DIFFERENCES
AND SIMILARITIES IN THE MILK PRODUCTION CHAIN: A COMPARATIVE ANALYSIS WITH THE
STATES OF MINAS GERAIS AND PARANÁ
Adriano Oliveira
Cruz
Universidade
Federal de Lavras, Brazil
E-mail: adrianocruz.zoo@gmail.com
José Kennedy
Lopes Silva
Universidade
Federal de Lavras, Brazil
E-mail: kennedysilv@gmail.com
Elvis Magno da
Silva
Universidade
Federal de Lavras, Brazil
E-mail: elvismagnosilva@gmail.com
Antônio Carlos
dos Santos
Universidade
Federal de Lavras, Brazil
E-mail: acsantos@ufla.br
Luiz Marcelo
Antonialli
Universidade
Federal de Lavras, Brazil
E-mail: lmantonialli@ufla.br
Submission: 3/12/2020
Revision: 5/13/2020
Accept: 8/12/2020
ABSTRACT
Brazilian agriculture has played a prominent role all over the world, being milk production one of the exponents of the national agribusiness. The states of Minas Gerais and Paraná are protagonists in the milk production business in the country. The objective of this study was to evaluate the differences and similarities of the milk production chain in these two states, considering the period from 2008 to 2017, in order to investigate their dynamics and their competitiveness. The methodological approach adopted in the research was of a quantitative nature, with the use of the software “Statistical Package for the Social Sciences” (SPSS), which allowed the analysis to be carried out with the statistical techniques of analysis of variance (Anova) and cluster analysis. Ward’s agglomerative method and discriminant analysis were also adopted. The state of Minas Gerais presented a superior milk production chain in comparison with Paraná in every year analyzed; however, statistically there was no significant difference in the milk production from 2009 to 2017. Paraná presented better milk productivity averages as compared to Minas Gerais; it was highly significant (1%) from 2008 to 2016 and significant (5%) in 2017. The results of the cluster analysis indicated that, due to the fact that Paraná has higher productivity indexes in relation to Minas Gerais, its limits are better in relation to Minas Gerais in the analyzed aspects. It was found that some municipalities that are considered to have high productivity in Minas Gerais do not enter this same group in Paraná. It can be said that Paraná was shown to be more efficient in the milk production chain as compared to Minas Gerais in the analyzed time period. The article indicates the need to improve the technology used in the milk production chain, so that the numbers related to productivity can be improved. In addition, it was found that it is necessary to invest in genetics and technical assistance so that milk producers in the states surveyed can become more competitive.
Keywords: Productive chain. Milk. Minas
Gerais. Paraná. Brazil
1.
INTRODUCTION
With the population
increase and its consequent demand for food, Brazil will be one of the major
global players in the supply of agribusiness produce (Bacha, 2000). According
to the Food and Agriculture Organization (FAO), an estimated 70% increase in total
demand for food is expected by 2050 (Fao, 2009). In 2015, this same entity
pointed out that around 805 million people in the world did not have enough
food to lead a healthy and active life.
Agribusiness is the main
economic segment responsible for generating employment, income and food in
Brazil (Assman et al., 2016). The country is one of the world leaders in the
production and export of various agricultural produce. The country is the first
producer and exporter of coffee, sugar, alcohol and fruit juices. Additionally,
it leads the ranking of foreign sales of soybeans, beef, chicken, tobacco,
leather and leather shoes.
In a study that analyzes
the period from 2001 to 2010, the authors state that agribusiness corresponded
to 38% of all Brazilian international business (Leme, 2011). This number is
significant, given that it is a single segment that holds more than a third of
all international transactions in the country. Even in 2008 and 2009, a period
in which there was an abrupt reduction in the comparison between one year and
another regarding total exports (22.7% decrease), agribusiness had a
considerable less significant decrease of less than 10% (Leme, 2011).
An analysis of the
Brazilian national market highlights the growth of the product “milk”, with
dairy farming standing out in Brazilian agribusiness. It is responsible for an
important part of the investments made in the country, represented by
producers, industries, commerce, government and consumers. States such as Minas
Gerais, Paraná, Rio Grande do Sul, Goiás, Rondônia, São Paulo and others stand
out in the milk production chain. In this study, we focus on the states of
Minas Gerais and Paraná, which are important milk producers in the country. The
objective of this study was to evaluate the differences and similarities of the
milk production chains in Minas Gerais and Paraná in the years from 2008 to
2017, aiming at understanding the dynamics and competitiveness relationships
that exist in the structures of each milk production chain.
This work is structured
in four sections. After this introduction, the second section deals with the
specific approach of the milk production system in Brazil. After that, it will
be presented how the milk production chains in Minas Gerais and in Paraná work.
