1. Introduction
Food loss has emerged as a significant challenge following the 2007–2008 food crisis, further impacting global food availability. The Food and Agriculture Organization of the United Nations (FAO) reported that despite the world’s ability to produce enough food for 7 billion people in 2009, the projected population growth to 9.3 billion by 2050 necessitates a 60% increase in food production to meet the expected 35% to 56% rise in global food demand by 2050 [
1,
2]. Food loss and waste (FLW) play a substantial role in exacerbating potential food shortages. Approximately one-third of the world’s annual food production is lost or wasted, with an estimated economic impact of over USD 1 trillion annually [
3,
4]. Harvest and post-harvest losses, inadequate supply chain management, and spoilage contribute to 25–30% of food loss between farm production and grocery store shelves [
5,
6]. As a result, addressing the issue of food loss has gained increased recognition and focus, particularly concerning food security.
SDG 12, one of the Sustainable Development Goals, focuses on reducing food loss and waste by halving global food waste at the retail and consumer levels, as well as minimizing waste from production processes and supply chains, including post-harvest losses, by 2030 [
7]. The reduction of food loss and waste is crucial for various reasons, including lowering production costs, improving the efficiency of the food system, enhancing food security and nutrition, and promoting environmental sustainability. According to a report by the FAO [
8], approximately 14.8% of food is lost globally after harvest, incurring a cost of at least USD 400 billion during transit, storage, and processing stages. Additionally, reducing food loss can have positive impacts on several other SDGs, such as SDG 2 (zero hunger), SDG 6 (sustainable water management), SDG 13 (climate change), SDG 14 (marine resources), and SDG 15 (terrestrial ecosystems, forestry, and biodiversity) [
9].
For policymakers at the national and international levels to assess the effectiveness of their initiatives in reducing food loss and waste (FLW) and achieving the goal of halving FLW by 2030, it is crucial to have reliable data and comparable measurements. Accurate measurement of FLW and identification of critical loss points are essential for evidence-based interventions and recommendations. Future research on FLW should adhere to the methodology used in the original FAO study or provide a compelling justification for using a different methodology. It is important to investigate if using a different methodology would have led to different conclusions drawn in the initial study. To address these needs, the FAO launched a methodology in 2018 for monitoring SDG 12.3, specifically focusing on the design of the global food loss index, data collection methods, and challenges for SDG 12.3.2, the global food loss index [
7].
According to the FAO [
8], food loss is defined as the reduction in food quantity or quality resulting from decisions and actions taken by food suppliers within the supply chain, excluding retailers, food service providers, and consumers [
9]. In other words, food loss occurs at various stages of the food supply chain, starting from harvest and continuing up to the point just before the retail level (as depicted in
Figure 1). It encompasses losses that happen during storage, transportation, and processing, as well as losses of imported commodities after they arrive in the host country. However, food loss does not include commodities that are utilized for non-food purposes, such as animal feed or industrial use.
In contrast, food waste encompasses food suitable for human consumption that is either discarded or left to spoil at the consumer level, irrespective of the cause. Commonly counted instances of food waste encompass both retail and consumer levels. This includes removing unsold products, including those nearing expiration, or damaged items from store shelves. It also involves discarding prepared but unpurchased food at retail. On the consumer end, food waste involves disposing of purchased but unconsumed items, uneaten leftovers, and food spoiling due to improper storage.
Table 1 displays the estimated food loss percentage in the food supply chain for each commodity group in different regions, and the Sub-Saharan Africa region had the highest percentage of food loss virtually for all food groups, followed by the South and Southeast Asia regions. Among foodstuffs in the South and Southeast Asia region, fruit and vegetable crops are lost at higher estimated rates than other food categories due to their perishable nature [
3,
10]. Unlike meat, dairy, and grains, fresh fruit can be a more recoverable food group because it requires little or no preparation before distribution [
11]. In Asia-Pacific, 15 to 50 percent of fruits and vegetables are out of customers’ reach because of inefficient harvesting, post-harvest handling practices, and inadequate knowledge and infrastructure [
12]. Due to the hot weather and inadequate storage, 30 percent of the fruits and vegetables were harmed during shipment [
13].
