows the proposed classification of the smallholders and large-scale farming systems according to the pig numbers, with holders raising less than 50 pigs being considered as smallholders (5000 pigs per holder for large). Right side shows a proposed classification of farming system according to pig types, with i) farrow-to-finish system if the holder includes all types of breeding pig (boar, sow, and piglet) as well as fattening pigs, ii) nursery system, if the holder includes all types of breeding pig (but no fatting pigs), and ii) finishing system if holder includes only fattening pigs
Smallholders and large-scale farming systems were separated based on the number of pigs per holder, with holders raising less than 50 pigs being considered as smallholders (5000 pigs per holder for large) (the categories shown in Table 1). We previously indicated that farm size is strongly linked to extensive and intensive system. Here, we use the number of 50 pigs per holder with
Detailed data on pig populations by pig types, farming systems and farm scales for 2010 are presented in Table 3. There were 8.3 million head of pigs throughout the country with 5.2 million fattening pigs (62 %), 2.5 million breeding pigs (30 %) and 0.68 million native pigs (8 %). The median number of pigs per holder was five, but when broken down by pig type it was three pigs per holder for native pigs, four pigs per holder for breeding pigs, and eight pigs per holder for fattening pigs. The breakdown of commercial farms was 78 % belonging to the finishing systems, 14 % to nursery systems and 8 % to the farrow-to-finish systems. However, the number of pigs per holder of the farrow-to-finish systems (556) was much higher than that of the nursery systems and of the finishing systems with 96, and 88 pigs per holder, respectively.
The association between the fitted functions and the predictor variables modelled by the quantitative RF model are shown in Fig. 5. The plots show that three variables, including rainfed croplands, irrigated croplands, and human population density shown a similar positive association with the predicted values for all pig farming types (Fig. 5d to f). In contrast, for two predictor variables, the travel time to the capital city and the travel time to the provincial capitals, different relationships were found according to the type of pig farming (Fig. 5a to b). Breeding pigs and fattening pigs showed a negative association with those predictors, whereas native pigs showed an inverse positive association. The same contrasting pattern with these predictors was found for the farm scale categories, where large-scale production systems showed a negative association with travel time to the capital city and travel time to the provincial capitals, whereas smallholders showed a positive association. Regarding elevation (Fig. 5c), fattening pigs and large-scale production systems showed correlation with low elevation, while smallholders, native pigs, and breeding pigs showed both a negative and positive association. In the binomial presence/absence model, such inverse associations were not apparent ((Additional file 1: Figure S2), as there was much more similarity between the presence/absence distributions of the different categories (e.g. probability of absence was predicted to be positively associated with elevation in all categories).
Most of the pig farming systems in Thailand belonged to the finishing systems (78 %) followed by the nursery systems (14 %) and the farrow-to-finish systems (8 %). The average number of pigs per holder in the farrow-to-finish systems (556) was much higher than that of the nursery systems (96) and the finishing systems (88). The farrow-to-finish systems handle all pig production stages. Consequently, they need to have a high level of specialization and a long experience in using modern technologies to increase productivity [41]. They control the entire production chain by adjusting both the number and quality of pigs raised and fattened [2]. In contrast, owners of the finishing systems need to purchase feeder pigs from external sources, which is a more risky strategy; exposing them to fluctuations in supply, unreliable genetic background, and to poor overall quality and health of the animals [2].
Detailed census data and spatial modeling has enabled the geographical and functional characterization of pig farming systems in Thailand. They highlight a process of intensification of the production, with increasing numbers of pigs per owner over time, large-scale pigs farms concentrated around the capital city to supply its demand, with a tendency of being located increasingly far from the center. Their distribution mostly corresponds to that of breeding and fattening pigs of improved breeds. In contrast, smaller-scale producers are distributed in more rural regions, and more strongly concentrated around local province capitals. These historical developments have not resulted from any specific planning in the past, and have resulted in a present distribution that may not be optimal in terms of environment and health impacts, for example. As the sector is still expanding, future developments may benefit from spatially-informed planning accounting for the specific health, environment and economical implications of the different pig production systems recognizing their specificities. This could be achieved, for example, through the promotion of sustainable intensification of small-scale producers to limit their potential local environmental impact, and by the implementation of AWI for the most intensive production sector in geographically limited parts of the country. Defining these areas geographically could be the scope of follow-up works using multiple-criteria decision analysis tools such as to incorporating environment, heath and economic spatial criteria in the decision-making. 041b061a72