The economic data of the two states surveyed will be presented in the last
section and a statistical analysis will be then carried out.
2.
LITERATURE REVIEW
2.1.
Milk
Agribusiness In Brazil
The context of dairy
production in Brazil is diverse and heterogeneous. There is milk production in
all regions and states of the country, and some regions and states stand out in
relation to the others – the South and Southeast regions and the states of
Paraná and Minas Gerais are examples of that (Lopes Júnior et al., 2012).
Another important factor is that there is no specific pattern of production in
Brazil and such process makes it difficult to have a greater production when it
comes to comparing it with the production of other countries (Lopes Júnior et al.,
2012).
Dairy farming has
remained on the sidelines in Brazilian agriculture for more than three
centuries. Since the end of the 19th century, dairy farming has
increased its production in Brazilian farms. This occurred largely due to the
coffee decline and the modernization of farms (Vilela et al., 2017). Regarding
such modernization, it is important to point out that it was only from the
1950s onwards that the technology of farms expanded, mainly due to the
country’s second industrial revolution.
Frame 1: Historical overview of dairy farming
in Brazil
|
Features |
Chronology |
|
Origin of livestock |
16th
century: first cattle arrived in the country; dairy farming did not exist
until 1950; after this year, husbandry was driven by technological
modernization. |
|
Modernization |
Since 1950:
public policies implemented by the Government have driven the regularization
of milk quality and production in the country. |
|
Impact on livestock |
Since 1990: The
maturation of the milk production chain has led to significant growth and
resulted in domestic production, due to the growth of the herd, substantial
imports and, above all, increased productivity. |
Source: Elaborated by the authors based on (Vilela et
al., 2017).
In
Brazil, in the last 50 years, milk production has grown considerably, despite
government interventions such as economic plans, prices and controlled imports.
Milk production in Brazil has shown growth since the first records released in
1961 by FAO. From the 1990s onwards, the milk production chain was transformed
in the context of a crisis involving the lack of specialization of rural
producers. It was necessary to make several advancements from the end of the
1990s and from the beginning of the 2000s that ended up modifying the behavior
of the agents of the milk production chain. Such transformations were possible
due to the proximity of producers with universities and research centers
(Slomp, 2003).
There are also some
improvements to be considered in the political and economic field which
reflected in the other links of the milk production chain. The roles of the Organização das Cooperativas Brasileiras (OCB),
of the Leite Brasil and of the Confederação da Agricultura Nacional de
Pecuária do Leite (CNPL) (respectively, Organization of Brazilian
Cooperatives, Brazilian Milk and Confederation of the National Agriculture for
Livestock of Milk) stand out. The main advances that public and private
policies have offered the milk production chain in Brazil are related to trade
defense. Regarding the imports of milk produce in Brazil, some important
measures can be mentioned: a) the prohibition of the production and marketing
of long-life milk; b) the adoption of
the prior consent of the Ministry of Agriculture to verify the quality of the
milk to be imported; c) the raising of taxes for the import of dried milk and
of cheeses in order to protect Brazilian producers (Slomp, 2003).
The specialization of
dairy farming is, in fact, an important aspect that has been improved in dairy
production in Brazil. Resources allocated by the Ministry of Agriculture via
rural credit contributed significantly to the specialization of dairy farming
(Slomp, 2003). Modernization is also a major factor in the growth of dairy
farming in Brazil (Vilela et al., 2017). Dairy production has already
experimented considerable influences from technology to increase its
production. It is estimated that, in order to be even more productive, more
technological investments on behalf of the government, of dairy producers and
of the entire milk production chain will be necessary.
Dairy farming is an
important segment of the country’s rural economy, as it generates jobs within a
very dynamic chain that involves several actors (Perobelli, Araújo Júnior &
Castro, 2018). Brazilian milk production leveraged mainly due to the creation
of public policies, which offered support, stimulated milk production and also
showed the most productive regions of Brazil in that respect, which are
Southeast, South and Midwest regions (Moraes
& Bender Filho, 2017). The North and Northeast regions have lower numbers
even with a significant herd.
The “productive chain”,
concept discussed by (Brum, Kelm & Albornoz, 2014), is considered in this
work as a set of activities and practices that are articulated in order to
accomplish a certain objective, mainly economic, according to several authors
(Zylbersztain, 2000; Proechnik & Haguenauer, 2002; Batalha, 2007; Brum,
2012). The production chains are the result of interdependent movements among
actors that subsidize structure, equipment and consumer products and mediate
the entire production process until the final result of distribution and
commercialization of a product.
