| Livestock Research for Rural Development 28 (9) 2016 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
Dairy farming is the main economic activity developed in Puno; this situation allows Puno’s dairy basin possess a huge potential in the short and medium term future. Therefore one of the alternatives has been implemented since more than a decade ago by Caritas and regional initiatives consisting in introduction dormant alfalfa W350 a variety adapted for the andes up to 4 200 m.a.s.l., however lack of support and knowledge in the farmers, who don’t calculate their incomes and expenses, no records of any production or to produce quality milk stand avoiding empowerment to enable them to improve their quality life. The following research was conducted in districts of Acora, Atuncolla, Paucarcolla and Mañazo in the province of Puno, Taraco in Huancane, Pucara in Lampa, and Ayaviri in Melgar in order to determine the cost of milk production.
The cost of production of the farmers first was classified in 3 groups according a cluster analysis, the cost determined for the small, medium and large farmer was US$ 0.30, 0.26 and 0.25/l of milk respectively. A second classification determined 2 groups, the efficient with at least 40% of the population in the herd represented by lactating cows with US$ 0.26/l of milk and the less efficient with US$ 0.31/l of milk. This study concludes that the cost of milk production in Puno where dormant alfalfa it’s used as a pasture forage is less in comparison with the intensive system as the one calculated by AGALEP (2007) US$ 0.52/l of milk or the Gobierno Regional de Arequipa (2009) US$ 0.47/l of milk.
Keywords: dairy cattle, farmers, forage, highlands, milk cost of production
According to the IV National Agricultural Census (CENAGRO 2012), the highlands have 73.20% of cattle population of the country. Peru has 881 920 agricultural units that breed cattle and Puno 128 646 agricultural units engaged in cattle breeding, of whom 51.88% produce milk.
There are initiatives to support management of grazing forages led to the cultivation of dormant alfalfa, a variety that can survive the drought period and recover for the next rainy season; this alfalfa can last from 15 to 20 years (AGROBANCO 2012). In addition to being considered as a successful example of technological upgrading in highlands region (Tapia 2013).
According to Cunliffe (2008) each dairy producer will have a different position regarding make decisions on your herd depending on costs and the milk yield from their cows. The cost of production and the breakeven point are required for better management by the farmer.
Therefore, this study aims to characterize the productive system of dairy livestock in Puno using as main feed dormant alfalfa W350 ( Medicago sativa L.), the cost of production and evaluate its breakeven point in the provinces of Puno, Lampa, Huancane and Ayaviri.
In 2008, the supply chain of milk in Peru market was made up 70.60% from local market and the remaining 29.40% from importation. (Ministerio de Agricultura y Gobierno Regional de Puno, 2008). Until October 2014 was predicted that the annual importation will reach 32.00%, leaving the national production in 68.00%. The current situation has allowed an increase in imported milk and facing this; Peru dairy farmers have managed milk production and reached a slight recovery in 2014 with an average growth of 1.9% (2015 AGALEP).
Dairy cattle in Puno is the livelihood of 66 739 agricultural units, besides the predominant activity in the region (CENAGRO 2012). Preliminary studies have shown in ten years (1997 to 2007) dairy production has doubled and there are 4 times more homes that sell milk, something similar happened with the dairy herds, with more genetically improved animals as they went from 6.4 to 10.4 l by farmer. (Kristjanson et al 2007).
The livestock sub-sector in Puno forms part of one of the most important economic activities, mainly emphasizing milk production with an annual average growth of 9.3% during the last decade (INEI 2014), this development is supported by an increased demand for dairy products by consumers of Puno and other regions (InfoLactea 2015). Table 1 shows the growth of milk production and puts Puno as the second dairy basin for the south and the fifth one nationally (Fernandez 2013).
