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BY 4.0 license Open Access Published by De Gruyter Open Access January 2, 2023

The impact of COVID-19 pandemic on business risks and potato commercial model

  • Pujiharto Pujiharto EMAIL logo and Sri Wahyuni
From the journal Open Agriculture

Abstract

This study was aimed (1) to analyze the productivity, cost, and income of potato farming; (2) to analyze the risk of potato farming; and (3) to analyze the potato trade system at the level before and during COVID-19 pandemic. This study used a descriptive-quantitative research type. It was conducted in Banjarnegara Regency, Jawa Tengah Province, Indonesia. The data were collected through surveys, observations, and Focus Group Discussions. The unit of analysis is the farmers who plant potatoes. Data analysis was done descriptively. The results showed that there is no difference between the two marketing channels before and during pandemic. There are two channels of the trading system, namely farmer–collector–traders–wholesaler–exporter partners and farmer–collector–traders–wholesalers–retailers. However, the trading model maximizes the Agribusiness Sub Terminal (AST) as a potato trading agent that can provide direct price information, attract traders, and facilitate transactions and trading contacts. The trading model allows potato trading agents to provide direct price information, attract traders, and facilitate transactions and trading contacts. The implication of this study is to anticipate productivity risk and potato farming income risk through the AST function. This study contributes to the condition of farming before and during COVID-19 pandemic by comparing differences in productivity, costs, income, productivity risk, and income risk as well as the potato grading model.

1 Introduction

COVID-19 is a global health and economic crisis that significantly impacts the society [1,2]. Since COVID-19 in Indonesia became a national epidemic, the government issued PP No. 21 of 2020 regarding the Large-Scale Social Restriction policy, as the government’s strategy to prevent the coronavirus from spreading wider. However, it has resulted a limited demand and decline in agricultural products [3,4]. The agri-food sector is not separated from this phenomenon, playing an important role in the magnitude of pandemic’s impact [5]. The Large-Scale Social Restriction is quite disruptive for the supply and delays of the potato commodities’ distribution. The impacts for distribution being less smooth, and stocks between regions are uneven since some regions have experienced a deficit and some excess experience production. In addition, the pandemic has resulted in several difficulties for potato farmers, such as a slowing supply chain due to disrupted agricultural logistics distribution. The impacts can be seen on the supply and demand for potato commodities and indirectly through decreased purchasing power and capacity to produce and distribute. The pandemic also affects the risk of farming, distribution, and trading patterns of potatoes from the farmer level to the consumer [6].

The existence of COVID-19 greatly affects the distribution of production inputs in potato farming, which makes it not smooth and constrained due to the implementation of the lockdown. This condition greatly affects productivity, costs, income of potato farming, productivity risk, income risk, marketing channel pattern, and potato trading system model. So it is important to compare variables before and during the COVID-19 pandemic. This study was aimed to: (1) analyze potato productivity, costs, and income of potato farming; (2) analyze the risk of potato farming; and (3) analyze the potato trade system at the farmer level before and during COVID-19 pandemic. Thus, reviewing the potato trading system model at the farmer level is necessary. The objectives of this research can be answered through the application of the methodology using the Soekartawi and Hernanto formula. Farm income is obtained from the total revenue minus the total cost [7], while the calculation of farming risk consists of production risk, cost risk, and income risk [8].

This study contributes to the condition of farming before and during COVID-19 pandemic by comparing differences in productivity, costs, income, productivity risk, and income risk as well as the potato grading model. By knowing this, the impact of pandemic turns out to be more affecting the distribution of inputs or agricultural production facilities that are hampered; so it affects the variables mentioned above. The originality of this study is that there is no study that examines the impact of COVID-19 on productivity, farming costs, income, productivity risk, income risk, and the potato trading system model.

2 Research method

The basic method used in this study is the quantitative method-numbers for the analysis of productivity–cost–income–productivity risk and income risk, while descriptive qualitative – to see channel patterns and marketing models and samples taken by saturated sampling method or census – all existing populations are taken all. The first analysis in this study is the production data (productivity); then, the costs incurred so the income of potato farmers can be calculated with Soekartawi formula (equation (1)). The potato trading system and models before and during the COVID-19 pandemic were analyzed descriptively and qualitatively. The data collection used survey techniques. The location was determined purposively in Banjarnegara Regency, considering that the district is the potato production center in Jawa Tengah Province. Furthermore, three sub-districts with the largest production contribution were selected: Batur, Pejawaran, and Wanayasa sub-districts. The sampling process was taken by sampling method (cencus). The samples are 120 farmers, 9 collectors, 9 wholesalers, 9 retailers, 1 exporter, and 1 Agribusiness Sub Terminal (AST). The data collection techniques were carried out by observation and interviews.