Figure
1 summarizes the configuration of the milk production chain in Brazil
(Perobelli, Araújo Júnior & Castro, 2018).
Figure 1: Milk production chain
Source:
Available in (Perobelli, Araújo Júnior & Castro, 2018, p. 301).
The
first horizontal axis represents the public sector and its responsibilities
towards the dairy activity. Its main
function is to support dairy farmers in their production. Consequently, it
involves the beginning of the network composed of the private actors that
surround the chain and it has as its responsibility to make the milk production
infrastructure available to other players in this process. The second axis, in
the vertical direction, plays the role of distributing fresh production to
large industries, associations and cooperatives and small industries that are
responsible for processing the product for later delivery to wholesalers and
retailers, who consequently give the customers access to the produced and
packaged milk.
The milk production chain
is formed by several agents that interact among each other from the moment of
the production of inputs, first link in the chain, which connects
manufacturers, equipment, credit and educational and research organizations. In
the second link, we find the producers who raise the animals and produce the
milk. After that, there are industries that transform the raw material and are
also responsible for the transportation and distribution of the milk. Finally,
we have the consumers who buy the dairy products (Brum, Kelm & Albornoz,
2014). This whole production chain needs good governance execution by the
mentioned actors, so that the product has a good standard in production and
marketing to reach consumers with quality. The involvement of all actors in the
chain is important for the dairy industry to continue standing out in the
national economy.
In Brazil, the numbers
of individual milk producers have been decreasing in recent decades. However,
this decrease has not affected milk production, a fact which can be justified
by the technological evolution and professionalization of milk production in
the country (Vilela et al., 2017). The consumption of such drink has also been
growing and this is due to several factors, such as population and economic
growth, shifts in consumer eating habits, greater milk production and consumer
access to the product.
Brazilian dairy farming
was encouraged to produce derivatives. This, however, generated a prospect of
importing milk from neighboring countries in South America, namely Argentina,
Uruguay and Chile (Moraes & Bender Filho, 2017). The export market in
Brazil is still in development, but it is promising. It needs actions and
policies so that the commercialization of Brazilian milk outside the country
can be consolidated.
In economic terms, the
mentioned increase in production and marketing was also influenced by
technological modernization and economic shifts reinforced by the Plano Real (Real Plan, a set of measures
taken to stabilize the Brazilian economy in 1994). Such factors contributed to
the decrease in production costs and, consequently, to a better organization of
the entire milk production chain, which generated better financial results.
The behavior of prices
and their evolution beyond the farm gate can be explained by the following
factors: supply and demand; industry and producer; changes in the milk market;
and government interference in livestock (Vilela et al., 2017).
Dairy activity in Brazil
is full of challenges, which are concentrated on pricing policies, production
methods and technology and product logistics. Therefore, it is necessary to
integrate the entire production chain in order to meet the central objectives
of dairy farming. Involving all actors in the chain is of paramount importance,
so that the Brazilian milk production continues to consolidate itself as an
important sector of agribusiness.
2.2.
Milk Agribusiness In The States Of
Minas Gerais And Paraná
The milk production
chain, which is named by Assmann et al. (2016) as the “Agro-Food System” (AFS)
for milk, is a set of diverse practices which involves organizations that, in a
way, keep everything interconnected for the development of activities in the
dairy segment (Assman et al., 2016). The same authors state that analyzing the
milk production chain is a very complex activity, since milk production
involves several actors in a network that needs a lot of dialogue among its
members.
Figure 2 shows the
Brazilian states with the largest milk production in the country. It can be
noted that Minas Gerais and Paraná stand out as important producers (Perobelli,
Araújo Júnior & Castro, 2018). In the case of Paraná, in 2015, there was a
considerable improvement in its position, which guaranteed the second place to
the state, surpassing important players like Rio Grande do Sul and São Paulo
(Perobelli, Araújo Júnior & Castro, 2018). For a better understanding of
the statistics of milk production, figure 2 presents information about the
states participating in the milk production chain.
Figure 2: Milk production in the most important
Brazilian states.
Source: Available in (Perobelli, Araújo Júnior & Castro,
2018, p. 302).
Caption: MG –
Minas Gerais; SP – São Paulo; RS – Rio Grande do Sul; PR – Paraná; GO – Goiás;
SC – Santa Catarina.
Minas Gerais stands out
due to recent production changes. Dairy farmers differentiate their production
practices by approaching technologies. Moreover, the state has also been
engaging in other types of agricultural production, which guarantees an opportunity
for producers for the good use of their land for cattle breeding.
Differences in regional
production in the state of Minas Gerais may occur due to the formulations of
regional production chains already exemplified in figure 1 (production chain).
