RISKS AND RETURNS IN STRAWBERRY, RASPBERRY AND CHERRY PRODUCTION WITH VARIOUS METHODS

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RISKS AND RETURNS IN STRAWBERRY, RASPBERRY AND CHERRY PRODUCTION WITH VARIOUS METHODS

Helma Jirgena

¹

, Juris Hazners

²

, Edite Kaufmane

³

, Sarmite Strautina

⁴

, Daina Feldmane

⁵

, Mara Skrivele

⁶

Horticultural production in Latvia has always been subject to numerous and diverse risks similar to other branches of crop plant production in Latvia. On the other hand, the climate of Latvia is favourable for plant crop growing but the value of production depends on climatic condition as well as field management and competence of the farmers. The markets of inputs used in strawberry, raspberry, and cherry farming have a direct impact on risks through unexpected rise in prices. Similarly, returns from horticultural outputs are affected by high volatility of fresh farm produce markets. Besides that, growers face the inevitable yield risks induced by adverse weather conditions, pests, and diseases.

There are a few systems used in production of strawberries, raspberries, and cherries - extensive and intensive growing both in open and covered areas. These methods vary by the level of risks and necessary investments. The production of berries and stone fruit in areas covered by polyethylene tunnels is expanding. The tunnel method of production provides better climatic conditions and reduces the damage by pests and diseases, thus, contributing to a longer and more predictable shelf life of the fruit. Production in tunnels extend the harvest season. High tunnels, in turn, can advance harvest dates earlier. Beyond the normal season, there is less competition and producer prices can be set higher. The aim of the study is the assessment of general risks in strawberry, raspberry, and cherry production, risks in production with various methods at farm level and evaluation of the tradeoffs among farming risks and expected returns.

Keywords: semi quantitative risk evaluation, strawberry, raspberry, cherry, returns.

JEL classification: Q16

Introduction

Horticultural production in Latvia has always been subject to numerous and diverse risks. In the past decades, financial vulnerability of farmers in the sector has increased due to market pressures, lack of local processing demand, low producer prices, and reduced profits. The markets of inputs used in strawberry, raspberry, and cherry farming have a direct impact on risks through unexpected rise in prices.

Similarly, returns from horticultural outputs are affected by high volatility of fresh farm produce markets. Besides that, growers face the inevitable yield risks induced by adverse weather conditions, pests, and diseases. These risks usually determine production in ways that are beyond the control of the farmers. Many risks are correlated. Input and output prices may be positively correlated. At the same time, production volumes and output prices are often negatively correlated mainly at aggregate level. Some risks are catastrophic because

___________________________

1Dr.oec, assoc. prof., University College of Economics and Culture; Director, Institute of Economics, Latvian Academy of Science Research fields: regional development, management, entrepreneurship

Mailing address: Akademijas laukums 1, Riga, LV-1050, Latvia E-mail: [email protected]

2MBA, MMath, researcher, Latvian State Institute of Agrarian Economics Research fields: international trade, risk management

Mailing address: Struktoru iela 14, Riga, LV-1039, Latvia E-mail: [email protected]

3Dr.biol., leading researcher, Latvia State Institute of Fruit-Growing

Research fields: integrated horticulture, technology transfer, product development, plant protection, risk management Mailing address: Graudu iela 1 Dobele, LV-3701, Latvia

E-mail: [email protected]

4Dr.biol., leading researcher, Latvia State Institute of Fruit-Growing Research fields: plant genetics, product development, sustainable production Mailing address: Graudu iela 1 Dobele, LV-3701, Latvia

5Dr.agr., researcher, Latvia State Institute of Fruit-Growing

Research fields: plant genetics, product development, sustainable production Mailing address: Graudu iela 1 Dobele, LV-3701, Latvia

6Dr.agr., leading researcher, Latvia State Institute of Fruit-Growing E-mail: [email protected]

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their occurrence is very unlikely but their damage can be disastrous. The main climate related risks in berry and stone fruit farming are hail, frost, torrential rainfalls, and strong winds. Lowering of quality also is an important factor besides the loss of production volumes. As these risks depend strongly on local circumstances, their overall assessment is difficult due to lack of reliable historical weather records. There are a few systems used in production of strawberries, raspberries, and cherries - extensive and intensive growing both in open and covered areas. These methods vary by the level of risks and necessary investments. The production of berries and stone fruit in areas covered by polyethylene tunnels is expanding.

