Technical and economic indicators of milk production systems in the Caiuá sandstone region

Simony Marta Bernardo Lugão

Instituto Agronômico do Paraná, Brasil

Bruno Volsi

Universidade Estadual de Londrina, Brasil

Gustavo Vaz da Costa

Universidade Estadual de Londrina, Brasil

Edson Luiz Diogo de Almeida

Instituto Paranaense de Assistência Técnica e Extensão Rural, Brasil

Tiago Santos Telles

Instituto Agronômico do Paraná, Brasil

The production of bovine milk has significant importance for Brazilian agribusiness. According to the Food and Agriculture Organization of the United Nations (FAO, 2018), in 2016, the country was the fourth largest milk producer in the world. That same year, the state of Paraná was the second-largest milk producer in Brazil, contributing approximately 14.1% of the national production, according to Municipal Livestock Production (Produção da Pecuária Municipal - PPM) data, from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística - IBGE). In the state of Paraná, there has been great technological development in milk production (Bazotti, Nazareno, & Sugamosto, 2012; Ferrazza, Lopes, de Moraes, & Pascoti Bruhn, 2015; Parré, Bánkuti, & Zanmaria, 2011). This is associated with organizational technical factors, such as collaboration between teaching, research and extension institutions, in addition to credit associations, the use of specialized labor, the selection of a herd with greater productivity and an active cooperative structure (Passetti, Eiras, Gomes, Santos, & Prado, 2016). However, there is a great heterogeneity between the producing regions (Capucho & Parré, 2012; Telles, Bacchi, & Shimizu, 2017) and the respective milk producers in Paraná (Lange et al., 2016; Neumann et al., 2016; Passetti et al., 2016). This difference is primarily characterized by the adoption of production techniques, feed supplementation for the dairy herd and genetic enhancements. Furthermore, dairy farming in Paraná is mainly undertaken on family farms, based in small agricultural establishments.

The Northwest Paraná mesoregion has a number of limitations regarding productivity gains in agricultural activities, associated with its climate and soil conditions, primarily because of the soils derived from Caiuá sandstone, considered fragile, with a low natural fertility (Fidalski, Tormena, Alves, & Auler, 2013). The presence of climate and soil characteristics unfavorable to dairy farming activities in the region, particularly with regard to the production of forage species, leads to a large increase in production costs during the winter period, mainly related to feeding the herd. Despite these constraints, the Northwest Paraná mesoregion has a relative importance in dairy farming; according to the IBGE’s PPM data, in 2016, it produced 401 million liters of milk (approximately 8.5% of the production in Paraná), ranking fifth in the state. Between 2002 and 2013, dairy production grew by almost 39%, accompanied by a 40% increase in productivity. It has approximately 23% of the effective cattle herd and 26% of the land used for pasture in the state, and approximately 78% of the establishments are family farms (Bazotti et al., 2012). According to Bánkuti, Caldas, Bánkuti, and Granco (2017) and Telles et al. (2017), this region of Paraná specializes in dairy farming.

However, there is a paucity of studies concerning the Caiuá sandstone area in the Northwest Paraná mesoregion, particularly regarding dairy farming, and it is very important to characterize the technological level of the region’s producers. According to Lopes Junior et al. (2012), there is no standard for production; the establishments range from subsistence farms to highly skilled producers with high productivity, and it is thus important to investigate the different production systems. Furthermore, there are problems with modernizing a traditional sector such as dairy farming in Paraná: it is difficult to spread and adopt process and product technologies to increase production and productivity, since technological transformations in agriculture collide with the farmer’s level of knowledge, their socioeconomic situation and the presence or absence of skilled and sustained multidisciplinary technical assistance.

It is thus understood that identification of the production systems actually used by milk producers in the Caiuá sandstone area, in the Northwest Paraná mesoregion, is important for supporting agricultural research and rural extension institutions in the creation and transfer of technologies compatible with the reality of producers in that area.

This study was realized to identify the different milk production systems in the Caiuá sandstone area in Northwestern Paraná according to their technological level and analyze their technical and economic indicators.