The formulation and practices of actors in the regional chain interfere in the
production of each region of the state.
The milk production in Minas Gerais is formed by small and medium-sized
dairy products (Perobelli, Araújo Júnior & Castro, 2018). The good results
of milk production are related to the infrastructure and to the network growth
of the production of the municipalities that take part in the dairy culture –
that is, the organization of the chain and the network among the municipalities
ensures that the milk production in Minas Gerais continues to stand out in
relation to the national dairy production.
The milk production
chain in Paraná has a hybrid governance structure, as it involves formal and
informal contracts between producers and processors. The two profiles of
specialized and non-specialized producers are also found (Acosta & Souza,
2017). Over time, the state has seen its milk production grow very
significantly. Between 1997 and 2006, Paraná’s milk production increased by
71%, which consolidated the state as the second largest dairy producer in the
country (Ipardes, 2009). Dairy production technology has gradually contributed
to the consolidation of dairy farming in the state of Paraná (Silva, Camara
& Telles, 2016).
Milk production in
Paraná was organized based on three structures: technology, governance and
legislation. The changes in milk production did not develop in a straight line
in the country and in Paraná, since there are several factors that interfere,
such as climate, geographic and cultural aspects, economic development, among
others. Such factors interfere in the diversity of the dairy field and its
structure as a production chain (Acosta & Souza,2017).
In the milk production
of Paraná, the discussion of the Differentiated Agrifood System (DAS) is also
highlighted in an incipient way. In the DAS, the production method adopted is
the agroecological one, which is mainly characterized by the production of
organic milk, a differentiated product due to a production system that refuses
the use of pesticides and takes care of the well-being of the animal (Nogueira
et al., 2018).
The profile of the dairy
farmer in Paraná is characterized as a family farmer who perceives dairy
farming as the main source of income, in addition to the social security
pension or retirement benefits (Bazotti, Nazareno & Sugamosto, 2012).
Generally, the properties of milk producers are formed by an average
three-member family. The labor force is usually female, but men take charge of
the management of milk production. Paraná producers sell their production to
buyers, who, generally, are small and medium-sized processors, cooperatives,
large industries and large food industries (Acosta & Souza, 2017).
Financing policies are
not used by dairy farmers, as they do not believe they will be able to pay the
financing and risk losing their land afterwards. Cooperatives and associations
develop important work to represent dairy farmers (Ipardes, 2009).
It is shown that the
fixed cost of production in Paraná is high, in the research that compares milk
production in Paraná and in the Province of Santa Fé, in Argentina, which ends
up making production values more expensive and, consequently,
makes the producers have lower profit rates with their production (Hofer &
Shikida, 2000).
3.
METHODOLOGY
This research adopted
the quantitative research method, which is used in the development of
researches in the social, communication, marketing, administrative and economic
fields, generally representing a guarantee of the accuracy of the results,
avoiding mistakes and distortions in the interpretation of the data (Oliveira,
2002).
For a comparison between
the milk production chains of Minas Gerais and Paraná, data were collected in
all the municipalities of these two states – 853 in Minas Gerais and 394 in
Paraná. Such data were obtained from the Instituto
Brasileiro de Geografia e Estatística (IBGE) (Brazilian Institute of
Geography and Statistics), considering the period from 2008 to 2017. The
variables analyzed were: milk production, number of dairy cows, productivity
and production value of each municipality/state. The secondary data obtained
were tabulated and processed using the Statistical Package for the Social
Sciences (SPSS) software. For data analysis, the following statistical techniques
were used: analysis of variance (ANOVA), analysis of clusters, adoption of the
Ward agglomerative method and discriminant analysis.
ANOVA was used to compare the averages of the variables. Hypotheses were
tested –the null hypothesis is that all averages are equal (Malhotra, 2006).
For the comparison of averages using ANOVA, the distribution of variables must
have a normal distribution (Maroco, 2007). This technique can be used depending
on the research carried out. When the intention is to compare a dependent
variable with more than two dependent groups, we use ANOVA-one-way. If there is
more than one factor, the analysis of variances must be done by the factorial
ANOVA (Maroco, 2007). In this article, we used ANOVA-one-way, since the
comparison was made between two variables. As it was already mentioned, a
comparison of the averages of the variables milk production, dairy cows,
productivity and production value between Minas Gerais and Paraná, in the
period from 2008 to 2017, was carried out.
Cluster analysis was
used to group the observations according to their similarity.