(1) I = TR EC ,

where I is the potato farming income (IDR), TR is the total revenue (IDR), and EC is the explicit cost/costs actually incurred (IDR).

The risk analysis of potato farming, including production, cost, and income, was analyzed by using the coefficient of variation (CV). The CV measures the relative risk obtained by dividing standard deviation by the expected value [9]. Mathematically, it can be formulated as equations (2)–(4) [8]. This method uses production, cost, and income data obtained from potato farming. This method is to answer the second goal.

(2) Production risk CV = σ Y ̅ ,

(3) Cost risk CV = σ C ,

(4) Income risk CV = σ I ̅ ,

where CV is the coefficient of variation, σ is the standard deviation, Y ̅ is the average production (kg), C ̅ is the average cost (IDR), and I ̅ is the average income (IDR).

Afterward, the descriptive analysis was carried out by tracing the potato trading chain from the producer point to final consumer to answer the third objective. Then, the potato trading system model was rearranged during COVID-19 pandemic to answer the fourth goal.

3 Result and discussion

3.1 Productivity, cost, and income of potato farming

The results showed that potato productivity at the farmer level was divided into the ABC class, the seed class, and the rindil class. The potato productivity by class is shown in Table 1.

Table 1

Average potato productivity by class

Class Productivity (kg/ha)
Before pandemic During pandemic
ABC 12761.28 12579.98
Seed 1518.00 1367.34
Rindil 716.47 454.32
Total 14995.75 14401.63

Table 1 shows that the potato productivity in all classes has decreased during COVID-19 pandemic. During pandemic, access to factory production facilities was hampered, resulting in decreased productivity [10]. The previous study has shown that the impact of COVID-19 resulted in a decrease in agricultural yields in all US regions ranging from 1.18 to 7.14% of total production [11]. The cost of potato farming per hectare in the location generally includes variable costs. At the merchant level, potato class ABC is separated into class A (4–9 number of tubers of the plant (knol)/kg), class B (10–14 knol/kg), and class C (15–25 knol/kg); each sold at different prices. Meanwhile, the price of seed and rindil grade potatoes was lower than the ABC class. In contrast, the fixed costs incurred are relatively small, almost all potato farmers own their land, so there is no land rental fee. Table 2 shows the average cost of potato farming broken down by production factors.

Table 2

Average cost of potato farming per hectare

Business costs Before pandemic During pandemic
Value (million IDR) Percent Value (million IDR) Percent
Manpower 11954.2 16.40 12948.1 17.48
Organic fertilizer 12110.0 16.61 13540.1 18.28
Mulch 4658.3 6.39 4775.3 6.45
Seeds 22125.9 30.35 21733.7 29.34
NPK fertilizer 2046.3 2.81 2187.9 2.95
Plant tools 2605.8 3.57 2745.7 3.71
Fungicides 13308.6 18.26 12458.9 16.82
Insecticide 4082.7 5.60 3701.9 5.00
Total 72892.1 100.00 74072.0 100.00

The cost structure of potato production per hectare before and during COVID-19 pandemic underwent several changes, the total cost increased, and inputs that experienced an increase were labor, organic fertilizer, mulch, NPK fertilizer, and stakes. Meanwhile, the lower input costs are seeds, fungicides, and insecticides. Agriculture has a positive spillover effect on the skilled labor market for simple tasks [12]. The labor required in potato farming per hectare is average as 225.88 working days, starting from land preparation, making beds, installing silver, and black mulch, making planting holes, planting potato seeds, installing stakes, tying potato plants to stakes, fertilizing, weeding, controlling pests and diseases, and harvesting and transporting crops to the roadside. The wages of male and female workers in the study area are equal from IDR 50,000 up to IDR 60,000 with an average as IDR 57,324. Labor costs occupy 17.48% of the total cost of potato farming per hectare.

