Livestock Research for Rural Development 31 (8) 2019 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
Mechanization in the dairy sector is an essential factor for sustaining production in which the production system tends to become a commodity-driven agribusiness. The dairy farming sector in Indonesia is still dominated by small farmer where labor-substitution technology has not been considered to develop their farming. These studies aimed to measure the impact of mechanization on herd size increase of smallholder dairy farming as well as farm labor efficiency. A survey was taken place in two dairy primary cooperatives in West Java. The data were collected from 111 dairy farmer who keep at least five dairy cows which chosen randomly. Selected farms are grouped into several categories based on mechanization adopted to decrypt differences in cattle herd size for each category. Causality between mechanization category and dairy cattle herd size is modeled by multiple regression. The Dummy variable is applied to measure the impact of herd size increase caused by certain machinery categories used. The results show that the use of farm machinery for milking cows and processing forages, each causes a significant impact on herd size increase. Moreover, the larger herd size is related to the skills of farmers in operating a couple of machines to handle various farm activities. Mechanization lead to increases the number of dairy cows with small increases in farm labor. This labor-saving practical is required by this sector, especially in helping small dairy farmers who try to increase their farming size, while labor costs recently tend to be more expensive.z
Keywords: dairy cooperatives, farm machinery, labor demand
Dairy farming in Indonesia mostly found in Java, a dense island with a population of more than 140 million people (BPS-Statistics Indonesia 2018). They develop in the suburban agricultural region, it accords to the Von Thunen agricultural spatial model, where the commercial farm producing fresh milk, vegetables, and fruits would take place at the first circle zone near the city (Parr 2015). However, in recent decades, many dairy villages develop influenced by regional market growth. The local resources becoming scarce due to the competition in demand among various sector in the economic activities.
The smallholder dairy farming is the most vulnerable group in facing such situation, they are difficult for sustaining or scaling up their herd size due to limited farm resources (Khapayi and Celliers 2016). They are in cooperation with other farmers in dairy cooperatives. Through collective action, they hoped it will help and sustaining their business. The various study reported that collective action has long been a central mechanism for improving market access and productivity of smallholder producers. The advantages are known to be improved bargaining power, more professional management, linked access to larger volume end markets and access to higher quality and more reliable inputs and services, including dairy business services (Ahuja and Staal 2013).
To support the on-farm sector to sustain and increase milk production, the cooperative provides farm input and technical services. It is important for achieving and strengthening the sustainability of the dairy value chain (Vanishree at al 2018). However, to gain a significant increase in producing milk, the farmer requires increment productive cows, skilled farm labor as well as the appropriate farm machinery. As the economy developed, labor demand and wage rate increases, the smallholder dairy farming that traditionally employs labor-intensive farm production system will be costly (Otsuka et al 2012). There is needed a viable technology at a minimum scale that allows smallholders to survive and increase their herd size without using more labor (Poapongsakorn 2013). Without an improvement of on-farm dairy production, the sector would difficult to grow and contribute to solving the domestic milk supply issues, while the small dairy farming is still being the backbone of domestic milk production.
In countries where the dairy industry has advanced, the farming sector benefited from the emergence of agricultural mechanization, the machinery equipment help producer control many processes to reduce waste and increase cattle-labor ratio (Schmitz and Moss 2015). Contrary to smallholder dairy farming, farmer mostly uses the labor of his own self or available family labor with limited skilled. The small farmer is common to a traditional practice such as cows milked and forages harvested by hand, it causes they have only a few cows (Cheeke 2004). Maintaining such practices could not support farmer to enlarge their farm size and cause the labor-cattle ratio relatively high.
The dairy production system in developing countries tends to become industrial livestock farming (Van der Zijpp at al 2010). Small dairy farmers will be part of the industrial system that will continue to change, they must operate their farm in economies of scale, increasing milk quality they produced as well as getting benefit from their farming. Good practicing of dairy production has become a necessity for the dairy farm sector. Introducing agricultural machinery is required to assist the farmer work more effective. For the long run purpose, it is needed to scale up their farming, reducing labor cost as well as increasing farm income (Hadiana et al 2017).
Many kinds of agricultural machinery and equipment are promoted and offered to the local market. Farmer to farmer extension program initiated by cooperative and accessible information nowadays helps the farmer easily to get new machinery tools. However, many constraints faced by the small farmer caused their response slightly. They argue that machinery equipment requires trained labor, maintenance, and as a physical good, a machine is going to depreciate with or without be used, their performance and value gradually will decrease (Houmy et al 2013).