The tunnel method of production provides better climatic conditions and reduces the damage by pests and diseases, thus, contributing to a longer and more predictable shelf life of the fruit. Production in tunnels extend the harvest season. High tunnels, in turn, can advance harvest dates earlier. Beyond the normal season, there is less competition, and producer prices can be set higher. Eleven production methods of strawberry, raspberry and cherry production are examined in the paper - extensive strawberry production with minimum investments in open areas, intensive strawberry production in open areas, strawberry production in covered areas, strawberry production in tunnels, summer-fruiting raspberry production in open areas, summer-fruiting raspberry production in Haygrove tunnels, summer-fruiting raspberry production in FVG tunnels, autumn-fruiting raspberry production in open areas, autumn-fruiting raspberry production in Haygrove tunnels, cherry production in open areas, and cherry production in covered areas. Risk management is the process of gaining greater control over the risks and financial returns for the particular farming method. It requires evaluating the tradeoffs among the risks and expected returns.

The additional costs in covers and tunnels have to be covered by gains in yields, quality and producer prices to justify the planned investments. Financing of relatively large investments in covers or tunnels may prove difficult if investment costs are high in relation to the farm’s financial viability. As stated by the OECD (2009), investments in farming production assets are usually used over several years. There is rather long gestation period before revenues are produced. The purchase of equipment requires a large lump-sum initial payment compared with the annual cash flow generated by the investment. The invested capital only amortises over a period of several years. Revenues from sales of the harvest for several years are rather low before reaching the planned level. At the same time, annual expenditures accrue during the immaturity period.

The risks associated by the investment depend upon the size of the investment relative to farming revenues.

Research objectives. The aim of the study is the assessment of general risks in strawberry, raspberry, and cherry production; risks in production with various methods at farm level; and evaluation of the tradeoffs among farming risks and expected returns.

Quantitative assessment of agricultural risk. The previous research on farm income variability in a number of countries has focused primarily on output price risk and production or yield risk. Both of these risks are generally perceived as risks that profoundly affect the financial well- being of the farmer. The input price risk has received much less attention because it tends to exhibit less variability over time; although, sometimes the volatility of input prices is high. The usually applied agricultural risk analyses are based on historical series of yield or price data. These historical data typically must be analysed to account for predictable trends and cycles. The time trend typically is capturing adjustments in yield potential through time. Likewise, price risk is often measured by using historical series of price data.

Variations of yields and correlations between producer prices and yields are indicators that can be used to evaluate the risk exposure of farmers in particular sector of the horticulture.

In general, viability of a particular production method in horticulture can be assessed by confirming the following inequality holds true:

, (1) where

EI - input expenditures;

OP - unit producer price;

OV - output volume (yield).

Therefore, the main production risks are input risks, producer price risks, and yield risks. The level of these risks has to be considered with respect to share of the horticultural production in farms’ whole operations and relative size of necessary investments.

Semi-quantitative risk evaluation. The most widely accepted formula for risk evaluation is Composite Risk Index (CRI) which is obtained by multiplying risk severity expressed in points according to ten point scale by probability of risk occurrence. While risk severity is evaluated by experts, probabilities of risk occurrence are obtained either by expert opinion or using statistical methods.

Anderson and Dillon (1992) suggested probabilities of risk occurrence should be assessed by semi-quantitative scale instead of linear scale with proportional distribution of probabilities. Risks with the CRI values below 0.04 are considered minimal, and their monitoring is unnecessary.

Risks with the CRI values in range from 0.04 to 0.4 are considered minor, and they are managed by monitoring. Risks with the CRI values in range from 0.4 to 1.2 are considered moderate, and their management requires actions. Risks with the CRI values in range from 1.2 to 4 are considered major, and their management involves immediate actions. Risks with the CRI values over 4 are considered catastrophic, and their management is considered almost impossible. Actions associated with the respective CRI values, risk severities, and probabilities are provided in Table 1.