The analysis of groups or clusters is an exploratory technique of
multivariate analysis that allows to group subjects or variables in homogeneous
groups in relation to one or more common characteristics. Each observation
belonging to a specific cluster is similar to all others belonging to that
cluster and is different from the observations belonging to the other clusters
(Maroco, 2007, p. 421).
The cluster analysis is important the purpose of grouping observations
of similar characteristics (Hair Júnior et al., 2005, p. 193; Maroco, 2007, p.
421) and
The resulting clusters of objects must then exhibit high internal
homogeneity (within clusters) and high external heterogeneity (between
clusters). Thus, if the classification is successful, the objects within the
groupings will be close when represented graphically and different groupings
will be distant. (Hair Júnior et al., 2005, p. 384).
The use of cluster
analysis in this work was based on the grouping of observations regarding the
productivity variable. The number of four clusters was defined in the following
way: group 1 refers to very low productivity; group 2, low productivity; group
3, medium productivity; and group 4, high productivity. The option for this
variable for the construction of clusters was considered as an important
indicator of the efficiency in the milk production chain.
The discriminant
analysis was used to assess which variables discriminated and which had the
greatest influence on the four groups formed in the cluster analysis of each
state. Hair Júnior et al. (2005) state that the discriminant analysis involves
determining a statistical variable. A discriminating statistical variable is
the linear combination of the two (or more) independent variables that are best
discriminated among objects (people, companies etc.) in the groups defined a priori. The discrimination establishes
the weights of the statistical variable so that each independent variable
maximizes the differences among the groups. The statistical variable for
discriminating analysis, also known as the “discriminating function”, is
determined by an equation.
4.
ANALYSIS OF RESULTS AND DISCUSSIONS
Tables 1 and 2 show the
values of the averages of the variables milk production, dairy cows,
productivity and production value of the states considered in this research. As
we can see, milk production in Minas Gerais increased from 2008 to 2014, but
there was a decrease of 2.41% in 2015 as compared to 2014. This decrease was
caused by climatic problems and by the increase in production costs (Seab,
2017). Despite such numbers, the state remains the top producer in the country.
The state of Paraná showed an increase in its production from 2008 to 2016,
jumping to the second place in the national ranking of milk producing states.
As milk production
dropped, the same could be seen in the number of dairy cows, which fell by
7.10% in Minas Gerais and 5.19% in Paraná, due to the factors previously mentioned.
Regarding the value of production, we observed a slight decrease (1.8%) in 2015
compared to 2014 in Minas Gerais – followed by an increase in 2016 (18.41%). In
the analysis, it was observed that even with the decrease in production and in
the number of dairy cows, the value of production continued to grow in Paraná
and Minas Gerais (with the exception of 2015), which can be explained by the
productivity factor. Productivity increased 67.76% in Minas Gerais and 45.58%
in Paraná, in the years from 2008 to 2017, which means that, even with a
reduced production, there may have been a reduction in property costs, since
there was a reduction in the number of milked animals.
Table 1: Average numbers of the variables milk
production, dairy cows, productivity and production value in the municipalities
of Minas Gerais.
|
Year / variable |
Milk production |
Dairy cows |
Productivity |
Production value |
|
2008 |
8976.93 |
6030.12 |
1408.12 |
5934.40 |
|
2009 |
9297.93 |
6188.48 |
1412.35 |
6237.64 |
|
2010 |
9833.58 |
6385.70 |
1439.12 |
7059.49 |
|
2011 |
10265.07 |
6601.49 |
1451.38 |
8132.85 |
|
2012 |
10440.78 |
6652.16 |
1462.30 |
8768.83 |
|
2013 |
10913.43 |
6859.01 |
1486.92 |
10821.54 |
|
2014 |
10985.32 |
6809.52 |
1507.93 |
10901.47 |
|
2015 |
10720.95 |
6358.35 |
1580.24 |
10708.74 |
|
2016 |
10516.74 |
5831.71 |
1704.88 |
12680.05 |
|
2017 |
10448.50 |
3990.12 |
2362.29 |
11161.31 |
Milk
production (1000 liters / state / year); Dairy cows (heads / state / year);
Productivity (liters / cow / state / year); Production value (R$ 1000 / state /
year).
Source:
Research data (2019).