The organic fertilizer used is a mixture of chicken manure and rice husks. This fertilizer is needed to maintain soil fertility due to rainfall and sloping land topography due to surface erosion. The use of various doses of organic fertilizers in combination with mineral fertilizers can increase potato yields and phosphorus and potassium contents [13]. Table 2 shows the use of organic fertilizers ranked third in production costs and increased during the pandemic. The average cost of organic fertilizer per hectare is 18.28% from the total cost of potato farming per hectare. The average needs for organic fertilizer per hectare in potato farming are 34156.38 kg or 14,156 tons, with an average price as IDR 402.65/kg. While the NPK fertilizer used is very small, below 3%, NPK fertilizer was a fertilizer that affected yield by increasing available nitrogen and reducing soil moistures, producing similar quality and taste tubers, and financially profitable [14]. In addition, NPK fertilizer can intensify plant photosynthesis, resulting in higher carbohydrate formation [15].

Silver black mulch is used in potato farming to protect the mounds from weed growth and reduce surface erosion after fertilization. Treatment of mound processing with mulch can increase soil moisture at the quadratic stage, encouraging increased photosynthesis and potato yields [16]. Planting with full mulch can improve the soil environment and increase potato tuber yield [17]. The average price of silver black mulch is IDR 450816.23/roll. The size of one roller is 100 m × 0.9 m. The average requirement per hectare is 10.60 rolls; so the average mulch cost is under 7% of the total. The stake is installed after planting the seeds; when the potato plant has started to grow tall, the potato plant stem is tied to the stake, so it does not fall. The average stake requirement per hectare is 35673.29 sticks, with an average cost of under 4%.

In potato production, the implementation of crop protection measures and the use of quality seeds are important aspects that affect the technical efficiency of potato farmers. Seeds occupy the first position in the cost of production. One hectare requires 32,000–36,000 knol, while the standard size potato seed for 1 kg contains 18 knol. The cost of purchasing seeds during the pandemic decreased from 30.35 to 29.34%. It is due to the declining price of seeds during the pandemic. Potatoes are susceptible to various pathogenic organisms and can lead to severe quality and yield losses, so potato production is highly dependent on pesticides, negatively impacting the crop sustainability [18]. Pesticides that farmers widely used are fungicides to control fungal attacks and insecticides to control potato plant pests. The needs for fungicides increase in the rainy season since the humid conditions and low temperatures increase fungal attacks. Leaf blight (Phytophtora infestans) is a significant disease, especially in rainy season [19]. The average cost of buying fungicides reaches IDR 12458902.10 (16.82%) and insecticides IDR 3701970.51 (5.00%) of the average total cost of potato farming per hectare.

The operating costs incurred by farmers are greater than other actors involved in the potato value chain [20]. Fertilizer, seed, and labor costs are a major part of the total variable costs associated with potato production [21]. The number of seeds impacts potato production, and resources are wasted [22]. The use of liquid organic fertilizer increased the number of tubers per plant, total tuber weight per plant, and tuber weight per plot [23]. Organic fertilizer significantly improves potato vegetative growth characteristics, yield, and high potato tuber quality as a sustainable agricultural practice for potato production [24]. Land and labor are the main input factors that affect household vegetable production [25]. The safe application of fungicides is important because they positively influence potato yield and quality [26].

Potato farming income per hectare is calculated from the production of each potato class multiplied by the respective potato price per class minus farming costs. The average income of potato farming per hectare is IDR 7093778.66 before pandemic and IDR 7758331.56 during pandemic, with a harvest age of 80–90 days (Table 3).

Table 3

Average productivity, product price, revenue, cost, and income of potato farming

Description Value
Before pandemic During pandemic
Productivity (kg/ha)
 ABC 12761.28 12579.98
 Seeds 1518.00 1367.34
 Rindil 716.47 454.32
Product price (IDR)
 ABC 5675.35 5991.39
 Seeds 4012.23 4042.55
 Rindil 2052.45 2097.85
Receipt (IDR/ha) 79985814.44 81830349.69
Farming cost (IDR/ha) 72892035.78 74.072.018.13
Income (IDR/ha) 7093778.66 7758331.56

3.2 Productivity risk and income of potato farming

Coefficient of variation analysis was used to see the magnitude toward the risk of potato productivity, namely the size of standard deviation divided by the average productivity. Potato productivity risk analysis is presented in Table 4.