Latest information reported an annual production 95 400 t of raw milk in 2014 with 98 700 milking cows (MINAGRI 2015).
|
Table 1. Milk production dairy cattle in Puno (t) and annual variation |
||
|
Year |
Production of milk (t) |
Annual variation (%) |
|
2004 |
43 242 |
18.25 |
|
2005 |
49 453 |
14.36 |
|
2006 |
62 011 |
25.39 |
|
2007 |
66 065 |
6.54 |
|
2008 |
67 951 |
2.85 |
|
2009 |
71 047 |
4.56 |
|
2010 |
76 907 |
8.25 |
|
2011 |
79 038 |
2.77 |
|
2012 |
83 285 |
8.60 |
|
2013 |
91 287 |
6.36 |
|
2014 |
95 416 |
4.52 |
|
Source: INEI 2014 |
||
Puno has 607 256 heads of dairy and Criollo cattle, of which the population of cows is equivalent to 46.40%, heifers is represented by 15.20%, calves by 22.30%, steers by 7.30%, and bulls 8.70% (CENAGRO 2012).
The population of milking cows in Puno during 2014 was 98 741 showing an annual average increase in its population in 15.8% (MINAGRI 2015).
In the region, among the common feedstuff for animal production are rangeland and cultivated pastures, the first with a large extension, but has been reduced and partially replaced by other species, reaching 3 501 506 has (CENAGRO 2012).
Dormant alfalfa has 80 000 ha (Torres 2016). There is a growing rate for forages either for cutting or grassing in Puno because milk production represents a profitable opportunity to famers (BCRP Puno 2013).
Dormancy is the period during there is no forage production as a result of their genetic characteristic and the combination of cold and short days. Thus dormancy is classified from 1 to 11 (to higher value, less dormancy) (AGROBIT 2016). W350 alfalfa has a dormancy of 3.8, feature that allows it to withstand extreme events such as drought and frost. This variety of alfalfa through its dormancy remains in the ground where it was seeded even against unfavorable conditions (from June to October) begins resting, for later sprout in the rainy season. It develops with outstanding value of biomass production between the 2 600 to 4 200 m.a.s.l. either alone or in association with legumes or grass, and can be grown under rain. The yield in the rainy season is 100 tons of green forage/ha/year its sinclusion in the Criollo cattle feeding program has shown increases in milk production up to 3 l, as well as longer milking campaigns with 70 more days (Silva 2015).
This research is part of a field exploratory and descriptive work, seeks to identify and characterize the main components of the cost of production of dairy farmers in Puno using dormant alfalfa in their systems.
This study was carried out in the department of Puno, in Atuncolla, Mañazo Paucarcolla districts in the province of Puno, Huancane in Taraco, Pucara in Lampa and Ayaviri, Melgar. This can be seen with more detail in the figure 1. The time of the data collection was conducted lasted 15 days in July 2013, corresponding to the dry season.
A minimum of 2 farmers have been identified by each district that met the following requirements:
- Produce raw milk for sale.
- Use as a main source of forage dormant alfalfa.
Finally, the sample size worked was 24 dairy farmers distributed in 7 districts.
|
| Source: INEI 2007 cited by MINAM 2014 |
| Figure 1. Map showing distribution of surveyed farmers |
The research used a semi-structured survey through interviews. The interview consisted of 90 questions between closed and open ones.
The statistical analysis used multivariate statistical techniques. The selection of quantitative variables were carried out through a principal components analysis for a smaller number of variables explaining an acceptable proportion of the overall variance.
The Clusters analysis and the main components correspond to a method of great interest in sociology in the perspective that is called dense descriptions (Fernandez 1991).
For the definition of groups, it was performed a Hierarchical Cluster Analysis using as distance measurement the squared Euclidean method and as group technique the linkage between groups method. The software used was SPSS 22.
The analyzed variables studied are number of cattle, cows, lactating cows, average herd/day production and average cow/day production.
In one of the classifications carried out in this study two groups were obtained, the first one formed by efficient farmers and the second by less efficient farmers. Both groups were identified by considering the technical index and population development (Almeyda 2011), which is used for the stabilized population under an intensive dairy system, but is useful as a benchmark for the puneño predominantly grazing management system.