Table
2: Average numbers of the variables milk production, dairy cows, productivity
and production value in the municipalities of Paraná.
|
Year / variable |
Milk production |
Dairy cows |
Productivity |
Production value |
|
2008 |
7114.12 |
3349.18 |
17178 |
4002.95 |
|
2009 |
8384.18 |
3741.40 |
1843.54 |
5035.58 |
|
2010 |
9012.04 |
3895.24 |
1945.52 |
5965.91 |
|
2011 |
9569.90 |
3994.22 |
1997.64 |
7175.92 |
|
2012 |
9948.19 |
4059.45 |
2062.55 |
8056.34 |
|
2013 |
10907.95 |
4311.53 |
2093.01 |
9907.89 |
|
2014 |
11380.86 |
4335.35 |
2185.63 |
10655.69 |
|
2015 |
11683.74 |
4121.62 |
2323.77 |
11334.23 |
|
2016 |
11841.92 |
4050.92 |
2413.25 |
14626.77 |
|
2017 |
11120.37 |
3624.39 |
2550.27 |
12794.40 |
Milk
production (1000 liters / state / year); Dairy cows (heads / state / year);
Productivity (liters / cow / state / year); Production value (R$ 1000 / state /
year).
Source:
Research data (2019).
The analysis of the variance in milk production, production value, dairy
cows and productivity is shown in table 3. As it can be seen, in the ANOVA of
milk production, there was a 5% significance only in 2008. In the other years,
there was no significance. Therefore, Minas Gerais presented a superior milk
production in comparison with Paraná in every year considered; however,
statistically there was no significant difference in milk production from 2009
to 2017.
Table 3: ANOVA for the variables milk production, dairy cows,
productivity and production value in the municipalities of Paraná and Minas
Gerais.
|
Year / Variable |
Milk production |
Dairy cows |
Productivity |
Production value |
||||
|
F |
Sig. |
F |
Sig. |
F |
Sig. |
F |
Sig. |
|
|
2008 |
5.649 |
0.018 |
45.025 |
0.000 |
61.716 |
0.000 |
14.666 |
0.000 |
|
2009 |
1.144 |
0.285 |
34.910 |
0.000 |
85.985 |
0.000 |
4.621 |
0.032 |
|
2010 |
0.841 |
0.359 |
33.770 |
0.000 |
110.023 |
0.000 |
2.909 |
0.088 |
|
2011 |
0.526 |
0.468 |
34.945 |
0.000 |
125.495 |
0.000 |
1.612 |
0.204 |
|
2012 |
0.242 |
0.623 |
32.180 |
0.000 |
149.967 |
0.000 |
0.679 |
0.410 |
|
2013 |
0.000 |
0.996 |
28.724 |
0.000 |
151.947 |
0.000 |
0.736 |
0.391 |
|
2014 |
0.134 |
0.714 |
27.159 |
0.000 |
185.638 |
0.000 |
0.056 |
0.814 |
|
2015 |
0.774 |
0.379 |
23.823 |
0.000 |
196.750 |
0.000 |
0.322 |
0.571 |
|
2016 |
1.507 |
0.220 |
18.247 |
0.000 |
161.403 |
0.000 |
1.863 |
0.173 |
|
2017 |
0.379 |
0.538 |
1.453 |
0.228 |
7.937 |
0.005 |
1.720 |
0.190 |
Source: Research data (2019)
Regarding the value of
production, the behavior of milk production was similar. It was tested and
found that the difference in the averages between Minas Gerais and Paraná was
highly significant (1%) only in 2008. The number of dairy cows was highly
significant in the years from 2008 to 2016. In 2017, there were no significant
differences between the averages, because there was a decrease of 31.6% in the
number of dairy cows in Minas Gerais and, in Paraná, a decrease of only 10.5% –
therefore, the averages stood close. Lastly, in terms of productivity, it was
highly significant from 2008 to 2016 and significant in 2017, when Paraná
presented better milk productivity averages compared to Minas Gerais (table 1).
The cluster analysis was
also carried out in order to group the municipalities according to their
productivity. In order to do so this, the total productivity of cows in liters
per municipality was calculated for the analyzed period (years from 2008 to
2017) for each state.
Based on the cluster
analysis, four groups were defined for each state: 1) very low productivity; 2)
low productivity; 3) medium productivity; and 4) high productivity. Analyzing
table 4, it can be noted that in Minas Gerais the group with the highest
frequency was of medium productivity (with 33.1%), and that the group with the
lowest frequency was the one with high productivity (with 10.2%). In Paraná,
the group with the highest frequency was the one with very low productivity,
with 54.6%, and the one with the lowest frequency was the highest productivity,
with 6.1%.
The results of the
cluster analysis indicated that, for the state of Paraná, below 19643.9
liters/cow/year would be the limit for the municipality with productivity to be
considered to have very low productivity. On the other hand, in Minas Gerais,
this item was much lower in relation to Paraná – that is, with 11505.5
liters/cow/year so that the municipality could be considered to be of low
productivity. For a comparison, the value of 19643.9 liters/cow/year, which is
considered the limit to be within the group of municipalities with very low
productivity in Paraná, would be considered a municipality of medium
productivity in Minas Gerais, a group that presents an interval productivity
from 16659.85 to 23468.72 liters/cow/year.