Table 4

Average potato productivity risk

Description Value
Before pandemic During pandemic
Average productivity (kg/ha) 14995.75 14401.63
Standard deviation 2083.12 2443.76
Coefficient of variation (productivity risk) 0.140 0.170

The average potato productivity per hectare from 120 respondents consisted of potato productivity in ABC class, seed class, and pebble class. The potato productivity risk during the pandemic increased from 14 to 17% during pandemic. The risk of potato farming income (Table 5) is greater than the risk of productivity (Table 4). Income risk is strongly influenced by the size of the productivity risk, product price risk, input price, and the amount of input. Income risk is caused by the amount of production fluctuating prices, large farming costs, and lack of market demand, and the highest risk is income risk, followed by production risk and price risk [27]. The income risk analysis is presented in Table 5.

Table 5

Average risk of potato farming income

Description Value
Before pandemic During pandemic
Average income (IDR) 7093778.66 7433624.32
Standard deviation 5068346.93 6518768.17
Coefficient of variation (income risk) 0.714 0.877

The results showed a relationship between income risk and income (high-risk high return); meaning that the greater the risk of potato farming income, the higher the income. It can be seen that high-risk income is also high. In terms of selling price variability, income risk is considered a key factor in farmer decision-making [28]. Moreover, farmer income is a good indicator of farming feasibility through the large income ratio to farming costs [29].

3.3 Farmer level potato trading

The potato trade system in the research site involves several trading institutions: farmers as producers, collectors, wholesalers, retailers, and exporters. The trading channel is a series of activities carried out by marketing institutions that taking over rights or assisting in transferring rights to a commodity from the hands of producers (farmers) to consumers. There is no difference in potato marketing patterns before and during COVID-19 pandemic. There are two channels of commerce found as follows (Figure 1).

  1. The first pattern of the potato trading channel

    In this pattern, farmers sell potatoes to collectors, deposit them to wholesalers, and then supply them to exporter partners after careful degrading. Some factors influencing them to sell potato products to collectors involved in the first pattern since there is an easy access to collector’s place so they do not have to go far to sell and a cash payment system makes them easier to fulfill their daily needs and the purchase price is already profitable. The prices are determined by collectors [30] who deal directly with farmers [31] since it is one of priority commodity in Indonesia to be developed and has the potential to be marketed both domestically and for export [32] (Figure 2).

  2. The second pattern of the potato trading channel

    In this channel, farmers sell potatoes to wholesalers, and then from the collectors, they deposit them to inter-provincial wholesalers and then to retailers in the markets. Potato grading at the trader level includes classes ABC, seed, and rindil with different prices for each class. Some previous studies found four main links involving five actors: farmers/producers, intermediaries or wholesalers, retailers, processors, and final consumers [33]. The agricultural strategies can help distributors and retailers to prepare the increasing of the versatility toward their operations to keep pace with changing market dynamics in the future [34].

Figure 1 
                  The first pattern of potato trading channel.
Figure 1

The first pattern of potato trading channel.

Figure 2 
                  The second pattern of the potato trading channel.
Figure 2

The second pattern of the potato trading channel.

3.4 Potato trading model due to the impact of COVID-19

Before COVID-19 pandemic, potato trading activities at the research site are strongly influenced by the relationship between farmers and traders, either directly or indirectly (Figure 3).

Figure 3 
                  Potato trading system model in research locations before COVID-19 pandemic.
Figure 3

Potato trading system model in research locations before COVID-19 pandemic.

Farmers have a bound obligation to sell their potatoes to them. Most of them, especially those with small- and medium-scale businesses, mostly sell their potatoes through collector traders; in addition, there are traders at the sub-district level market. Another marketing channel is that farmers sell to collectors, and then from collectors, they are marketed to wholesalers, while from wholesalers, they can go to exporters or to retailers in the market. For farmers with large-scale farming, potato marketing is also sometimes done directly to wholesalers. The AST and farmer groups are not fully functional with this trading system pattern. The main reason is that most farmers’ production factors are met by traders (Figure 4).

Figure 4 
                  Model of potato during and after the COVID-19 pandemic by functioning AST.
Figure 4

Model of potato during and after the COVID-19 pandemic by functioning AST.