In order to determine the cost of production, the first task was to consider the main costs made by dairy farmers, the expenses for their cow to produce milk. So the study started with forage production cost and cultivated pastures, for the cost of feed; cost of reproduction depending on the number of inseminations; health from health care costs; cost of livestock management; labor cost; depreciation of infrastructure; and cost of fuel, depreciation of equipment and machinery. Administrative costs were discarded because it comes mostly from small to medium size dairy farmers; the cost components can be seen in table 2.
95.83% of the evaluated sample handles cattle under the semi-intensive system, either continuously (dry and rainy season) or alternate, which involves hours of grazing during the day and concentrates supplemented or other forages during the morning or afternoon, so it was necessary to estimate consumption of feed based on dry matter intake, and for cattle from the highlands was considered a value of 12.00 Kg of dry matter (DM) for a lactating cow; 8.00 kg of DM for a dry cow, 7.00 to 7.50 Kg for a heifer and 6.50 to 7.00 Kg for a steer.
The population of male animals was eliminated from the beginning, with the exception of farmers that used natural mating as reproductive system in their herds. There aren´t include the income from sale of male calves or the sale of culling cows or heifers.
Labor cost calculation was totalizing the hours dedicated to management of livestock in tasks such as grazing, milking, feeding with concentrates or hay by the members of the family during the dry and rainy; led to the amount of a working day of 8 hours.
|
Table 2. Components of the cost of production |
|
|
Cost |
Component of the cost |
|
Fixed costs |
Labor cost |
|
Depreciation of infrastructure |
|
|
Depreciation, maintenance and fuel for machinery and equipment |
|
|
Variable costs |
Feedstuff cost |
|
Reproduction cost |
|
|
Health cost |
|
|
Cost of livestock management |
|
The breakeven point seeks to determine the volume of sales (at different prices) so the manufacturer or dealer covers their costs or achieve the balance between income and expenses, its analysis is very helpful because it allows establishing prices and estimate potential gains and losses. (Buzel et al 1979, cited by Ramos 2012)
It can be defined as that point or moment of a livestock company in which certain volume of sales covers all the production expenses (Romero 2000).
Estimation of breakeven point (Almeyda 2010).
 |
Where:
BP: Breakeven point
TFC: Total fixed cost
TVC: Total variable cost
TSV: Total sales volume
Groups observed in table 3 correspond to 3 clusters obtained in the analysis of hierarchical conglomerate. These groups present significant differences among them, divided according to their productive size; the first group distributed in 7 districts: Acora, Taraco, Pucara, Atuncolla, Paucarcolla, Mañazo and Ayaviri represented 4 provinces, concentrated 66,67% of the sample; the second group, distributed in 4 districts, Mañazo, Atuncolla, Ayaviri and Taraco representing 3 provinces with 20.83% of the sample size and the third group distributed in 2 districts, Ayaviri and Pucara representing 2 provinces and 12.50% of the sample.
In relationship with the number of animals, table 3 shows that the average number of cattle is 23 and 15 cows per farmer, lower values than the ones obtained by Gomez et al (2003) in the Central Highlands (Pachacayo), being the average number of cattle per production unit 36 and number of cows 23. However Gamboa (2012) identified two groups, small dairy farmers with 6 dairy cattle and 4 cows; and large dairy farmer with 33 dairy cattle and 14 cows in Jauja during dry season.
In terms of levels of milk production Gomez et al (2003) recorded cow/day milk production ranging from 7.6 to 10.0 kg during the dry season and 6.3 to 6.5 kg for the rainy season in rye grass/clover system. While Gamboa (2012) during the dry season identified a small dairy farmer with 9.63 l cow/day and a big one with 18.00 l under systems that use concentrates and forages as maize, agricultural by-products or crop residues in the district of Jauja. In Puno the average cow/day production values from the small, medium and large farmers are 7.98, 9.87 and 10.20 l respectively.