The dairy farm machinery intended in this study is a category or type of machined equipment appropriate for a small farmer, such as portable machinery for milking cows, small forage chopper machine as well as the motorized carriage or a pickup car for goods delivery (forage, concentrate feed, milk, etc.).
Data was gathered from 111 smallholder dairy farmer those who hold at least five dairy cows. This farmer group is categorized as the potential adapter for innovation. The farmers who own five cows or greater are assumed they concern to farm machinery for better farming practices, and they have viable income that could be allocated for equipping their farm with proper machinery tools. The survey was conducted in two dairy cooperatives service area in the district of Bandung and West Bandung, both are known as the largest dairy cooperatives in West Java.
Multiple regressions were used to describe causality relation between dairy herd size and several explanatory variables that consist of farm resources (occupied land acreage and labor) and farm machinery. MWDs test of linearity results accepted of H0: Z=0, it leads to a decision that the regression model is linear instead of log-linear (Gujarati and Porter 2009). Dichotomous or binary scale was applied for categorizing farmer related to kind of the machinery adopted.
To construct the regression model of mechanization impact, the selected farmer was grouped into five categories. The first is the farmers who do not use any farm machinery, named as a basic category. The other four groups are those uses farm machinery, they are consist of the category of the farmer those uses milking machine (D1), those who have motorized carriage (D2), those who uses forage chopper machine (D3), and the interaction of the three categories, that is the farmers who operate the three kinds of machinery on their farm (D4). The machinery adoption by the farmer was modeled as a technological factor that impacts the farmer capacity to keep more dairy cows. In the qualitative regression model, the technological impact is explained the by dummy coefficient.
Analysis of variance (ANOVA) and analysis of covariance (ANCOVA), both were used to analyze the survey data. At the first analysis, the regressor contains qualitative or dummy variables only (mechanization categories), while at the second, both dummy and quantitative variables (labor and land) are included into the same equation (Gujarati and Porter 2009).
The two modelss are as follows:
Yi = α10 + α11D1i + α12D2i + α13D3i + α14D4i + μ1i
Yi = α20 + α21D1i + α22D2i + α23D3i + α24D4i + β21X1i + β 22X2i + μ2i
Where Y = dairy herd size (number of cow);X1 = farm labor (man worker);X2 = land acreage (1000 m2). The dummy variable uses nominal or dichotomous scale, denoted by either 1 (one) or 0 (zero). Dj=1, if the farmer uses the concerned machine and Dj=0 if others, and μ = stochastic disturbance.
Estimation of the regression model results in the coefficient ofα1j, α2j for j= 1,2,3,4 mechanization category, and the coefficient of βk for X variables. All the dummy coefficients were hypothesized have positive sign. It represents that introducing farm machinery is helpful for the farmer increasing the number of cows. Furthermore, the dummy coefficients were used to predict the measures of average increment of herd size or number of cows.
The farmer equipped their farm in various machinery types and category, depend on their priority related to farmer planning, farm resources availability, workload, farmer skill and experience in using machinery equipment as well as their perception regarding mechanization. Farmers require vehicle facilities for delivering fresh milk they produced, cattle feed, forages, and other farming activities. Most farmer use motorbike for carrying a small load in a short route. The bike is not used to facilitate their farm activities only, but it is also used for family transportation purposes. Motorbike is preferred because it can be used for multipurpose transportation, convenient for rural infrastructure condition, low fuel consumption, acceptable price, and other benefits, even many farmers recorded has more than one motorbike.
Most small farmers get free forages carried from communal land or forestry area, therefore they prefer to use more forage to reduce costs of production. Motorized carriage or pick up car is the effective transportation tools for carrying forage from the away sources; some farmers also uses motorbike to carry a smaller load or a couple sack of forage. Chopper machine is used to cut forage or grass before being fed to cattle, and the remains is fermented and stored as silage. Shorter chop forage tends to compact the mass in storage and improve the digestion rate by rumen bacteria and intestine enzyme (Mahanna 2013).
Table 1. Number of Smallholder Farm Using Equipment Machinery |
|||
No. |
Category of machinery |
Farmer |
Percentage* |
1 |
Milking machine |
29 |
26.1 |
2 |
Motorized carriage |
37 |
33.3 |
3 |
Forage chopper machine |
15 |
13.5 |
4 |
Motorbike |
87 |
78.4 |
5 |
Generator Set |
3 |
2.7 |
* The sample size, including the sample farmer which does
not have |
The percentage of smallholder dairy farmer who uses machines is shown in the Table-1. The number of machineries used above, especially on the use of milking machines and grass chopper machine, has not represented the degree of mechanization of entirely smallholder dairy farmers. In this study, the observed farmers are those who have a relatively large amount of cattle and produce more milk, so they are considered economically eligible to adopt the machine equipment. However, those who use milking machines are only a quarter of potential farmers. This adoption rate is low compared to their farm income. To own a unit portable milking machine, for example, it could be obtained for an average of IDR (Indonesian Rupiah) 20 million, equivalent to the price of a pregnant heifer.