During COVID-19 pandemic, the accessibility of farmers to the market is difficult; there are even times when they could not go to the market due to the large-scale social restrictions, the frequency of the presence of collectors is reduced [10]. Strong cooperation should be built among input suppliers, farmer associations, extension services, and local retailers to assist farmers during COVID-19 [35]. The Human Resources Agency of the Ministry of Agriculture of Republic of Indonesia issued a policy of empowering ASTs to formulate the potato trade system during and after the pandemic. The function of AST is as a place for auctioning potato products, increasing the bargaining position of farmers since the farmers and farmer groups only display examples of potato products offered, efficiency in marketing costs and reducing crowds like in traditional markets. In this way, potato farmers sell their products with coordinated by the head of the farmer group by functioning AST, and the group leader has data and product samples that will be offered to buyers through AST and, at the same time, knows the market price formed and after that submits the sample to the auction officer. The responsibility of the farmer group is to coordinate the amount of production and select several criteria according to the class of potatoes produced. Thus, it will positively impact farmers by producing good products and increasing the quality of production, as well as enabling farmer groups to function.

Farmer’s income impacts the level of poverty and food security of farmer households; related to the ability of farmers to meet food needs based on income received from farming [29]. As the actors in trading system, farmers must be able to carry out production and product marketing activities that can provide maximum profit. Therefore, they are required to regulate the using of production factors efficiently to reduce production costs. In addition, they must be able to manage their capital well and adopt production and marketing technology to ensure sustainable potato farming activities. Thus, the operating food supply chains can produce value-added products and improve their social situation [36].

Collector traders know trading system activities by potato farmers and their products as an ingredient for determining the purchase price and selling price to a higher level trader. So far, the mediators have supplied local market traders, wholesalers, and traders; so the other traders, including collectors, do not come directly to the farmers but can access AST anytime. Sometimes, wholesalers and retailers can also access AST to get the necessary potato commodity. The distance from the nearest market, access to market information, buyer confidence, access to credit, number of products sold, own transportation facilities, and access to off-farm/non-agricultural income will affect the likelihood of households in combination to choose collector, wholesaler, retailer, and consumer markets at different levels of significance [37].

The most important role of AST is closely related to market price information. In this case, the function of AST is to bring together the traders (buyers) to potato commodities offered by farmer groups. Its another function is to carry out the auction function or fully regulate the transaction process between farmers represented by farmer groups and several traders through pre-agreed terms. AST will be able to bridge the farmers’ capital and provide an alternative for farmers to get out of their dependence on the previous financiers gradually. It is hoped that farmers will be freer to market their potato products through AST. It should also be a source of distribution of potato products demanded by traders. Thus, indirectly, AST’s role is to stabilize the continuity of production and the availability of products at market and at the consumer level that is, in the end, the formation of relatively stable prices.

4 Conclusion

This study concluded that during COVID-19 pandemic, potato productivity declined in all classes (ABC, seed, and rindil). However, the decline in potato productivity was followed by the increasing price of potato products and increasing farmers’ income, even though there were several production cost structures, such as labor, organic fertilizer, mulch, NPK fertilizer, and stakes. By this change, the risk of potato productivity during the pandemic has increased to 17%, and income risk increased to 87.7%. There are two channels of trading system, namely farmer–collector–traders–wholesaler–exporter partners and farmer–collector–traders–wholesalers–retailers. There is no difference between the two marketing channels before and during the pandemic. However, during the pandemic, the potato trading model tends not to rely on farmers and traders. The trading model allows potato trading agents to provide direct price information, attract traders, and facilitate transactions and trading contacts. The implication of this study is to anticipate productivity risk and potato farming income risk through AST function. It is hoped that AST can improve the bargaining position of farmers, efficiency in marketing costs, and reduce crowds like in traditional markets. The problem for further research is related to potato trading system that experienced the model changes before and during the pandemic, even after the pandemic. It needs to be investigated further.

Acknowledgments

The authors would like to thank Universitas Muhammadiyah Purwokerto and PP Muhammadiyah Diktilitbang Council for their support.

  1. Funding information: This study was funded by the Mu-Research Grant program Batch V of PP Muhammadiyah Diktilitbang Council.

  2. Conflict of interest: The authors state no conflict of interest.

  3. Data availability statement: All data generated or analyzed during this study are included in this published article.

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Received: 2022-04-13
Revised: 2022-10-29
Accepted: 2022-11-20
Published Online: 2023-01-02

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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