|
Table 3. Classification of variables to characterize dairy farmers |
||||||
|
Variable |
Unit |
Small |
Medium |
Large |
SEM |
Prob |
|
Average cost |
US$/ l milk |
0.30 |
0.26 |
0.25 |
0.06 |
0.02 |
|
N° dairy cattle dry season |
Unit |
12 |
38 |
58 |
21.8 |
0.001 |
|
N° dairy cattle rainy season |
Unit |
11 |
40 |
60 |
22.5 |
0.001 |
|
N° cows dry season |
Unit |
7 |
25 |
36 |
14.1 |
0.001 |
|
N° cows rainy season |
Unit |
8 |
26 |
36 |
14.0 |
0.001 |
|
N° lactating cows in dry season |
Unit |
4 |
11 |
28 |
9.22 |
0.001 |
|
N° lactating cows in rainy season |
Unit |
5 |
15 |
28 |
9.54 |
0.001 |
|
Total production in dry season |
l/day |
27.2 |
83.0 |
240 |
75.0 |
0.001 |
|
Total production in rainy season |
l/day |
39.9 |
154 |
300 |
94.7 |
0.001 |
|
Total average production |
l/day |
33.5 |
119 |
270 |
84.0 |
0.001 |
|
Average production cow/day |
l/cow/day |
7.98 |
9.87 |
10.20 |
3.04 |
0.32 |
|
Source: Own elaboration |
||||||
The average percentage of given feed cost is 39.32%, which comes from the general cost of production by component once calculated. Similarly the average feed cost for the small, medium and large farmers represent 34.37, 37.22 and 52.46% respectively. Farmers that use concentrate have a fairly representative feed cost with 44.35%, while those who do not supplement with any concentrate reach up 34.30%, far enough considering that they also feed their cows with rangelands.
However farmers well prepared, the ones who did conservation of forages either with hay (alfalfa, oat, barley) or silage (oat) can for sure reduce costs in small, medium or large scale dairy units. Conservation of forages are and will be a key factor for food security and good quality of fodder for dairy cows in highlands. Table 4 shows major crops used and its percentage of use by farmers.
|
Table 4. Use of feedstuff supplies for dairy cattle in Puno |
|
|
Forages |
Percentage of use, % |
|
Dormant alfalfa |
100 |
|
Forage oats (fresh-cut or hay) |
100 |
|
Barley grass (fresh-cut or hay) |
37.5 |
|
Rangeland (grazing) |
75.0 |
|
Concentrate (dry or rainy season) |
50.0 |
|
No concentrate (dry or rainy season) |
50.0 |
|
Alfalfa hay (dry season) |
62.5 |
|
Oat silage (dry season) |
33.3 |
|
Source: Own elaboration |
|
Concentrate use can represent an alternative if it’s produce nearby, but most of these grains are brought from different regions. Local grains can fill the cow’s requeriments and represent an important alternative, depending on the rain season and water availability for medium and small farmers in Puno.
In Vermont, United States only one fourth the amount of hay that was produced in 1950 is harvested now, on the other hand on 2009 more corn was harvested than in the 50’s which represent a potential threat for the soil, due to more production of annual crops represent more erosion and a heavily application of fertilizers (USDA, 2009 cited by Krieg, 2014).
62.5% of dairy farmers use family labor and the 37.5% remaining features different from the familiar local labor.
Within this system of livestock management that grazes in alfalfa, natural grass and cultivated pastures, it is reasonable that feedstuff cost is less than labor cost, since the price of rangeland was based on an estimation that gives it a value of US$ 0.04 per kg, reducing the feedstuff cost.
Sobczyński et al. (2015) state, production cost keep close relationship with family labor and technical infrastructure of the region.
Reproduction management has allowed a genetic improvement considering the programs supported by local and regional funding. This research has identified 29.17% of farmers use artificial insemination (AI) and local genetic improved bulls, 58.33% use only AI, and 12.50% continues with natural mating using regular bulls and not the ones with better genetics.
Related with reproduction the average milk production per champaign in Puno has been 966 kg in 2014 (INEI, 2014). Nevertheless the average production according the farmers interviewed is 1 634 l considering longer milk champaigns due to the use of this legume.