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Methodology and results

Yield variation and correlation between yields and producer prices. General risks in the three crop production associated with the loss in expected yields along with the output price risks are evaluated in the aggregated national level by the methodology proposed by the OECD (2009). First, the yield variation coefficients in a set of producer countries over the certain period of time are calculated by dividing the standard deviation in array of the yield data with the simple average. Relatively lower value of the computed coefficient indicates fewer risks associated with the yield loss. Second, the correlation coefficients between the yields and output prices in a set of producer countries over the certain period of time are calculated. A negative coefficient indicates the higher possibility that losses in output volumes would be entirely or partly compensated by higher producer prices. Therefore, the

output price risks are lower. Mapping these two coefficients on a two-dimensional diagram enables the evaluation of the risk level of the particular crop in a set of countries. Mapping of coefficients of strawberry yield variations and correlation coefficients between the yields and producer prices in selected countries over the period from 1995 to 2011 are shown in Figure 1.

In countries positioned in a lower left quarter in a map, situation for the production planning is the most favourable. In turn, position in an upper right quarter points to unfavourable situation. In neighbouring Estonia, the situation is favourable as the country is positioned in a lower left quarter. Lithuania, on the contrary, is positioned in an upper right quarter. Important producer countries, such as the USA, Mexico, and Turkey have high correlation between yields and producer prices but low yield variations. In Latvia, correlation between yields and producer prices can be considered moderately negative. This Table 1. Semi-quantitative Composite Risk Index table

Severity Probability CRI Actions

Catastrophic >8 Very likely >0.5 >4 Emergency situation

Major >6<8 Highly possible >0.2<0.5 >1.2<4 Immediate action Moderate >4<6 Moderately possible >0.1<0.2 >0.4<1.2 Action

Minor >2<4 Unlikely >0.02<0.1 >0.04<0.4 Monitoring

Low <2 Improbable <0.02 <0.04 -

Source: Anderson and Dillon, 1992

Canada

Italy France

New Zealand

Japan Spain Poland

Switzerland Cyprus

Belgium Brazil Palestine

Norway Paraguay

Finland Tunisia

Croatia Iran

Austria

Greece Macedonia

Argentina Estonia

Kyrgizstan

Bulgaria Czech Republic

Hungary

South Africa Kazakhstan

Peru

Portugal Korea

Sweden Ireland

Bolivia

Russia Germany

Serbia Luxembourg

Holland Colombia

USA Moldova

Slovenia

Romania Mexico

Israel Bosnia and Herzegovina

Chile Morocco

Malta

China Latvia

Denmark Australia Venezuela

Slovakia

Ukraine Lebanon

TurkeyCosta Rica United Kingdom

Belarus Egypt

JordanLithuania

Ecuador Kenya

0 0.2 0.4 0.6 0.8 1 1.2

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Yield variation coefficient

Correlation between yields and producer prices Source: FAO, 2012

Fig. 1. Strawberry yield variations and correlation between yields and producer prices

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means producers can expect the higher prices would offset lower yields. At the same time, yield variation is very high.

The most favourable situation for production planning is in Canada.

Mapping of coefficients of raspberry yield variations and correlation coefficients between the yields and producer prices in selected countries over the period from 1995 to 2011 is shown in Figure 2.

In Latvia, correlation between yields and producer prices is positive. This points to the lack of an opportunity to offset possible yield losses with higher unit price. Similarly, yield variation is higher than in major producing countries.

Nevertheless, there are only minor differences for coefficients in Latvia and major producer countries, such as Serbia and Bulgaria. The most favourable situation for production planning is in Germany, France, Canada, Croatia, and the United Kingdom. In Estonia, situation is highly favourable.

Mapping of coefficients of sweet cherry yield variations and correlation coefficients between the yields and producer prices in selected countries over the period from 1995 to 2011 is shown in Figure 3.

In Latvia, correlation between yields and producer prices is markedly negative. Therefore, the output losses can be offset by higher unit price. While the yield variation in Latvia is only slightly above the simple average in all selected countries, most countries have less pronounced yield variations. The most favourable situation for production planning is in France, Spain, Germany, and Argentina. In Estonia, yield variation is

relatively high, while correlation between yields and producer prices is markedly negative. In Lithuania, yield variation is very high, while negative correlation between yields and producer prices is less pronounced.