The study area comprises the Caiuá sandstone region, which in Paraná occupies a large part of the Northwest mesoregion and some municipalities in the West and North mesoregions (Figure 1). The region has a mesothermic humid subtropical climate, denominated Cfa by Köppen climate classification (Köppen & Geiger, 1928), characterized by hot summers, with infrequent frosts, no dry season and no water deficit. The Caiuá sandstone area is approximately 32,000 km², i.e., approximately 16% of the area of the state of Paraná.

Figure 1
Area covered by the study and by Caiuá sandstone in Northwestern Paraná.

After identifying, characterizing, classifying, and defining the types of agricultural establishments prevalent in each municipality/region of the state of Paraná, based on the 1995/96 Agriculture Census by Doreto, Laurenti & Del Grossi (2001), the Reference Network for Family Agriculture (Redes de Referência para Agricultura Familiar - REDES)¹ selected and began to monitor 38 family farms², with homogeneous characteristics in terms of milk production system (as described in Table 1), representative of the Caiuá sandstone area in the Northwest Paraná mesoregion. The farms differ according to the degree of intensification of pasture management. The REDES data are the foundation of this study.

After monitoring and analyzing the family farming establishments dedicated to milk production in the region, technical and animal indicators of milk production were obtained. Then, based on the categorization and technologies recommended by the IAPAR, three milk production systems were defined, classified according to pasture management - specifically, low, medium and high technological standards - whose characteristics are described in Table 2.

The analyses of the costs and profitability of milk production were based on the methodology of the Agriculture Federation of Parana State (Federação da Agricultura do Estado do Paraná [FAEP], 2005). The fixed and variable costs of production and the most commonly used dairy farming inputs were estimated. The prices paid and received by milk producers were obtained from the Department of Rural Economy (Departamento de Economia Rural - DERAL), of the Paraná State Department of Agriculture and Supply (Secretaria da Agricultura e Abastecimento do Paraná - SEAB-PR). The analysis period covered the harvest years 2002/2003 to 2013/2014.

Table 1
Common characteristics of milk production systems according to the technological standard.

Table 2
Specific characteristics of each milk production system according to the technological standard.

Notes. ¹Stocking rate of pastures in the rainy season. PTP: perennial tropical pasture. N: nitrogen. AU: animal unit. H Eq.: human equivalent.

The economic indicators analyzed in this study were the following: revenue from milk, revenue from sales of waste and scrap, total operating cost (TOC), actual operating cost (AOC), depreciation, total cost (TC), variable cost (VC), fixed cost (FC), gross margin (GM) and income from agricultural operations (IAO). Revenue from milk was calculated based on the amount of milk that each intensified system produced, multiplied by its price in that same period. TC was calculated based on the sum of the VC and FC. VC was composed of the sum of the items (i) fertilization, (ii) energy/protein supplementation, (iii) mineralization, (iv) health, (v) breeding and (vi) return on working capital, not considering taxes and fees. FC was the sum of expenditures on (i) animals, (ii) the site’s physical structure, (iii) miscellaneous equipment, (iv) planting of sugarcane and pasture, including soil preparation, and (v) the opportunity cost, composed of return on land, capital invested and labor. TOC was calculated based on the sum of AOC and depreciation. AOC was obtained based on the sum of VC and taxes and fees, less return on working capital. GM corresponds to revenue from sales of milk, waste and scrap, less AOC. IAO is composed of revenue from sales of milk, waste and scrap, less TOC. Economic profit was calculated by subtracting TC from the revenues.

All economic indicators were adjusted by the Extended Consumer Price Index (Índice de Preço ao Consumidor Amplo - IPC-A), the official inflation index in Brazil, to December 2017 values and converted into US dollars.

Table 3 presents the results of analyzing the profitability of dairy farming in production systems with low, medium and high intensities of pasture management between the years 2002/03 and 2013/14.