The average cost of production was US$ 0.29/l of milk, being US$ 0.32 in the dry season and US$ 0.25 in the rainy season. A similar value was identified in a paper presented by Gomez et al (2003), with US$ 0.29 at Pachacayo. However, higher values were found, as identified by MINAG (2004), US$ 0.36/l of milk in Arequipa, by AGALEP (2007), US$ 0.52/l in Lima, Gobierno Regional de Arequipa (2009) with US$ 0.47/kg, Ramos (2012) with US$ 0.40/l in Tacna and Gamboa (2012), who obtained US$ 0.40/l of milk during the dry season in Jauja. These values were updated to American dollars to 2013 through inflation calculator (http://www.westegg.com/inflation/#).
A recent study has identified a cost of production for a small dairy farmer of US$ 0.27 while for the large dairy farmer US$ 0.33 in Concepcion - Junin (Fuentes, 2014).
A high degree of specialization and increments in input prices have the highest impact on the cost, nevertheless the size of the dairy unit seem not to have any effect on it (Wieck and Heckelei, 2004).
On the other hand, Peru, Argentina, Uruguay and Chile form together one of the three low cost regions based on the average sized farms in the world according IFCN (2015).
Efficient farmers are those dairy farmers with at least 40% of the population of their herds represented by lactating cows (Almeyda 2011).
Table 5 shows efficient farmers with lower production costs, whom in rainy season reach an average of US$ 0.22/l of milk and during the dry season S/ 0.31/l of milk. The lowest cost of production was found in Atuncolla, in a farmer with 30 ha. of land, an average production of 8 l milk per cow during the dry season and 10 l of milk in the rainy season, which employs concentrate in a semi intensive system.
|
Table 5. Farmers with greater proportion of lactating cows |
|||||
|
Name |
District |
Cost of production |
Food |
||
|
Dry season |
Rainy season |
Average |
|||
|
Farmer 1 |
Acora |
0.47 |
0.19 |
0.33 |
Concentrate |
|
Farmer 2 |
Acora |
0.27 |
0.26 |
0.26 |
Without concentrate |
|
Farmer 3 |
Atuncolla |
0.31 |
0.17 |
0.24 |
Without concentrate |
|
Farmer 4 |
Atuncolla |
0.17 |
0.16 |
0.17 |
Concentrate |
|
Farmer 5 |
Atuncolla |
0.27 |
0.25 |
0.26 |
Concentrate |
|
Farmer 6 |
Paucarcolla |
0.27 |
0.24 |
0.26 |
Without concentrate |
|
Farmer 7 |
Paucarcolla |
0.41 |
0.29 |
0.35 |
Without concentrate |
|
Farmer 8 |
Taraco |
0.21 |
0.34 |
0.27 |
Without concentrate |
|
Farmer 9 |
Taraco |
0.24 |
0.13 |
0.19 |
Without concentrate |
|
Farmer 10 |
Taraco |
0.33 |
0.29 |
0.31 |
Without concentrate |
|
Farmer 11 |
Pucara |
0.22 |
0.14 |
0.18 |
Concentrate |
|
Farmer 12 |
Ayaviri |
0.35 |
0.16 |
0.26 |
Concentrate |
|
Farmer 13 |
Ayaviri |
0.45 |
0.18 |
0.32 |
Concentrate |
|
Average |
0.31 |
0.22 |
0.26 |
|
|
|
S.D. |
0.26 |
0.18 |
0.22 |
|
|
|
With concentrate |
Average |
0.32 |
0.17 |
0.25 |
|
|
Without concentrate |
Average |
0.29 |
0.25 |
0.27 |
|
Regarding some important data for this group, the average milk production per cow/day ranges in the dry season 4.00-12.00 l; while in the rainy season varies from 5.80-18.89 l, besides 31% have mechanized milking and 69% uses family labor. In terms of the reproduction system, 92% uses artificial insemination.