Table 4: Result of the cluster analysis of the
municipalities of Minas Gerais (MG) and Paraná (PR), with their frequencies,
minimum and maximum productivity limits for each group.
|
Groups |
Frequency MG |
Frequency PR |
Minimum MG |
Maximum MG |
Minimum PR |
Maximum PR |
|
Very low |
208 |
215 |
4129.42 |
11505.50 |
5961.85 |
19643.90 |
|
Low |
276 |
90 |
11632.96 |
16578.11 |
19836.51 |
28544.60 |
|
Medium |
282 |
65 |
16659.85 |
23468.72 |
28923.81 |
27601.4 |
|
High |
87 |
24 |
23707.4 |
49769.5 |
38517.95 |
73245.2 |
|
Total |
853 |
394 |
- |
- |
- |
- |
Frequency:
number of municipalities belonging to each group by state; Minimum: Minimum
required productivity in liters of cows / municipality / period determined by
cluster analysis by group; Maximum: Maximum required productivity in liters of
cows / municipality / period determined by cluster analysis by group.
Source:
Research data (2019).
Considering both states, the municipality with the lowest productivity
is Divisa Alegre, which belongs to the state of Minas Gerais, with a
productivity of 4129.42 liters/cow/year – such number corresponds to 1.13l cow per day. On the
other extreme, we have the municipality of Castro, in the state of Paraná,
which presented the best productivity of the two states: 73245.2 liters
cow/year, the same as 20.07l cow per day. The municipality of Castro stands out
in terms of milk production and productivity in Brazil. It was even awarded the
title of “Brazilian Capital of the Milk” by Law number 13.584, in force since
December 26th 2017 (Brasil, 2017).
Due to the fact that
Paraná has higher productivity indexes in relation to Minas Gerais, its limits
are better in relation to Minas Gerais in the analyzed aspects (very low, low,
medium and high productivity). It was found that some municipalities that are
considered to have high productivity in Minas Gerais do not enter this same
group in Paraná.
For the discriminant
analysis, the four groups extracted by the cluster analysis were defined as the
dependent variable. Tables 5 and 6 show the independent variables, all
considered highly significant (0.000) by the discriminant analysis.
Table 5: Results of the discriminant analysis
of the groups in Paraná with the extraction stages, Wilks’ Lambda statistics
and level of significance for each variable.
|
Stage |
Inserted |
Wilk’s Lambda |
Sig. |
|
1 |
Total production PR |
0.623 |
0.000 |
|
2 |
Total dairy cows PR |
0.581 |
0.000 |
|
3 |
Total production value PR |
0.521 |
0,000 |
Source: Research data (2019).
In Paraná, according to
the data presented in table 5, it seems that the variable value of total
production was the first to enter the discriminant function, which means that
this variable was the one that most discriminated the four groups regarding
productivity. The variable “dairy cows” was the second to enter the model,
followed by total production.
Table 6 shows the three
discriminating variables of the four groups in Minas Gerais. The variable
“total production” was the first to enter the model, followed by the variables
“total dairy cows” and “total production value”.
Table 6: Results of the discriminant analysis
of the groups in Minas Gerais with the extraction stages, Wilks' Lambda
statistics and level of significance for each variable.
|
Stage |
Inserted |
Wilk’s Lambda |
Sig. |
|
1 |
Total production value MG |
0.806 |
0.000 |
|
2 |
Total dairy cows MG |
0.602 |
0.000 |
|
3 |
Total production MG |
0.560 |
0.000 |
Source: Research data (2019).
As previously mentioned,
the results demonstrate that there is a marked difference between the two
states. Minas Gerais has the highest total milk production and, on the other
hand, Paraná has the best productivity. According to the Censo Agropecuário (Brazilian Agriculture Census) conducted by the
IBGE, between 2006 and 2017 the number of establishments that produced milk
fell by 2.98% in Minas Gerais and by 27.34% in Paraná. However, the same did
not happen with milk production (as shown in table 7). This be attributable to
technological advances (Perobelli, Araújo Junior & Castro, 2018): even with
the expressive decrease in the number of rural producers in Paraná, milk
production suffered no impact.
Table 7: Number of establishments that produced
milk in Minas Gerais and Paraná.
|
Year |
State |
|
|
Minas Gerais |
Paraná |
|
|
2017 |
216.419 |
87.048 |
|
2006 |
223.073 |
119.810 |
Source: Censo Agropecuário
(IBGE, 2006; 2017).