Thailand plays a significant role as a major producer and exporter of agricultural and food products, particularly tropical fruits and processed tropical fruit products. In 2017, the FAO reported that Thailand’s food loss amounted to 6.96 million tons [FAO, 2017]. As the study of food loss is relatively new in Thailand, few investigations have been conducted and are limited to specific aspects. For example, the Office of Agricultural Economics, in collaboration with the Rice Department, conducted a study on the average harvest loss rate of paddy [
13]. Moreover, they conducted a food loss study specifically focusing on fourteen fresh vegetables [
14]. In a separate study, Attavanich et al. (2020) [
15] examined five different commodities. However, it is important to note that both studies had their research methodological differences and deviated from the FAO guidelines.
Recognizing the importance of food loss in strengthening food security, the Thai government emphasizes the need for cooperation among stakeholders throughout the food supply chain, from farmers or producers to consumers, to effectively reduce food loss. This commitment is reflected in the launch of initiatives such as the Sustainable Consumption and Production Roadmap 2017–2037, driven by the Office of Natural Resources and Environmental Policy and Planning (ONEP), and the Strategic Framework for Food Management in Thailand, 2nd Edition (2018–2037), implemented by the National Food Board (NFB) and the Ministry of Agriculture and Cooperatives (MOAC) [
16]. The Roadmap aims to achieve a 5% annual reduction in food loss across the entire food supply chain from 2020 to 2037, compared to the base year statistics. Several key government agencies within the Ministry of Agriculture and Cooperatives (MOAC) are responsible for implementing this mission, including the Department of Agriculture (DOA), the Office of Agricultural Economics (OAE), and the Agricultural Research Development Agency (ARDA). In 2019, the Food Loss Reduction Subcommittee (FLRS) was established to propose measures for reducing food waste and driving Sustainable Development Goals.
Subsequently, the ARDA hosted discussions with stakeholder agencies to initiate a research project called “A national food loss assessment in food, and agricultural products”. The project endeavored to establish a food loss baseline to categorize critical food loss points and determine food loss mitigation measures throughout the value chain following the FAO guidelines [
7], as well as report on the SDG 12.3.1 implications. The research project received approval from the ARDA and resulted in a national loss index and a global food loss index specific to Thailand. These indexes help manage and report food loss to FAO and the UN. The project also establishes a national loss baseline to guide goal-setting for reducing agricultural and food product losses in Thailand. It provides guidelines for long-term monitoring and reporting of the Thailand loss index, along with policy recommendations to minimize quantity losses across the integrated value chain of agricultural and food products.
The FAO guidelines [
7] stipulate that the national loss index should include five groups of commodities: (1) Cereals and Pulses; (2) Fruits and Vegetables; (3) Roots, Tubers, and Oil-bearing crops; (4) Animal products; and (5) Fish products and Others. The selection of target agricultural and food products is based on criteria such as large-scale production, high economic value, significant losses, and significant environmental impact. After careful consideration, the FLRS (Food Loss Reduction Subcommittee) chose eleven agricultural and food products to be included in the study: Mung beans, Banana, Longan, Mango, Chili, Vegetable salad, Oil palm, Chicken meat, Egg, White leg shrimp, and Sugar cane [
17].
Longan, scientifically known as Dimocarpus longan Lour., is a fruit that belongs to the Sapindaceae family. It is commercially cultivated for both fresh consumption and processing purposes. Originating from tropical Asia and China, longan is renowned for its sweet taste. In Thailand, two primary types of longans are consumed and traded: fresh longans and dried whole longan fruit. The fresh longan has been included in the commodity basket for food loss assessment due to its substantial economic value, especially in terms of exports, its extensive large-scale production and cultivation, and the involvement of numerous stakeholders along its value chain. In 2022, longan production in Thailand amounted to 1,032,326.7 million tons [
18]. The volume and value of fresh longan export was 470,538.71 metric tons and USD 491.90 million, respectively [
19]. China serves as a prominent target market for longan exports.
A comprehensive review of the literature reveals that food losses in various tropical fruits, such as Litchi [
20,
21,
22], Mangoes [
23,
24,
25], and Banana [
26], have received significant research attention. However, most of these studies rely on expert opinions or questionnaire surveys on a few stages of the value chain to estimate food loss percentages. A limitation of these methods is that the reported loss percentages are subjective opinions and may not accurately reflect the true extent of the problem. To address this limitation, there is a critical research gap that needs to be filled through comprehensive studies incorporating direct measurements and observations at the farm level. This approach is crucial for obtaining accurate and reliable data on food loss, particularly in the longan value chain. By closing this research gap, valuable insights can be gained into the actual magnitude of food losses and enable the development of targeted strategies to effectively mitigate them.