Input risks. The input risks are assessed by evaluation of the possibility of significant input price increases over the previous year. According to the commonly accepted “rule of thumb”, increases in a particular variable are considered significant if they exceed the 15% level. The data for the particular input price over the certain time period are assumed to be normally distributed. Probabilities of significant price increase in the next year are calculated for all inputs. Severities of input risks are evaluated as shares of particular input in total expenditures.

Composite Risk Indexes for every input line are calculated by multiplying computed probabilities of significant price increase to risk severities. Agricultural input price arrays were formed from the data on gross margins for inputs provided by Latvian Rural Advisory and Training centre (LLKC) for the period from 1997 to 2012. The government statistics by the Central Statistical Bureau are used on such general inputs as construction, fuel, electricity, gas, plastics, wages and social tax. Risk severities for particular input in eleven production methods of three crops are calculated as share of input in total input costs multiplied by 10. Composite Risk Index for particular input is calculated as product of risk severity and respective probability of occurrence. After calculating all composite input risk indexes, an aggregate index is calculated by adding up all risks for the production method.

Greece France

Canada Croatia

United Kingdom Kyrgizstan

Germany Slovakia

Hungary New Zealand

Denmark

Russia Estonia Moldova

Holland Australia Bulgaria

Romania

Finland

Israel USA

Poland Latvia

Norway

Switzerland Ukraine Czech Republic

Italy

Sweden Bosnia and Herzegovina Mexico

Spain Azerbeidjan

Portugal

Serbia

0 0.2 0.4 0.6 0.8 1 1.2 1.4

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Fig. 2. Raspberry yield variations and correlation between yields and producer prices

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France

Argentina Spain

Peru

Switzerland

Japan Germany Cyprus

Ukraine Czech Republic

Poland Slovakia

Belgium

Kazakhstan Israel

Norway Romania Bulgaria

South Africa

Russia Jordan Chile

Lebanon

Bolivia Croatia

Greece Moldova

Slovenia Latvia

Algeria

Italy Serbia United Kingdom

Portugal

Iran Macedonia Estonia

New Zealand

Pakistan Turkey

Azerbeidjan USA

Armenia

Morocco Sweden

Tunisia Canada Albania Kyrgizstan

Tadjikistan Holland

Bosnia and Herzegovina Austria

AustraliaIndia Georgia Hungary

China Lithuania

0 0.2 0.4 0.6 0.8 1 1.2 1.4

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Fig. 3. Cherry yield variations and correlation between yields and producer prices

Composite indexes for the main input risks in strawberry production with various methods along with the respective aggregate indexes are provided in Table 2.

In strawberry production in open area either with minimum investment or intensively, all input risks are minor or lower, and risk management does not require actions. The highest input risk is associated with unexpected surge in packaging costs. Similarly, in strawberry production under cover, all

input risks are minor or lower, and risk management does not require actions. The highest input risk is associated with possible rise in wages. In strawberry production in tunnels, all risks but tunnel construction costs are minor or lower, and risk management does not require actions. Risks associated with rise in tunnel construction costs require actions. Cost reduction measures should be considered. In general, the use of covers or tunnels significantly reduces aggregate input risks.

Table 2. Composite input risk indexes in strawberry production Inputs

Open area (minimum

investment) Open area Cover Tunnel

Composite Risk Index

Wages 0.10 0.11 0.17 0.07

Pesticides 0.10

Fertilisers 0.24 0.19

Manual weed pulling 0.20 0.16

Straw 0.08 0.05

Social tax 0.04

Plants 0.13 0.11 0.08

Planting 0.08

Packaging 0.29 0.33 0.18 0.08

Tunnel construction 0.40

Aggregate index 1.08 1.17 0.68 0.69

Source: expert evaluation

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Composite indexes for main input risks in raspberry production with various methods along with the respective aggregate indexes are provided in Table 3.