Milking machines have been introduced to farmers since the last decade. It was started when the cooperatives initiating to organize training program for better milking technique addressed to the selected farmer, the cooperative established a partnership with milk equipment suppliers. The farmer reason decides to adopt mechanization, frequently are related to farm labor issue. As much 34.5% of respondent says that he intended to replace manual milking in order to save time and labor as well; 20.7% purpose to increase dairy herd size, 17% faced farm labor scarcity, hence they use the machine to replace milking cows by hand, and 10.2% related to the decrease of the farmers’ workload due to age factor.
There is a relationship between the level of agricultural production and the access to important inputs, including machinery tools (Sims and Kienzle 2017). Introducing of machine milking instead of hand milking can improve the hygiene equality of milk and increased the work efficiency on small farm (Filipovic and Kokaj 2009).However, the achievement of the adoption rate is still below expectations due to several factors such as the lack of dairy farming practices to better production, poor of farm management skills, as well as low education levels (Khapayi M and Celliers 2016).
The survey data is decrypted to figure out the herd size increase related to mechanization categories (figure 1). Farmers who adopt mechanization were categorized based on the number or kind of machines they used. There is a tend the number of dairy cows increased with the increasing of mechanization based on the number of farm activities mechanized. Farmers those who categorized having the largest number of dairy cattle use two or more machines to handle their farm activities. Contrary, without mechanization farmers maintain a few dairy cattle, they keep on average 7.63 cows.
Figure 1. Average dairy herd size of smallholder dairy farming in various mechanization category |
Estimating the regression coefficients using the ordinary least square resulted in coefficients as shown in Table 2. For the purposes of statistical analysis, the specified regression model did not include groups of farmers who using two categories machinery due to the emergence of multi colinearity between independent variables. The two results of the regression analysis, each of which is the analysis of variance (ANOVA) and covariance (ANCOVA), both presented in Table 2. The statistic F analysis resulted in that the regression model effect herd size (p<0.01 ). The proportion of the variation of the dependent variable (herd size) caused by each regression model or the coefficient of determination (R 2) of the first model is 0.51, and the second model is 0.57.
All of the estimated coefficients indicate the positive impact of the explanatory variable partially. The first model shows that farm machinery, either milking machine, motorized carriage or forage chopper machine, each lead to a larger in dairy cow number (p<0.05). In the second model, where agriculture land and farm labor were added as the explanatory variable, shows that farm labor leads to an increase in herd size (p<0.05), meanwhile land acreage does not affect. Land is needed by dairy farmers for forage stock. However, land is a very limited resource in many dairy areas. For recent decades, regional growth has led to the demand for scarce resources to grow rapidly, especially land, therefore most dairy farmer treat forage as an external farms input that can be purchased from feed suppliers or they themselves cut forages and carrying it from nearby forests.
Table 2. Regression Coefficient of Mechanization Impact |
||||||||
Model variables |
ANOVA |
ANCOVA |
||||||
coef. |
t-ratio |
p |
coef. |
t-ratio |
p |
|||
Constant |
αi0 |
7.56 |
12.80 |
<0.001 |
4.25 |
4.11 |
<0.001 |
|
Land |
β21 |
- |
- |
- |
0.11 |
1.37 |
0.172 |
|
Labor |
β22 |
- |
- |
- |
1.38 |
3.18 |
0.002 |
|
Machinery category: |
||||||||
D1_milking |
αi1 |
3.04 |
2.51 |
0.014 |
3.28 |
2.76 |
0.007 |
|
D2_carrying |
αi2 |
2.15 |
2.03 |
0.045 |
1.45 |
1.44 |
0.153 |
|
D3_forage chopping |
αi3 |
6.02 |
2.69 |
0.008 |
4.56 |
2.12 |
0.037 |
|
D4_interaction |
αi4 |
5.57 |
1.96 |
0.052 |
5.54 |
2.01 |
0.041 |
|
Since dairy cows were introduced to small farmers through the Indonesian government's milk policy in the 1980s, the dairy cooperative was encouraged to develop a milk marketing partnership with the milk processing industry. As a consequence, farmers must be part of an industrial system that strictly pays attention to good production systems, control of milk quality and the timeliness of the milk distribution chain. It is important for cooperatives to have an agenda to improve farmers skills in good dairy farming practices as well as their productivity, it could bring up the farmer from the backyard tradition to more commercial operations (Poapongsakorn 2013).