Therefore, this study aims to address this gap by answering the following research questions related to food loss in the longan industry in Thailand: To what extent, in both quantitative and qualitative terms, does food loss occur throughout the fresh longan supply chain while adhering to FAO guidelines (2019)? Where do food losses reach critical levels within the various stages of the fresh longan supply chain? What actionable policy recommendations can be devised to significantly diminish food losses and promote the sustainability of the fresh longan industry? To achieve answers to these research questions, the study evaluates the percentage of food loss along the supply chain of fresh longan, adhering to the FAO guidelines (2019) [
7], identifies critical loss points in each longan supply chain, and proposes the policy suggestion to mitigate the longan loss. The research focuses on two specific longan supply chains: fresh longans for domestic consumption and fresh longans for export. Crop-cutting measurement surveys, on-farm direct measurements, and stakeholder sample surveys with questionnaires are fundamental tools for assessing longan loss. These data collection methods capture crucial information during the on-season and off-season harvesting and post-harvesting of fresh longans at lower levels, providing valuable insights into the extent and causes of the losses.
This is the first time the baseline for longan loss in Thailand will be established from the evaluation of the food loss percentages. As a result, the three main research contributions are (1) the detailed descriptions of the guidelines for field survey measurements, particularly from on-farm measurements, and data collection from stakeholders along the longan supply chain, sampling method, and calculating methodologies following FAO guidelines; (2) the analysis of the critical loss points in each chain; and (3) the policy suggestion to mitigate the longan loss, which can be a synergetic policy package towards food sustainability. This paper’s structure is as follows. In
Section 2, we review the definition of food loss, conduct literature reviews on food loss measurement and evaluation, and explore the longan supply chain and longan losses.
Section 3 outlines the methodology and data collection process. The empirical results are presented in
Section 4, while
Section 5 contains the discussion and conclusion. Finally, the last section covers the limitations of the study and suggestions for further research.
3. Materials and Methods
3.1. The Scope of Food Loss Assessment
The scope of this study entails a comprehensive assessment of fresh longan loss, encompassing both in-season and off-season production. The assessment includes examining physical and economic losses at all stages of the fresh longan value chain, including harvesting, sorting, grading, packaging, and transportation. The research adheres to the global food loss assessment guidelines provided by the FAO [
7]. The study area focuses on the two largest in-season longan-growing regions in the upper north of Thailand, specifically Chiang Mai and Lamphun, as well as the two largest off-season longan-growing regions in the eastern region, Chanthaburi and Sa Kaeo. Data will be sourced from the OAE database [
46].
The FAO guidelines recommend commencing food loss assessment by concentrating on product losses, encompassing all quantity losses throughout the value chain. The longan value chain flowchart presented in
Figure 3, provided by the Office of Agricultural Economics (OAE), offers insights into the dynamics of the longan industry [
47]. Two main fresh longan value chains were examined for food loss measurement: the fresh longan bunch chain for domestic consumption (BL) and the fresh longan in white basket chain (WBL) for export, which account for 9% and 44% of total production, respectively. The remaining 47% of production is directed to the processed longan chain, which includes canned longan, golden-dried longan, and frozen longan. The primary focus of this study revolves around the BL and WBL value chains.
3.2. Population and Sample Size
The population and sample size for longan loss assessment in this study were meticulously determined through two distinct phases. Phase I conducted a preliminary food loss assessment to identify critical loss points, analyze the industry context and supply chain, and determine driving factors affecting food loss. It also calculated the coefficient of variation (CV) and established the appropriate sample size for Phase II.
Data collection for this study involved a comprehensive approach, encompassing in-depth interviews, semi-structured questionnaires, and focus group interviews, targeting longan growers and stakeholders within the fresh longan supply chain. The sample size included 300 longan growers and 19 stakeholders, selected through a combination of snowball and purposive sampling methods. Additionally, two focus group interviews were conducted in Chiang Mai and Chanthaburi provinces, representing the northern and eastern Longan plantation regions, respectively, to obtain valuable insights from key industry stakeholders. Despite the challenges presented by the COVID-19 pandemic, data collection took place from June to December 2020. The computed coefficient of variation (CV) yielded values of 0.78 for longan growers and 0.28 for fresh longan factories or suppliers for export, indicating the variability within the data sets. For more in-depth findings from Phase I, detailed results are available upon request.
