The main goal of this article is to present the System for Grain
Storage in Brazil (SIARMA), which aims to identify grain storage prices (soy
and corn) in Brazil for the main producer regions. Also, it is presented the
developed tool, integrating an information system of secondary statistics
(statics of storage capability, grain production, exportation seasoning,
marketing prices and road freight prices) in a way it can quantify logistics
strategies to maximize the revenue of the Brazilian producer and evaluate
benefits that could come out from the use of storage. It is
presented a case for the main producer state of soy and corn in Brazil, Mato Grosso.
Such tool has presented successful results to instigate discussions about
economic benefits of storage and support the decision-making both in public as
well as in private sectors. Also, are presented data source of grain storage in
the country. Siarma’s next steps involve the incorporation of other
agricultural products, identifying annual storage levels, among other factors.
Keywords: Grain; Brazil; Storage; Stock; SIARMA; SIFRECA
1.1. Context of the storage situation in Brazil
storage in the country has the function of keeping the products in order to
meet needs in different places and periods with the due quality. In the case of
the agriculture, this characteristic of maintaining the grains offer throughout
the off-season is extremely important. On the other hand, the storage can also
be used as a commercial strategy to obtain higher revenues in the product sales
with opportunity in periods of lower logistics costs and/or higher marketing
Brazilian grain storage capacity accounts for something around 131 million tons
(Brazilian Institute of Geography and Statistics - IBGE, 2016a), while the
grain (soybean and maize) production in the country is about 182 million tons
(IBGE, 2016b), implying a storage deficit of about 28%. Still in this line, it
is estimated that only 17% of that capacity is associated with on-farm storage
structures (IBGE, 2016b). Such configuration, added to Brazil’s continental
dimensions and its big production records (especially when considering the
external markets), implies some logistic bottlenecks such as long lines at land
and port terminals; accumulation of grains (“Open sky”) outside the storage
units, which has accounted for big amounts of post-harvest losses; high
logistic costs (related to an environment with lack of infrastructure and
storage capacity) to supply a very concentrated demand in some periods of the
1 shows a relationship between the evolution of grain production (soybean
and corn), total and relativestorage
capacity in Brazil. It is interesting to note that storage capacity has
accompanied the production of grain, but in a non-proportional way -
agricultural production has increased more than the growth of storage.
reference purpose, the logistic cost of soy from the main Brazilian state
producer, Mato Grosso, revolves around 30% of the product market price, going
to Santos Port . Specifically, for corn,
depending on the transportation corridor, it can reach very significant and
close levels to the marketing price.
1.2. About the Information System forGrain Storage
Information System for Grain Storage in Brazil (SIARMA) aims to identify the
prices of grain storage service in the main producing regions of the country,
more specifically: to perform research on key storage features, especially on
agricultural products (soybean and corn). SIARMA is linked to the University of
Sao Paulo (USP), College of Agriculture “Luiz de Queiroz” (ESALQ), specifically
at Group of Research and Extension in Agroindustrial Logistics (ESALQ-LOG).
gathering occurs annually and the report is available in free format at
ESALQ-LOG Group website. The contributors of the research also receive an
electronic report via email.
report presents the following information: storage price, composition storage
price, static storage capacity and relative storage capacity.
logistic strategy simulator was also created to reduce the information
asymmetry in the Brazilian agriculture, integrating the SIARMA with the Information
System for Freight Value (SIFRECA), which provides information on freight
prices used in many transportation corridors of agriculture products in Brazil.
This tool aims to support deciding whether to use or not to use the storage for
the product marketing, given the commercial conditions (price of grain) and
logistic conditions (transportation and storage costs). Besides, such tools evaluate
if the use of storage in the specified conditions brings economic benefits for
the analyzed period.
2. Methodology used
methodology used on SIARMA to create a store price index involves the following
a. Definition of the interviewed: In this step,
the goal is to identify the sample that will be interviewed, in order to meet
the main soy and corn producer’s region in the country. This selection
involves, specifically the main states that produces soy and corn in the
country. Then we select the cities with the highest production levels and
storage static capacity for each meso-region of the defined states. The last
one involves a selection of warehouses group (service providers) to be
interviewed based on the available warehouses registration bank of National
Supply Company - CONAB (2015)- the selection
on this registration bank occurs randomly in each selected city.
b. Interviews with the selected warehouses. In
this step, a group of researchers from ESALQ-LOG made interviews by telephone.
The research is done annually and involves around 100 interviewed agents. The
objective of the interview is to collect the following information:
Receiving and shipping flows.