In summer-fruiting raspberry production in open area, all input risks but plant cost increase are minor or lower, and risk management does not require actions. Cost reduction measures should be considered for plant purchasing risks. In summer-fruiting raspberry production in Haygrove tunnels, all input risks but tunnel cost increase are minor or lower, and risk management does not require actions. Cost reduction measures should be considered for tunnel purchasing risks. In summer- fruiting raspberry production in FVG tunnels, all input risks are minor or lower, and risk management does not require actions. In autumn-fruiting raspberry production in open area, all input risks but plant cost increase are minor or lower, and risk management does not require actions. Cost reduction measures should be considered for plant purchasing risks. In autumn-fruiting raspberry production in Haygrove tunnels, all input risks but tunnel cost increase are minor or lower, and risk management does not require actions. Cost reduction measures should be considered for tunnel purchasing risks.

The differences between aggregate input risk indexes either for summer-fruiting or autumn fruiting raspberries for production in open area and in Haygrove tunnels are minor. In general,

the use of FVG tunnels significantly reduces aggregate input risks.

Composite indexes for main input risks in cherry production with various methods along with the respective aggregate indexes are provided in Table 4.

In cherry production in open area, all input risks are minor or lower, and risk management does not require actions.

The highest input risk is associated with unexpected rise in pesticide costs. In cherry production under cover, all input risks but cover purchase and installation cost increase are minor or lower, and risk management does not require actions. Cover purchase and installation cost reduction measures should be considered for tunnel purchasing risks. In general, the use of covers increase the aggregate input risks in cherry production as the aggregate composite input risk index for production under cover is higher.

Yield risks. Yield risk probabilities of occurrence and risk severities are evaluated based upon the available historical climate records and by industry experts with long- term experience in production of strawberries, raspberries, and cherries with various methods in pilot orchards. Yield risks in strawberry production with various methods along with the probabilities of occurrence and risk severities are provided in Table 5.

Table 3. Composite input risk indexes in raspberry production Inputs

Summer-fruiting cultivars Autumn-fruiting cultivars Open area Haygrove tunnel FVG tunnel Open area Haygrove tunnel

Composite risk index

Wages 0.09 0.07 0.04

Pesticides 0.08 0.04

Tunnel costs 0.68 0.60

Plants 0.46 0.06 0.07 0.71 0.10

Packaging 0.12 0.08

Tractor rental 0.07

Tunnel construction 0.11

Aggregate index 0.88 0.85 0.31 0.96 0.81

Source: authors’ calculations

Table 4. Composite input risk indexes in cherry production

Inputs Open area Cover

Composite risk index

Wages 0.06 0.04

Pesticides 0.29 0.06

Mulch 0.06

Cover purchase and installation 0.52

Plants 0.07 0.04

Fence 0.05

Aggregate index 0.56 0.72

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Composite yield risk indexes for strawberry production are provided in Table 6.

For all four strawberry production methods, winterkill is a serious risk as the value of CRI exceeds 1.2. These risks require immediate actions, and insurance against winterkill losses would be appropriate. Pest risks are serious for open area and cover methods as the value of CRI exceeds 1.2. These risks require immediate actions by preventive use of pesticides.

Heavy rain and frost risks are serious for open area production methods as the value of CRI exceeds 1.2. These risks require immediate actions, and insurance against heavy rain and frost losses would be appropriate. Hail risks are major for open area production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against hail losses would be appropriate. For cover and tunnel production methods, frost risks are major as the value of CRI exceeds 0.4. These risks require actions, and insurance against frost losses would be

appropriate. For tunnel production methods, pest risks are major as the value of CRI exceeds 0.4. These risks require actions by preventive use of pesticides. For tunnel production methods, heavy rain risks are minor as the value of CRI does not exceed 0.4. These risks require only monitoring.

Risks in summer-fruiting raspberry production with various methods along with the probabilities of occurrence and risk severities are provided in Table 7.

Composite yield risk indexes for summer-fruiting raspberry production are provided in Table 8.

For all three summer-fruiting raspberry production methods, winterkill is a serious risk as the value of CRI exceeds 1.2. These risks require immediate actions, and insurance against winterkill losses would be appropriate.