The average total revenue of the period in production systems with low, medium and high technological levels was US$ 28,853.27, US$ 56,019.48 and US$ 65,601.88, respectively. For the three systems evaluated, approximately 87% of the total revenue, on average, came from the sale of milk, irrespective of the production system. In the system with a medium technological level, there was an increase in total revenue of 94.42%, compared to the low technological level. Between the systems with medium and high levels, the difference in earnings was 17.11%; between the systems with low and high levels, this difference was 127.36%. Alvim and Botrel (2001) obtained similar results when they found that higher revenues were obtained in systems with a greater intensification of pasture management, although they showed that efficiency decreases with increased dosage of N. In this period, the total revenue of the three technological levels grew at an annual rate of 4.5% per year. This rate remains the same in the three systems studied, as, regardless of the technological level adopted, the herd’s productivity is the same; the difference between them is the number of animals. The productivity per area was thus higher in systems with higher technological levels due to the higher concentration of lactating cows per ha.

Figure 2 presents the price history per liter of milk from harvest years 2002/03 to 2013/14. The average real price per liter of milk received by the producers in the period was US$ 0.31. Regarding the price paid to the producer per liter of milk, there were sharp declines in the agricultural years 2005/06 and 2008/09, which may have compromised the producer’s revenue. These results demonstrate that in addition to climate and soil constraints, it is necessary to address market seasonality, which compromises the activity’s sustainability.

Table 4 presents the costs of producing one liter of milk, in accordance with the technological level adopted, in the Caiuá sandstone region in Northwestern Paraná between the agricultural years 2002/2003 and 2013/2014. As a rule, the system with a low technological level presented higher costs, mainly due to the economies of scale and scope of the other systems.

The variable cost accounted for 69.08, 75.70 and 77.92% of the total cost, in systems with low, medium and high technological levels, respectively, figures close to those found by Lopes et al. (2005) and Lopes et al. (2009) for the municipality of Lavras (MG). The lowest variable cost per liter of milk was found in the system with a medium technological level, at the cost of US$ 0.29. This value was 7.16% lower than that of the low level and 1.15% lower than that of the high level. In an economic feasibility study of different supplementation levels, Silva et al. (2008) obtained similar costs, ranging from US$ 0.27 to US$ 0.32 for the municipality of Campos Gerais (PR).

Table 3
Economic indicators of dairy farming in family production systems in the Caiuá sandstone region in Northwestern Paraná between the agricultural years 2002/03 and 2013/14. in US$.

Note: Actual operating cost (AOC). Total operating cost (TOC). Income from Agricultural Operations (IAO).

In the fixed cost, there was an increase of 28.72% between the systems low and medium technological levels, whereas there was an increase of 4.68% between the systems with medium and high levels, and an increase of 34.74% between the systems with low and high levels. The difference between the systems with medium and high levels was lower, as the increase in the number of lactating cows (38 compared to 45) is smaller than that between the systems with low and medium technological levels (20 compared to 38). Furthermore, most of the infrastructure investments made in the system with the lowest intensification are the same, thus gaining economies of scale in production. Although the system with a low technological level exhibits the lowest fixed cost, i.e., US$ 11,442.21, the fixed costs were more diluted in the unit cost per liter of milk in the systems with a medium and high level, US$ 0.09 and US$ 0.08, respectively. Regarding the actual operating cost, the highest cost per liter of milk was identified in the system with a low technological level: an average of US$ 0.30. Knowing that the producer is able to achieve economies of scale in the systems with medium or high technological levels, this figure was reduced an average of 7.15% in the medium level and 6.13% in the high level.

Figure 2
Price per liter of milk from harvest years 2002/03 to 2013/14, US$ L^-1. Note: the values were adjusted to December 2017 values using the IPC-A.

Table 4
Average costs of milk production per liter in the Caiuá sandstone region in Northwestern Paraná between the agricultural years 2002/2003 and 2013/2014, in US$.

Regarding the analysis of total operating cost, where the depreciation of machinery, equipment and improvements was also considered, the costs sustained in the period increased by an average of 8.88% for the low level, 5.11% for the medium level and 4.43% for the high technological level. In the studies of Simões, Silva, Oliveira, Cristaldo, and Brito (2009), depreciation was responsible for 13.16% of direct costs in the system with intensive milk production. In Lopes, Santos, Resende, Carvalho, and Cardoso (2011), the depreciation of assets ranged from 3.8% to 19.4% of the total operating cost, and the lower percentage was a reflection of the farm’s lack of infrastructure, which may have led to lower milk production. These results denote a certain breadth and heterogeneity of dairy systems, especially in relation to the use of the farms’ physical structure.