Processing of the collected information. In
this step, it is made a statistical analysis of the information, especially
regarding storage price. In this case it is defined a confidence interval for
the data of each producer state, involving the average more/less one standard
deviation - values in this interval go into the analysis, the ones out of this
gap are excluded.
Indicators’ generation: Storage Rate and
Storage Rate consists of three types of
Fixed Rate:it refers
to the charge related to the use of warehouse, regardless of the storage
period. It includes the reception operations, pre-cleaning, drying (it was
adopted the standard of 17% of moisture), purge and shipping operations.
Variable Rate:it refers
to the rate of the storage operation for a period of 30 days, after the grace
Technical Loss:it refers
to the contractual tolerance related to the physical losses during storage
service, in %.
Storage Price refers to the price of storage service,
charged for a specific period in the contract. It is calculated according to
the previously reported rates, and it can be calculated by the equation (1):
s from fartm to
warehouse and from this to rate
〖PARM〗_in=〖TF〗_i+((n-c_i ))/30 〖TV〗_i+〖qt〗_i 〖pc〗_i
for n <c,〖TV〗_i=0
PARMi,nis the storage price for the regioni for n days stored (US$/t).
TFiis the fixed rate usedat warehouse in the
on the storage period (US$/t).
TViis the variable rate related to the operation
of storage in region i. usually, this rate is negotiated for thirty-day
contracts. In this case, it was decided to standardize the rate based on the
number of days stored.
nis the number of days the grain get stored.
cis the number of days of the grace period.
qtiis the technical loss (%).
pciis the price of grain (US$/t).
Specifically for the development of the
logistic strategy simulator, it was structured the following set of
price indicators: originating from linear regressions of the freight price
according to the distance for each month and region analyzed in Brazil, using
information available at SIFRECA (2015).
of grain storage levels for the meso-region interested producer: Statistic
originated from CONAB (2015).
storage indicators according to the numbers of days stored: SIARMA (2015).
marketing indicators according to time: Center for Advanced Studies on Applied
Economics - CEPEA (2015).
statistics by port according to time: Secretariat of Foreign Trade, part of
Ministry of Development, Industry and Foreign Trade-MDIC/SECEX (2015).
The simulator involves comparing and
commercializing the analyzed grain in the month of its production, or storing
it for a posteriorimarketing, taking into consideration the marketing prices,
transportation and storage prices in force at the time. This way it is possible
to: (i) evaluate if the storage in fact brings economic benefits and (ii)
indicate the optimum situation to maximize the product net revenue, defined by
the equation (2).
ENRhp is the expected net revenue from the sale in
the period p of the product harvested
in the period h (US$/t).
MPpis the market price in the period p
TPpis the transportation cost in the period p
including flows from farm to warehouse and from this to the port (US$/t).
SChpis the cost of storage from the harvesting
up to the marketing periodp (US$/t).
The economic benefit of grain storage in Brazil is reached when the
expected net revenue obtained in the situation where the grain harvested in the
and marketed in the period p is higher than the expected net revenue in the
commercialization of the grain in the harvest period h (without storage), as specified by
Condition for the economic benefit of storage:
ENRhis the expected net revenue from the sale of
the product harvested in the period h
The SIARMA report is available
in “PDF” and the logistic strategy simulator in electronic worksheet.
3. Obtained Results
The first set of results generated by SIARMA is the coefficient
indicator of the storage rate for storage price calculation, using the equation
The Tables 1 and 2 shows the indicators
of average parameters for storage fee for soybean and corn in selected producer
states in Brazil, respectively.
It is interesting to note a high correlation between the level of grain
production in the producing regions and the storage capacity in Brazil, as
shown in Figure 2.
Regarding the logistic strategic simulator, the results occur according
to the definition of the parameters to be evaluated, involving: (i) production
region; (ii) transportation corridors (port), (iii) harvest; (iv) marketing
period; and, (v) distance between farm and warehouse.
The examples of the generated results were programmed for the following
Origin: Meso-region of Sorriso (Mato
Transportation Corridor: Santos Port
Marketing Period: June/2015.
Road distance from the farm to the
warehouse: 50 kilometers.
Figure 3 shows the
storage price indicators as a function of storage period (US$/t and US$/t.day)
as an example there is the state of Mato Grosso for soybean. In this situation,
for each day stored, the storage price for the producer is enhanced in
approximately US$ 0.04 per ton.