Heavy rain and drought risks are serious for open area production methods as the value of CRI exceeds 1.2. These risks require immediate actions, and insurance against heavy Table 5. Probabilities and severities of yield risks in strawberry production

Risks Probability

Open area (minimum

Severity

Winterfrost damages 0.1 10.0 10.0 10.0 10.0

Early moderate frosts 1.0 1.8 1.8 0.0 0.0

Early severe frosts 0.4 8.5 8.5 2.0 2.0

Hail 0.1 9.0 9.0 9.0 0.0

Heavy rain 0.3 4.5 4.5 4.5 1.0

Pests 0.5 7.5 7.5 7.5 1.0

Table 6. Composite yield risk indexes in strawberry production

Risks Open area (minimum

Winterfrost damages 1.4 1.4 1.4 1.4

Early moderate frosts 1.8 1.8 0.0 0.0

Early severe frosts 3.4 3.4 0.8 0.8

Hail 0.9 0.9 0.9 0.0

Heavy rain 1.5 1.5 1.5 0.3

Pests 3.8 3.8 3.8 0.5

Table 7. Probabilities and severities of yield risks in summer-fruiting raspberry production

Risks Probability Open area Haygrove tunnel FVG tunnel

Severity

Severe winter frost damages 0.2 10.0 10.0 10.0

Moderate winter frost damages 0.3 4.5 4.5 4.5

Hail 0.1 9.0 0.0 0.0

Heavy rain 0.5 6.5 1.0 1.0

Drought in June 0.3 6.5 0.0 0.0

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rain and drought losses would be appropriate. Hail risks are major for open area production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against hail losses would be appropriate. Heavy rain risks are major for tunnel production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against heavy rain losses would be appropriate.

Risks in autumn-fruiting raspberry production with various methods along with the probabilities of occurrence and risk severities are provided in Table 9.

Composite yield risk indexes for summer-fruiting raspberry production are provided in Table 10.

For autumn-fruiting raspberry production in open area, late frost risks are catastrophic, as the value of CRI exceeds 4. These risks point to an emergency situation, and viability of this production method should be assessed.

Heavy rain and drought risks are serious for open area production method as the value of CRI exceeds 1.2.

These risks require immediate actions, and insurance against heavy rain and drought losses would be appropriate. Hail risks are major for open area production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against hail losses would be appropriate. Late frost

Table 8. Composite yield risk indexes in summer-fruiting raspberry production

Risks Open area Haygrove tunnel FVG tunnel

Severe winter frost damages 1.8 1.8 1.8

Moderate winter frost damages 1.5 1.5 1.5

Hail 0.9 0.0 0.0

Heavy rain 3.3 0.5 0.5

Drought in June 1.6 0.0 0.0

Table 9. Probabilities and severities of yield risks in autumn-fruiting raspberry production

Risks Probabilities Open area Haygrove tunnel

Frosts in September 0.5 6.3 0.0

Frosts in October 1.0 5.0 1.0

Hail 0.1 9.0 0.0

Drought in August 0.3 2.5 0.0

risks are major for tunnel production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against frost losses would be appropriate.

Probabilities and severities of yield risks in sweet cherry production are provided in Table 11.

The values of calculated Composite Risk Indexes for cherry production are provided in Table 12.

For cherry production in open area, bird damage risks are catastrophic as the value of CRI exceeds 4. These risks point to an emergency situation, and viability of this production method should be assessed. For both production methods, winterkill is a serious risk as the value of CRI exceeds 1.2. This risk requires immediate actions, and insurance against winterkill losses would be appropriate. For both production methods, pest risks are serious as the value of CRI exceeds 1.2. These risks require immediate actions by preventive use of pesticides. For production in open area, heavy rain and frosts are serious risks as the value of CRI exceeds 1.2. These risks require immediate actions, and insurance against heavy rain and frost losses would be appropriate. Hail risks are major for open area production methods as the value of CRI exceeds 0.4. These risks require actions, and insurance against hail losses would be Table 10. Composite yield risk indexes in autumn-fruiting raspberry production

Risks Open area Haygrove tunnel

Frosts in September 3.1 0.0

Frosts in October 5.0 1.0

Hail 0.9 0.0

Heavy rain 3.5 0.0

Drought in August 0.6 0.0

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Table 11. Probabilities and severities of yield risks in sweet cherry production