Phase II of the study encompassed a comprehensive food loss assessment, which aimed to quantify quantity, quality, and economic losses along the longan supply chain. Additionally, the study sought to analyze critical loss points, identify causal factors, and calculate product loss percentages for the national baseline. The focus was directed toward the top eight longan cultivation provinces, together accounting for 93.05% of the total longan plantation area. Among these provinces, six were known for on-season cultivation, namely Chiang Mai, Lamphun, Chiang Rai, Phayao, Nan, and Lampang, while off-season cultivation took place in Chanthaburi and Sa Kaeo. Data collection for the on-season was undertaken from July 2021 to September 2021, while data for the off-season were gathered from November to December 2021. To assess harvest losses for longan growers, multiple methods were employed, including on-farm direct measurements and agricultural production questionnaires.
The on-farm direct measurements utilized purposive sampling with a focus on clustered areas. This method entails physically measuring and observing crops in the fields. Researchers visit selected farms to directly assess longan quantity, harvested produce weight, and longan loss. This approach ensures precise and accurate data on crop yields and losses at the individual farm level. Sixteen farms were selected for on-farm direct measurements, with ten samples taken from on-season farms and six samples from off-season farms. For on-season farms in Chiang Mai and Lamphun provinces, the planting regions were categorized into upper, middle, and lower parts, considering variations in planting techniques, weather conditions, and harvesting periods. Each area was represented by one sample, resulting in three observations for the Chiang Mai and Lamphun provinces. However, due to the relatively smaller plantations in Nan, Chiang Rai, Lampang, and Phayao, only one sample was collected from each of these provinces. For the off-season longan in Chanthaburi and Sa Kaeo provinces, data collection required selecting four farms from Chanthaburi and two farms from Sa Kaeo. This decision was made because Chanthaburi has a larger area dedicated to longan cultivation compared to Sa Kaeo.
Agricultural production questionnaires, also known as on-farm questionnaires, play a vital role in assessing critical loss points and identifying underlying causes. These surveys are distributed to farmers and agricultural stakeholders to gather essential insights into diverse aspects of agricultural practices—ranging from crop cultivation and input usage to crop yields and losses. By utilizing these questionnaires, researchers can uncover factors influencing food loss and formulate strategic decisions to address agricultural production challenges, thus effectively reducing losses.
Determining the appropriate sample size for the agricultural production questionnaires employed Thomson’s formula for relative precision [
66], represented as
where
N signifies the population size,
γ stands for the coefficient of variance,
z indicates the 95% confidence level, and
r represents the preferred potential error, set to be under 10%. This formula aids in calculating a suitable sample size that captures data with the desired accuracy and confidence level.
The surveys were conducted during the primary longan cultivation season, covering Chiang Mai and Lamphun. Conversely, the off-season encompassed Chanthaburi and Sa Kaeo. Applying Thomson’s formula to the longan grower data from all four provinces yielded a total sample size of 88. Subsequently, the sample allocation for each province was determined proportionally to its population. As a result, 72 samples were collected from in-season farmers in Chiang Mai and Lamphun provinces, while 16 samples were obtained from off-season farmers in Chanthaburi and Sa Kaeo provinces.
The on-farm questionnaire is specifically crafted to gather firsthand information directly from farmers and agricultural stakeholders regarding losses encountered during different stages of longan harvest and post-harvest. The questionnaire aims to comprehensively collect details about diverse facets of agricultural practices. These include harvesting, as well as processes such as collection, grading, packaging, transportation, and storage. Furthermore, the questionnaire delved into essential aspects such as crop cultivation, input utilization, crop yields, losses experienced at the farm level, and the underlying causes of these losses.
Engaging with off-farm stakeholders, including cooperatives, fresh longan export factories, and wholesalers, we adopted a unique approach. In cases where official data for cooperatives were unavailable, we utilized the snowball sampling method to select our sample. With a focus on the primary cultivated regions of Chiang Mai and Lamphun provinces, we chose cooperatives involved in fresh longan activities from each province to represent our sample. This encompassed Pratu Pa Agricultural Cooperative Limited of Lamphun and Phrao Agricultural Cooperative Limited of Chiang Mai. Similarly, for fresh longan export factories strategically situated in high cultivation areas, we computed the sample size using the formula from Equation (1). For the on-season, we determined a sample size of fourteen, equally divided between Chiang Mai and Lamphun provinces, while the off-season in Chanthaburi province was represented by twelve samples. A comparable strategy was employed for wholesale stakeholders. Within the well-known fresh fruit wholesale market, ‘Ta-laadthai’, we identified two wholesale markets as the foundation of our sample through the snowball sampling method.