It can be said that
Paraná has shown to be more efficient in the milk production chain compared to
Minas Gerais in the analyzed period. Unlike Minas Gerais, in Paraná the
variable that most discriminated against the four groups was production because
it had higher productivity. Minas Gerais has the top milk production in Brazil
and has a higher number of municipalities than Paraná – therefore, the value of
milk production had greater divergence between the groups of Minas Gerais for
presenting a smaller interval of milk production as compared to Paraná.
In Minas Gerais, milk
production dropped slightly in 2017 (table 1), after an increase of nine
consecutive years. This was due to increased productivity. With the increase in
productivity, even with fewer establishments, production continued to increase.
Productivity is an index that indicates the efficiency of a milk producing
establishment. Therefore, it was found that Paraná is superior in productivity
in relation to Minas Gerais in the analyzed period. The adoption of
technologies, animals of proven genetic quality, good management practices and
technical assistance to rural producers may have influenced Paraná’s high
productivity.
In 2017, of the total
milk producing properties in Minas Gerais (216.419 properties), 70.27% of them
did not receive any type of technical assistance, number which corresponds to
152.079 rural properties without access to external technical information
(IBGE, 2017). In Paraná, of the total number of properties (87.048 establishments),
47.83% did not receive technical assistance. The fact that the rural producer
in Minas Gerais did not modernize, improve techniques, improve livestock, among
other practices, may have contributed to the significant difference in the
technical efficiency of the production (IBGE, 2017).
5.
CONCLUSIONS
The objective of this
study was to evaluate the differences and similarities of the milk production
chain in the Brazilian states of Minas Gerais and Paraná in the years from 2008
to 2017. In order to do so, variables related to dairy activity were analyzed
for the 853 municipalities in Minas Gerais and for the 394 municipalities in
Paraná, according to data released by the IBGE.
The differences in
averages of these variables between the two states were tested using ANOVA,
which presented expressive results regarding the differences in the production
chain of these two states. The cluster analysis was also carried out for each
state – that is, the municipalities were grouped considering the productivity
variable. In Paraná, the productivity limits among the extracted clusters
proved to be higher and therefore more rigorous.
The results of the
discriminant analysis showed the main differences between the states,
considering the clusters as a dependent variable. The significant independent
variables for the two states were extracted. In Paraná, the variables in order
of extraction were: total production, total dairy cows and total production
value. On the other hand, in Minas Gerais, the variables in order of extraction
were: value of total production, total dairy cows and total production.
Membership in
cooperatives can be an alternative for rural producers to improve zootechnical
production rates, in addition to having efficient technical assistance on their
property. The municipality of Castro, belonging to the state of Paraná, was the
one that stood out the most in this work, performance for which the Castrolanda
Cooperative is mainly responsible. Nowadays, this cooperative has 877 members
and is one of the most well-known cooperatives in the country, having already
received recognition and awards, such as “The farm of the year”, for its
national prominence in dairy farming (CASTROLANDA, 2019). This cooperative may
have influenced directly in the recognition of the municipality of Castro as
the Brazilian Capital of Milk.
The results point to the
importance of adopting technology in the milk production chain. This factor was
reflected in this work indirectly in the productivity variable, improving
production. To become more competitive in the market, dairy farms must invest
in technology, genetics and technical assistance.
The state of Minas
Gerais presented higher values of the variables milk production,
dairy cows and production value in relation to the state of Paraná, but it was
lower in the productivity variable. Productivity is the factor that
demonstrates the efficiency of the dairy activity. If there is investment in
technology, genetics and technical assistance, there will be a tendency to
increase productivity rates.
The limitations of this
work are related to the method of data collection and secondary measures, as
well as in relation to the exclusion of the year 2018. The lack of some
variables was also a limiting factor, such as the average production cost of
dairy farms and the number of producers for each year analyzed in the study,
since these data would be useful for an in-depth investigation and comparison
between these two states.
As a result of the
discussions in this work, it is possible to suggest a research agenda in
relation to the milk production chain in Brazil. Therefore, it is suggested
that the following studies be carried out: a) a research involving comparisons
among the production chains of other states and others regions of the country,
so that we can have a broader understanding of how milk production chains in
Brazil develop and function; b) an analysis of the specific patterns of dairy
production in Brazil and how they impact in the production processes; c) a
development of specific research in the North and Northeast regions on the milk
production of the states of such regions, in order to understand why their milk
production is lower in relation to the states in other regions of the country;
and d) a comparison between the Brazilian production chain and those of other
countries that are reference in production and productivity, in order to
identify positive aspects and aspects that can be improved in the national milk
production chain.
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