The average cost of production during the dry and rainy season for this group is US$ 0.31 and 0.22/l of milk respectively, the average annual cost of production for those who use concentrate reaches US$ 0.25 /l of milk, on the other hand for those who do not use concentrate their cost is US$ 0.27/l of milk. Representing an interesting alternative the inclusion of concentrate in the rainy season to reduce cost until US$ 0.17/l of milk, reflected in a decline of 21.7% of the production cost in the group.
Table 6 show the cost of production has as a major component in labor (43,09%); followed by feedstuff (41,00%), which can be increased if farmers use as inputs concentrates during certain season of the year. Then the infrastructure cost (7.33%), to continue with health (3.42%) and reproduction (2.79%).
|
Table 6. Components of the cost of production for efficient farmers |
|||||||||
|
Name |
District |
Direct costs (%) |
Indirect costs (%) |
Total |
|||||
|
Feed |
Reproduction |
Health |
Livestock |
Labor
|
Infrastructure |
Equipment and |
|||
|
Farmer 1 |
Acora |
43.53 |
2.16 |
5.27 |
4.37 |
40.18 |
3.65 |
0.85 |
100 |
|
Farmer 2 |
Acora |
40.02 |
0.79 |
3.30 |
0.00 |
54.15 |
1.75 |
0.00 |
100 |
|
Farmer 3 |
Atuncolla |
37.34 |
1.92 |
4.36 |
0.00 |
49.08 |
6.62 |
0.69 |
100 |
|
Farmer 4 |
Atuncolla |
44.81 |
0.25 |
4.45 |
1.09 |
46.43 |
2.14 |
0.83 |
100 |
|
Farmer 5 |
Atuncolla |
36.12 |
10.83 |
5.96 |
0.00 |
38.77 |
6.68 |
1.64 |
100 |
|
Farmer 6 |
Paucarcolla |
23.91 |
2.48 |
5.66 |
1.16 |
63.14 |
1.10 |
2.54 |
100 |
|
Farmer 7 |
Paucarcolla |
33.90 |
1.94 |
2.79 |
3.63 |
52.14 |
5.18 |
0.43 |
100 |
|
Farmer 8 |
Taraco |
27.29 |
1.33 |
3.69 |
4.80 |
49.09 |
11.96 |
1.85 |
100 |
|
Farmer 9 |
Taraco |
41.07 |
5.87 |
0.84 |
0.00 |
40.41 |
10.53 |
1.27 |
100 |
|
Farmer 10 |
Taraco |
39.18 |
0.00 |
1.23 |
0.00 |
55.35 |
4.25 |
0.00 |
100 |
|
Farmer 11 |
Pucara |
52.11 |
2.02 |
0.55 |
0.00 |
39.81 |
4.14 |
1.37 |
100 |
|
Farmer 12 |
Ayaviri |
56.25 |
2.71 |
2.54 |
0.40 |
10.32 |
25.56 |
2.23 |
100 |
|
Farmer 13 |
Ayaviri |
57.51 |
3.99 |
3.90 |
0.44 |
21.28 |
11.76 |
1.12 |
100 |
|
Average |
41.00 |
2.79 |
3.42 |
1.22 |
43.09 |
7.33 |
1.14 |
100 |
|
The distribution of cost of production has a characteristic behavior in the grazing system; Gomez et al (2003) reported a 38% for feedstuff. 40% for labor. 11% for health and reproduction in Pachacayo with rye grass/clover, similar to the values calculated in the present research.