Applying the good dairy practicing and mechanization of the farming, both also must be an essential factor for developing the dairy sector to grow faster. Nowadays there are many options of innovations that cover all level of farming technology and many kinds of dairy farm equipment, from simple tools to complicated and motorized equipment (FAO 2016).
Figure 2. Dairy herd size increase and farm labor demand in various mechanization category |
Labor productivity is directly related to mechanization. The increase of herd size due to farming mechanization causes labor-cattle ratio decreased (Figure 2). The average number of dairy cows increases from 7.6 head at the basic category up to 24.3 head. Meanwhile, the farm labor demand varies in a small change from on average 1.80 up to 3.45 workers per farm. Mechanization makes some farm duties become effortless. The small farmer who intends to enlarge their farming enables to increase their cow's number doubling without an addition of hired labor. They argued instead of adding new hired labor, it’s more benefit to equip and train the available farm labor. Milking cows by using a machine instead of hand milking increased work efficiency on small farm (Filipovic and Kokaj 2009), improve milk quality and safety (Reinemann 2008). Studies in other agriculture sector (Verma 2005) shows that farm mechanization led to an increase in inputs and increase the productivity of farm labor.
Farmers spend many funds in the early years of the machinery adoption process with a hope they gain benefits in the future. Small farmers who put out his money to own farm machinery usually find that investment in mechanization technology is too expensive for themselves (Sims and Kienzle 2017). They spend IDR 11 to 20 million for the portable milking machines. While if they buy other kinds of farm machinery, the farmer invests funds of IDR 41 to 120 million, it is varied depending on the number of machine unit, kinds, performance, and its price.
Figure 3. The yearly cost structure of the mechanized and non-mechanized farming |
Mechanization causes farmers use larger inputs and higher cost of production (Verma 2005) especially during the early months of using a new machine. Despite mechanization lead to a rise in the number of the dairy cow and milk production, however, there is no difference in the incremental farm income between the farmers who mechanized and did not mechanized their farming. By mechanization, the farmer looks for achieving larger and better harvest, increasing income and job for the farmer (FAO 2016). However, the high cost of investment in procuring machinery leads to farmers' budgeting problems which can make small farmers reluctant to mechanize their farming.
The above results illustrate that in the early stage of mechanization the farmer has not benefited compared with those who not use farm machinery, meanwhile, the incentive in farmer income is required for the innovation adoption process, particularly for the farmer that is demanded to be more competitive commercially. The dairy farmer who produce raw milk, includes the smallholder farmers, no exception, have being a part of local dairy industrial system. However, the small-scale farms face many constraints of resources if they have to develop mechanization by their own self. Small-scale farmers commonly have limited funds sourced from their own savings, while fixed assets are not available for investment purposes (Saifulla and Miyazako 2013). Developing mechanization in smallholder dairy farmer requires supporting policy, the one is the farm inputs credit which could encourage the selected farmer to mechanize their dairy farming.
The other supporting policy that integrated with mechanization program is also required such as milk price incentives, increasing cow productivity and milk quality improvement through dairy extension services and technical assistance. To build local capacity in development of dairy sector, mechanization program should involve a partnership between manufacturers, researchers and user groups (Sims and Kienzle 2017). In many cases the role of agricultural machinery sellers and the mechanical service provider at the village level are required to help the farmer get the machinery works properly.
The research was funded by ALG Program organized by Directorate of Research, Community Development and Innovation (DRPMI). Padjadjaran University. We are thankful for the support of DRPMI and staffs to facilitate this study.
Ahuja V and Staal S 2013 Poverty, Food security, Livestock and Smallholders: Issues and Options for the Asia and the Pacific Region. In Ahuja V (Ed.) 2013. Asian Livestock: Challenges, Opportunities and the Response. Proceedings of an International Policy Forum held in Bangkok. Thailand. 16-17 August 2012. Animal Production and Health Commission for Asia and the Pacific. ILRI and FAO of the United Nations.
BPS-Statistics Indonesia 2018 Statistical Yearbook of Indonesia. Publication Number: 03220.1811. Catalog: 1101001. Biro Pusat Statistik. Indonesia. https://www.bps.go.id
Cheeke P R 2004 Contemporary Issues in Animal Agriculture. Third Edition. Department of Animal Sciences Oregon State University. Pearson Prentice Hall.