Risks Probabilities Open area Cover

Severity

Winter frost damages 0.2 9.0 9.0

Winter frost damages caused the plant death (Western European

and Canadian cultivars) 0.3 7.0 7.0

Early moderate frosts 1.0 2.0 0.0

Early severe frosts 0.2 2.5 1.3

Hail 0.1 9.0 0.0

Moderate rain 1.0 1.5 0.0

Pests 0.5 7.0 7.5

Bird damage 0.9 7.0 1.5

Table 12. Composite yield risk indexes in sweet cherry production

Risks Open area Cover

Winterkill 1.6 1.6

Winterkill (Western European and Canadian cultivars) 1.8 1.8

Early moderate frosts 2.0 0.0

Early severe frosts 0.6 0.3

Hail 0.9 0.0

Moderate rain 1.5 0.0

Heavy rain 2.3 0.3

Pests 3.5 3.9

Bird damage 6.3 1.4

appropriate. For cherry production in covered area, bird damage risks are serious as the value of CRI exceeds 1.2.

These risks require immediate actions by the use of additional side covers. For cherry production in covered area, frost and heavy rain risks are minor as the value of CRI does not exceed 0.4. These risks require only monitoring.

Price risks. The CRI indexes for producer prices are calculated using an array of annual averages. Prices are assumed to be normally distributed. Probabilities that price in the next year following the last year in the certain price array would not exceed the particular price from array are calculated. The possible severities of respective risks are calculated by dividing differences between the expected price and recorded price from array to expected price.

The obtained result is multiplied by 10 to get an index in points. For every recorded price, CRI is calculated by multiplying probabilities to severities. Final CRI is established as a maximum value in array of calculated CRI indexes.

Price risks, risk severities, and CRI are calculated using the FAO data on strawberry, raspberry and cherry producer prices for the period from 2000 to 2011. Prices provided by LVAI are used for 2012. For production in covered and tunnel areas, severity of price risks is adjusted lower

according to the expert recommendations. The adjustment is due to an option to extend the sales period off-season, thus, getting higher prices.

The values of calculated Composite Risk Indexes for producer prices are provided in Table 13.

Returns on investment. Gross profit is calculated by the equation

, (2) where

GP - Gross Profit;

TR - Total Revenues;

TE - Total Expenditures.

The return on investment is calculated by the equation , (3) where

ROI - Return on Investment;

GP - Gross Profit;

TI - Total Investment.

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Table 13. Composite Risk Indexes for strawberry, raspberry and cherry producer prices

Crop Open areas Covered and tunnel areas

Strawberries 0.89 0.17

Summer-fruiting raspberries 2.82 1.67

Autumn-fruiting raspberries 0.64 0.56

Cherries 2.77 1.08

Revenues, investments and expenditures over the period from year of the planting to the first year of maturation are taken into account. For strawberries and raspberries, period lasts three years. For cherries, period lasts four years. The calculated values for gross profit and returns on investment for eleven production methods in strawberry, raspberry, and cherry production are provided in Table 14.

Table 14. Returns on investment for various methods in strawberry, raspberry and cherry production

Production method Revenues Investments Expenditures Gross

profit ROI

Strawberries in open area extensively 12,177 11,666 15,972 -3,795 -33%

Strawberries in open area intensively 19,977 13,893 17,312 2,665 19%

Strawberries in open area with cover 35,177 23,102 25,943 9,234 40%

Strawberries in tunnel 104,209 81,866 97,250 6,959 9%

Summer-fruiting raspberries in open area 28,000 9,914 21,430 6,570 66%

Summer-fruiting raspberries in Haygrove

tunnel 130,460 62,745 91,168 39,292 63%

Summer-fruiting raspberries in FVG tunnel 139,560 82,059 99,837 39,723 48%

Autumn-fruiting raspberries in open area 41,380 13,441 30,533 10,847 81%

Autumn-fruiting raspberries in Haygrove

tunnel 174,750 67,147 85,642 89,108 133%

Cherries in open area 30,000 21,165 29,576 424 2%

Cherries in covered area 88,007 59,693 85,001 3,006 5%

Source: LVAI

In strawberry production in open area with minimum investments, aggregate expenditures exceed total revenues and investments provide no returns. Production in open area intensively, yields better returns on investment than production in tunnels. Production in open areas under cover provides the best returns on investment in strawberry production.