The total operating cost per liter/milk in the systems with low, medium and high technological levels was US$ 0.33, US$ 0.30 and US$ 0.30, respectively. These values were close to those found by Silva et al. (2008). When the total operating cost was subtracted from the gross revenue from milk, no positive result was obtained for the system with a low technological level. It is thus essential that additional revenue from the sale of waste and scrap be generated, in order to begin operating with a positive income from agricultural operations.

Table 5 presents the items that constitute the actual operating cost and its percentage shares for the three production systems between the agricultural years 2002/03 and 2013/14. The components that have the greatest impact on the actual operating cost are those related to animal feed.

Across the three production systems, the item with the greatest weight in the actual operating cost was energy and protein supplementation, representing an average of 64.02%. In the studies of Segala and Silva (2007), a similar result was found for the municipality of Irani (SC), with feed representing 58.7% of the total, especially during periods of drought. The second-most-represented item in the costs was the fertilization of sugarcane, with an average of 10.2%. The third-largest expenditure was animal health, corresponding to 8.5% of the actual operating cost, a figure approximately 3% greater than that found by Lopes et al. (2011) and Lopes and Santos (2012).

Regarding expenditures on animal breeding, rural electricity, conservation and repairs and technical assistance, the systems presented expenditures on these components that were inversely proportional to the technological level adopted, i.e., as the intensification of pasture management increased, their share of the AOC decreased.

Regarding gross margin, considering the average values of the period evaluated, the system with a low technological level presented the lowest gross margin (US$ 3,973.82). In the system with a medium level, the gross margin was US$ 11,366.95; compared to that of the low level, this value represents an increase of 186.0%. In the system with a high technological level, the gross margin was US$ 12,671.51; compared to that of the medium level, there is a gain of 11.5%, and compared to the low level, this gain is 218.9%. The best gross margin per liter of milk was obtained in the systems with a medium and high technological level, with an average value of US$ 0.07, followed by the low level, with US$ 0.05. As in Lopes et al. (2011), the gross margin economic indicator showed that dairy farming in systems with medium or high intensities of pasture management is sustainable even in the short and medium term.

Table 5
Components of the actual operating cost, of dairy farming in family production systems in the Caiuá sandstone region in Northwestern Paraná between the agricultural years 2002/2003 and 2013/2014.

Regarding income from agricultural operations, where expenditures on depreciation are also considered, the system with a medium technological level was the only one that did not present negative values over the period. However, considering the average values of the period evaluated, the system with a high technological level exhibited the best income from agricultural operations (US$ 10,373), with a gain of 586.7% compared to the low level and 114.2% compared to the medium level. The values for the average income from agricultural operations per liter of milk obtained in the systems with low, medium and high technological levels were US$ 0.02, US$ 0.06 and US$ 0.06, respectively. Thus, increasing the technological level can improve income, provided that the marginal cost of the extra milk produced is lower than the price of the milk received (Macdonald et al., 2017).

From an economic point of view, when considering the opportunity cost, i.e., costs of return on land, capital invested, working capital and labor, the system with a low technological level was not economically feasible, even in years where the price of milk was above the average value. The system with a medium level was economically feasible in three years, whereas the system with a high technological level was feasible in four agricultural years, years in which the price paid per liter of milk was higher than US$ 0.33-with the exception of the agricultural years 2007/08 and 2012/13, when the market presented a generalized increase in the prices of this activity’s inputs, pressured by the rise of the dollar.

Based on the analysis of economic feasibility, milk production systems confront barriers to being considered economically feasible. Both the price per liter of milk received by the producer and the prices paid for the agricultural inputs influence the final results. However, more important is the fact that in short, even in the Caiuá sandstone area, a region with climate and soil constraints, without considering economic profit, dairy farming can be profitable for family milk producers.

In dairy farming systems operating in the Caiuá sandstone area, in the Northwest Paraná mesoregion, between 2002/03 and 2013/14, without considering economic profit, these systems presented the possibility of profitability for the producers, depending primarily on the price per liter of milk and the inputs inherent in the production. However, when considering economic profit, the systems were not economically feasible.

The technological level influenced the production costs and profitability of the production systems, with a greater intensification of pasture management being correlated with better results for the indicators analyzed.