In this group are those who present less than 40% of the population represented by lactating cows. The farmers presented in table 7 are those who possess a higher proportion of dry cows and heifers in relationship with population of lactating cows. These dairy farmers are those who get a greater cost of production than the first group, during the rainy season US$ 0.28/l of milk and in the dry season US$ 0.34/l of milk. The lower cost of production for this group was found in Paucarcolla, in a farmer with 10 ha, an average production of 7.5 l of milk/cow during the dry season and 9.4 l of milk for the rainy season, which does not use concentrate in a semi intensive system.
|
Table 7. Farmers with lower proportion of lactating cows |
|||||
|
Name |
District |
Cost of production |
Feed |
||
|
Dry season |
Rainy season |
Average |
|||
|
Farmer 14 |
Acora |
0.39 |
0.35 |
0.37 |
Concentrate |
|
Farmer 15 |
Acora |
0.25 |
0.39 |
0.32 |
Concentrate |
|
Farmer 16 |
Acora |
0.48 |
0.27 |
0.38 |
Concentrate |
|
Farmer 17 |
Acora |
0.26 |
0.36 |
0.31 |
Without concentrate |
|
Farmer 18 |
Paucarcolla |
0.20 |
0.22 |
0.21 |
Without concentrate |
|
Farmer 19 |
Pucara |
0.29 |
0.29 |
0.29 |
Concentrate |
|
Farmer 20 |
Ayaviri |
0.39 |
0.17 |
0.28 |
Without concentrate |
|
Farmer 21 |
Ayaviri |
0.38 |
0.28 |
0.33 |
Concentrate |
|
Farmer 22 |
Ayaviri |
0.41 |
0.22 |
0.31 |
Without concentrate |
|
Farmer 23 |
Mañazo |
0.42 |
0.26 |
0.34 |
Concentrate |
|
Farmer 24 |
Mañazo |
0.31 |
0.32 |
0.32 |
Without concentrate |
|
Average |
0.34 |
0.28 |
0.31 |
|
|
|
S.D. |
0.24 |
0.19 |
0.21 |
||
|
With concentrate |
Average |
0.39 |
0.32 |
0.35 |
|
|
Without concentrate |
Average |
0.30 |
0.26 |
0.28 |
|
Regarding some important information likewise the average production of milk per cow/day ranges in the dry season from 3.75-12.00 l; and during the rainy season varies between 6.6-16.0 lt. The average cost of production during the dry and rainy for the less efficient group is US$ 0.34 and 0.28/l of milk respectively, but if put together the annual average cost of production for those who used concentrate with US$ 0.35/l, while those who do not use it, its cost is reduced until US$ 0.28/l of milk.
In table 8 are the components of the cost of production for this group. The structure is very similar to the previous, the main cost is the labor with 46.23%, followed by the feed with 36.21%, to continue with the infrastructure (8.25%), health (3.69%), reproduction (2.56%), management of livestock (1.37%) and equipment and machinery (1.03%).
|
Table 8. Components of the cost of production for least efficient farmers |
|||||||||
|
Name |
District |
Direct costs % |
Indirect costs % |
||||||
|
Feed |
Reproduction |
Health |
Livestock |
Labor |
Infrastructure |
Equipment |
Total |
||
|
Farmer 14 |
Acora |
34.51 |
2.12 |
4.20 |
4.29 |
50.30 |
3.90 |
0.68 |
100 |
|
Farmer 15 |
Acora |
36.01 |
0.00 |
4.60 |
1.31 |
53.40 |
4.68 |
0.00 |
100 |
|
Farmer 16 |
Acora |
37.56 |
0.00 |
1.72 |
0.00 |
55.02 |
5.36 |
0.34 |
100 |
|
Farmer 17 |
Acora |
43.29 |
1.65 |
1.02 |
0.00 |
48.98 |
3.54 |
1.53 |
100 |
|
Farmer 18 |
Paucarcolla |
35.28 |
3.00 |
3.99 |
8.64 |
47.54 |
0.41 |
1.14 |
100 |
|
Farmer 19 |
Pucara |
42.72 |
4.13 |
2.37 |
0.00 |
45.63 |
4.09 |
1.06 |
100 |
|
Farmer 20 |
Ayaviri |
47.63 |
3.44 |
9.13 |
0.71 |
36.68 |
2.07 |
0.34 |
100 |
|
Farmer 21 |
Ayaviri |
48.79 |
4.82 |
2.60 |
0.16 |
18.37 |
22.24 |
3.02 |
100 |
|
Farmer 22 |
Ayaviri |
21.06 |
3.73 |
3.54 |
0.00 |
59.05 |
10.47 |
2.14 |
100 |
|
Farmer 23 |
Mañazo |
42.29 |
2.47 |
3.14 |
0.00 |
20.77 |
30.20 |
1.13 |
100 |
|
Farmer 24 |
Mañazo |
21.61 |
2.74 |
4.32 |
0.00 |
67.54 |
3.78 |
0.00 |
100 |
|
Average |
37.34 |
2.56 |
3.69 |
1.37 |
45.75 |
8.25 |
1.03 |
100 |
|
Different values were obtained in the study by Gomez et al (2003), who point out a distribution of the cost: 51% feed, 25% labor, 9% health and reproduction for an intensive system at Lima on the other hand, Gamboa (2012) ponders as main components feed with values ranging from 55.34 to 77.24% for small and large Jauja farmer respectively.