FAO 2016 Sustainable Agriculture Mechanization. Food and Agriculture Organization. United Nations. http://www.fao.org/sustainable-agricultural-mechanization/overview/what-is-sustainable-mechanization/en/
Filipovic D and Kokaj M 2009 The Comparison of Hand and Machine Milking on Small Family Dairy Farms in Central Croatia. Livestock Research for Rural Development. 21 (5).
Gujarati N D and Porter D C 2009 Basic Econometrics 5th Edition. McGraw Hill. New York.
Hadiana M H, Daud A R, Supratman R H and Suryadi D 2017 Optimizing Farm Inputs of Maize Silage Production Integrated with Small Scale Dairy Farming. Proceeding. The 7TH International Seminar on Tropical Animal Production. Indonesia.
Houmy K, Clarke L G, Ashburner J E and Kienzle J 2013 Agricultural Mechanization in Sub-Saharan Africa Guidelines for Preparing a Strategy. Integrated Crop Management. Food and Agriculture Organization. Rome.
Khapayi M and Celliers P 2016 Factors limiting and preventing emerging farmers to progress to commercial agricultural farming in the King William's Town area of the Eastern Cape Province. South Africa. S Afr. J. Agric. Ext. [online] vol.44. n.1. pp.25-41.
Mahanna B 2013 Forage Management Considerations to Improve Animal Productivity and Feed Efficiency. International Dairy Nutrition Symposium. Feed Efficiency in Dairy Cattle.Wageningen. Universiteit Utrecht.
Mini K P 2012 In vitro assessment of anthelmintic effect of Arstolochia species plants against Haemonchus contortus. Ph.D Thesis, Tamil Nadu Veterinary and Animal Sciences Unviersity, Chennai, 51.
Otsuka K, Liuand Y and Yamauchi F 2015 The Future of Small Farms in Asia. In Proceeding of 29th International Conference of Agricultural Economist: Agriculture in an Interconnected World. Milan. Italy.
Parr J B 2015 Overlooked Aspects of the von Thunen System. Spatial Economic Analysis. Vol. 10. No. 4. 471–487. http://dx.doi.org/10.1080/17421772.2015.1076577.
Poapongsakorn N 2013 Livestock Industrialization in Asia: Growth. Scaling Up. Competitiveness and Outlook for Smallholders. In Ahuja V (Ed.) 2013. Asian Livestock: Challenges. opportunities and the response. Proceedings of an International Policy Forum held in Bangkok. Thailand. 16-17 August 2012. Animal Production and Health Commission for Asia and the Pacific. ILRI and FAO of the United Nations.
Reinemann D J 2008 Robotic Milking: Current Situation. NMC Annual Meeting Proceedings. University of Wisconsin. Madison. Wisconsin USA.
Saifulla S and Miyazako M 2013 Promoting Investment in Agriculture for Increase Production and Productivity. In Ahuja V (Ed.) 2013. Asian Livestock: Challenges. opportunities and the response. Proceedings of an International Policy Forum held in Bangkok. Thailand. 16-17 August 2012. Animal Production and Health Commission for Asia and the Pacific. ILRI and FAO of the United Nations.
Schmitz A and Moss C B 2015 Mechanized Agriculture: Machine Adoption. Farm Size. and Labor Displacement. AgBioForum. 18(3):278-296.
Sims B and Kienzle J 2017 Sustainable Agricultural Mechanization for Smallholders: What Is It and How Can We Implement It? Agriculture 7(6). 50; https://doi.org/10.3390/ agriculture7060050.
Van der Zijpp V, Wilke A P and Carsan S 2010 Sustainable Livestock Intensification. In: Swanepoel F. A Stroebel and S Moyo (Ed.). The Role of Livestock in Developing Communities: Enhancing Multifunctionality. The Technical Center for Agricultural and Rural Cooperation (CTA). https://cgspace.cgiar.org/bitstream/handle/10568/3003/role.
Vanishree M, Sendhil R, Smita S, Chauhan A K, Rashmi H M and Ponnusamy K 2018 Role of Dairy Cooperatives in Strengthening Value Chain of Liquid Milk and its Sustainability in Karnataka: Findings from Preliminary Study. Indian Journal of Economics and Development. 14(1a): 410-415.
Verma S 2006 Impact of Agricultural Mechanization on Production. Productivity. Cropping Intensity Income Generation and Employment of Labor. https://www.researchgate.net/ publication/237801065.
Received 19 December 2018; Accepted 19 July 2019; Published 1 August 2019