9

20.1 2.4

11.6 4.3

4.8

11.3 3.9

9.2

13 12.9

5%

2%

133%

81%

48%

63%

66%

9%

40%

19%

Cherries in covered area Cherries in open area Autumn-fruiting raspberries in Haygrove tunnel Autumn-fruiting raspberries in open area Summer-fruiting raspberries in FVG tunnel Summer-fruiting raspberries in Haygrove tunnel Summer-fruiting raspberries in open area Strawberries in tunnel Strawberries in open area with cover Strawberries in open area intensively Strawberries in open area extensively

Returns Risks

Source: LVAI, authors’ calculations

Fig. 4. Aggregate risks and returns on investment in strawberry, raspberry, and cherry production

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Both productions in open area and in Haygrove tunnel yield similarly high returns on investment for summer-fruiting raspberries. The returns on investment for production in FVG tunnel are somewhat lower.

For autumn-fruiting raspberries, production in Haygrove tunnel yields very high returns on investment. Returns on investment for production in open areas are somewhat lower.

For cherries, production under cover yields better returns on investment. However, both methods provide relatively low returns.

Aggregate risks and returns on investment. To compare various production methods taking both risks involved and expected returns on investment, aggregate Composite Risk Indexes for every production method are calculated by adding up input, yield, and price risk indexes. Aggregate indexes along with the expected returns are shown in Figure 4.

For strawberries, production in open area with minimum investments yields no returns, while risks are relatively high. Production in open area intensively also is associated with similar risks, while yielding moderate returns on investment. Production in open area with cover reduces risks and significantly improves returns on investment.

Production in tunnels significantly reduces risks, while returns on investment are moderately low.

Production of summer-fruiting raspberries yields high returns on investment both for growing in open areas and in Haygrove tunnels. However, the use of Haygrove tunnel provides twofold decline in risks. Benefits from slightly lower risks for production in FVG tunnel if compared with Haygrove tunnel might be insufficient to offset the lower returns on investment.

For autumn-fruiting raspberries, production in Haygrove tunnels yields very high returns on investment, while the risk level is very low. Growing in open areas also provides high returns, while risks are relatively high.

For cherries, production in covered areas yields slightly higher albeit relatively low returns on investment if compared with production in open areas. However, the twofold decline in risk level might be sufficient to adjust the investment in covers.

Conclusions

1. For strawberry production in general, the relationship between yield variations and correlation between yields and producer prices suggests moderately unfavourable situation in production planning.

2. Production of strawberries in open areas with minimum investments is associated with high risk, and provides no returns on investment.

3. High risks for intensive production of strawberries in open areas might be offset by higher returns on investment.

4. Covers substantially reduce risks in strawberry production, while yielding relatively high returns on investment.

5. For strawberry production in tunnels, relative risk levels are very low, while returns on investment are moderate.

6. For raspberry production in general, the relationship between yield variations and correlation between yields and producer prices suggests markedly unfavourable situation in production planning.

7. Production of raspberries in open areas yields very high returns on investment at high risk levels.

8. The use of tunnels substantially reduces risks in summer- fruiting raspberry production, while yielding high returns on investment.

9. For autumn-fruiting raspberries, production in tunnels yields very high returns on investment at very low risk level.

10. For cherry production in general, the relationship between yield variations and correlation between yields and producer prices suggests slightly unfavourable situation in production planning.

11. Returns on investment for cherry production are rather low both for open and covered areas.

12. The use of covers in cherry production provides twofold decline in risks. However, even the reduced risk levels should be considered high.

Bibliography

1. Anderson, J.R., Dillon J.L. (1992). Risk Analysis in Dryland Farming Systems. Farming Systems Management Series No 2, FAO, Rome.

2. CSB (2012). Latvijas Statistika. Retrieved: http://www.

csb.gov.lv/dati/statistikas-datubazes-28270.html.

3. FAO (2012). Faostat Domains. Retrieved: http://faostat3.

fao.org/faostat-gateway/go/to/download/T/TM/E.

4. LLKC (2013). Gross Margins in Agriculture. Retrieved:

www.llkc.lv/en/biblioteka/bruto-segumi‎.

5. LVAI (2013). Unpublished materials.

6. OECD (2009). Managing Risk in Agriculture: a Holistic Approach, ISBN- 978-92-64-07530-6.