The use of concentrate has some advantage in specific periods of a year, as during the rainy season, for the farmers with a large proportion of lactating cows, good genetics and fed with quality forage, but it should be consider that they can produce more milk but get less income for each liter of milk produced, also it has been showed with a larger cost of feed for those who supplement concentrate with 44.35% against 34.30% for the ones who don’t use it.
Table 9 shows that more efficient farmers are those with lower percentages of breakeven point, because only selling a low percentage of their production they cover their costs, the less efficient ones are farmers 24, 23 and 14.
|
Table 9. Breakeven point (BP) and % of BP |
|||
|
Unit |
District |
Breakeven point, US$ |
% PE |
|
Farmer 1 |
Acora |
1 071.94 |
46.22 |
|
Farmer 2 |
Acora |
2 022.35 |
54.72 |
|
Farmer 3 |
Atuncolla |
4 771.19 |
48.37 |
|
Farmer 4 |
Atuncolla |
4 347.33 |
26.08 |
|
Farmer 5 |
Atuncolla |
3 643.14 |
50.16 |
|
Farmer 6 |
Paucarcolla |
1 861.73 |
71.36 |
|
Farmer 7 |
Paucarcolla |
2 463.83 |
44.52 |
|
Farmer 8 |
Taraco |
2 156.25 |
38.28 |
|
Farmer 9 |
Taraco |
5 214.22 |
33.32 |
|
Farmer 10 |
Taraco |
3 783.47 |
82.81 |
|
Farmer 11 |
Pucara |
10 134.66 |
25.90 |
|
Farmer 12 |
Ayaviri |
10 186.10 |
33.45 |
|
Farmer 13 |
Ayaviri |
22 896.39 |
51.12 |
|
Farmer 14 |
Acora |
1 794.04 |
88.41 |
|
Farmer 15 |
Acora |
1 933.43 |
72.10 |
|
Farmer 16 |
Acora |
2 876.43 |
79.38 |
|
Farmer 17 |
Acora |
1 543.72 |
76.07 |
|
Farmer 18 |
Paucarcolla |
3 562.45 |
38.15 |
|
Farmer 19 |
Pucara |
4 354.33 |
66.09 |
|
Farmer 20 |
Ayaviri |
3 655.13 |
22.01 |
|
Farmer 21 |
Ayaviri |
11 287.44 |
63.57 |
|
Farmer 22 |
Ayaviri |
2 101.44 |
65.93 |
|
Farmer 23 |
Mañazo |
14 493.57 |
97.77 |
|
Farmer 24 |
Mañazo |
1 388.52 |
112.40 |
|
Maximum value |
22 896.39 |
.12.40 |
|
|
Minimum value |
1 071.94 |
22.01 |
|
|
Average |
5 147.63 |
57.84 |
|
The authors thank the Animal Science Department, Facultad de Zootecnia, Universidad Nacional Agraria La Molina for supporting the initiation of this research as well as Sierra Exportadora a governmental agency that helped during the days in the field in Puno from south to north.
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Received 30 June 2016; Accepted 25 July 2016; Published 1 September 2016