The strategy selected for the soybean harvest in March and the commercialization
in June, incurs in expected net revenue of US$ 231.11 per ton (equivalent to
69.33% of the gross revenue, which means, from the marketing price), taking
into account soymarketing price and transportation price in June, besides the
storage costs between March and June. Figure 4
presents the impact of logistic costs on soybean farmers' revenue for the
Figure5 presents the
storage viability analysis for the selected strategy, involving the
optimization of the expected net revenue of the soybean farmer. In this
context, in case the producer had commercialized the soy on the same month of
the harvest (March) his expected net revenue would be around US$ 253.62 per ton
(opportunity cost). With the use of storage and marketing in subsequent months,
the expected net revenue is lower than the opportunity cost. For the selected
marketing strategy in June, the producer stopped making US$ 19.21 per ton,which
means, the storage formation did not bring any economic benefit.
SIARMA seeks to identify storage service prices of soy and corn in the
main regions of Brazil,and has performed successful results.Besides from being animportant
system in the contribution of the reduction of asymmetric information in the
market, and in helping the decision-making at the strategic, tactical and
operational levels for both the private and public sectors, based on the
integrated analysis tool of the commercialization and logistic market (SIARMA
and SIFRECA integration).As well as secondary statistics for valuation and stock
management, specially related to the quantity of the benefits (or not) on the
formation of soy and corn stocks- given the highly competitive structure of the
agricultural and logistic commodities market.
In Brazil, there are official providers of grain stocks. The first is a
National Company of Food Supply, so-called CONAB.
CONAB releases information of public and private stocks. In the case of
private, they are included coffee and rice. The public stocks involve various
products such as soybean, corn, wheat, among others. The types of information
provided are volume, spatial distribution and segment of storage in state
level. The method consists of a questionnaire applied by post or email to
register agents at the public information system of CONAB.The frequency is
The second provider is ABIOVE - Brazilian Association of Vegetable Oil
Industries, specific for soy complex. ABIOVE releases
information of soybean, soymeal and soy oil private stocks for a national
level. ABIOVE performs a survey about the soybean volume used by companies with
activities in the soybean industry. The information is published monthly.
5. Success Achievement and Issues for Further Research
SIARMA’s next steps involve: (i) Expansion of the survey of storage
prices for other agricultural products in the country; (ii) Identification of
the turns number of the warehouses, evaluated to estimate the level of annual
inventory formed in different producing regions; (iii) Collection of inventory
information at the level of railway, waterway and port terminals; (iv) Cost
structure for implementation of the various types of warehouses in the country;
and (v) Structuring mathematical models to identify and recommend the optimal
location of new warehouse facilities in the country.
Figure 1: Evolution of
storage capacity (total and relative) and grains production in Brazil. Source:
developed from IBGE (2015a)  and IBGE (2015b) .
Figure 2: Correlation
between storage capacity and grain production by meso-region level. Source:
developed from IBGE (2015a)  and IBGE (2015b) .
Figure 3: Storage Price
as a function of storage period (US$/t and US$/t.day) for soybean - Mato Grosso
state. Source: SIARMA (2015) .
Figure 4: Impacts of
logistic costs on soybean farmers' revenue for the selected strategy
(simulation) - Mato Grosso state. Source: SIARMA (2015) .
Figure 5: Storage
viability analysis: optimization of the expected net revenue of the soybean
farmer. Example for Mato Grosso state. Source: SIARMA (2015) .
IBGE (2015a) Brazilian Institute of
Geography and Statistics. SIDRA: Produçãoagrícola municipal.
IBGE (2015b) Brazilian Institute of
Geography and Statistics. SIDRA: Pesquisa de Estoques.
ESALQ-LOG (2015) Group of Research
and Extension in Agroindustrial Logistics (ESALQ-LOG). Logistics
strategies simulador (SIFRECA and SIARMA integrated tool).
CONAB (2015) National Supply
Company. Sistema de Cadastro Nacional de
SIFRECA (2015) Information System for
Freight Values. Group of Research and Extension in Agroindustrial Logistics
CONAB (2015) National Supply
Company. Sistema de Cadastro Nacional de Unidades Armazenadoras.
SIARMA (2015) Information System for
Grain Storage in Brazil. Group of Research and Extension in Agroindustrial Logistics
CEPEA (2015) Center for Advanced Studies
on Applied Economics. Soybean Price Index.
SECEX/MDIC (2015) Secretariat of Foreign
Trade (2015) at Ministeryof Development, Industry and Foreign Trade.
Sistema AliceWeb - Estatísticas de exportação.
ABIOVE (2016) Brazilian Association
of Vegetable Oil Industries. Statistics.