The off-farm questionnaire is specifically designed to gather information about loss during the transportation, storage, and various other stages of fresh longan beyond the farm level. The questionnaire employed a combination of inquiries and direct observations to comprehensively document these losses. Additionally, the questionnaires recorded supplementary indicators such as transportation mode, packaging type, transported quantity, storage method and facility, quantity stored or handled, humidity, temperature, causes of loss, and the proportion of loss relative to the total quantity handled at each stage of the process.
3.3. Data Collection by On-Farm Direct Measurements
The data collection process for on-farm direct measurements in this study encompassed two distinct approaches to capturing loss data: quantitative loss, which referred to the reduction in the amount of consumable food throughout the supply chain, excluding weight loss, and qualitative loss, characterized by the degradation in food quality or value while still retaining edibility [
67].
3.3.1. On-Farm Direct Measurements at the Lower Level of Logan Grower
The selection of longan orchards for on-farm direct measurement involved a systematic approach aimed at identifying suitable representative locations reflecting diverse longan farming practices. This method included thorough research to identify areas with high longan production levels, varying cultivation methods, and diverse agro-climatic conditions. The emphasis lay on achieving geographic diversity, accessibility, and collaboration with local farmers to pinpoint pertinent sites. Furthermore, accounting for both the main harvesting season and off-season was crucial to gaining comprehensive insights into the factors impacting longan production.
Once the sample longan orchards were identified, the process commences with conducting interviews with growers to gather information about the longan plantation areas and the number of longan trees. This data aids in creating a comprehensive map of the Longan plantations. Subsequently, the methodology involved establishing points for measuring food loss on the farm, aligning with the FAO’s 2018 food loss measurement guidelines. Specifically, three rows were randomly selected within each of the three clusters of samples, with three longan trees chosen from each row (
Figure 4). The research team then undertakes preparations, including cleaning the area beneath the longan trees and laying out a canvas of the same width as the shrub’s size to facilitate accurate measurement procedures.
- 2.
Food loss measurement
This stage involves assessing losses occurring at the grassroots level of longan cultivation and across the entire longan supply chain. Losses during the harvesting and post-harvest management of longan encompass distinct processes based on their respective purposes.
- (2.1)
Harvesting process: Once the canvas was laid out, local harvest laborers commenced the process of harvesting longans. To begin the assessment, the research team first recorded the weight of the various baskets employed by the workers for collecting longans, given that these baskets differ among different orchards. Subsequently, fruit pickers gather the longans and place them in the baskets. The combined weights of the harvested longans were then measured (A) and documented, accounting for the baskets’ weight to accurately determine the longans’ weight. Following this, the research team collects any longans that had fallen during the harvesting process (B) onto the blue plastic canvas, recording their weight. The loss of produce at this stage was considered a “quantitative loss,” as all fallen output was deemed unsuitable for consumption, regardless of the reason for its falling.
- (2.2)
Sorting, grading, bunching, and packing process: In this phase, freshly harvested longan fruits were typically sorted, graded, bunched, and packed on the farm by skilled sorting and packing teams, adhering to both domestic consumption and export standards for longan quality. A randomly selected batch of fresh longans from the baskets was weighed, after which the fruit grading and packing personnel meticulously removed any undesirable leaves and branches that did not meet quality standards. Following this, the workers proceeded to identify and separate damaged longan fruits (E) and lower-quality longans (F). The damaged longan fruits represented a ‘quantitative loss,’ while the lower-grade longans signify a ‘quality loss’. The remaining longans, which met the required standards for size and quality, were weighed and documented (D). Subsequently, these premium fresh longan fruits were meticulously packed into baskets destined for selling to both fresh longan business operators and export-oriented fresh longan factories.
- 3.
Calculation of Food Loss Percentage
Using the collected data, the percentages of food loss (both in terms of quantity loss and quality loss) were calculated using the formula below. Given that the direct measurement of the weight of all longan output (excluding branches and leaves) from a sole longan plant was not feasible within the regular harvest process, it was instead derived from the collected data. Let
Y denote the total weight of all harvested longan output from a specific longan plant, except for branches and leaves.
Food loss percentage during harvesting (quantitative):
Food loss percentage during grading (quantitative):
Food loss percentage during grading (qualitative):
where
A = Total weight of harvested longan yield, including longan plant branches and leaves (harvesting process);
B = Weight of fallen longan fruits during harvesting (harvesting process);
C = Weight of a randomly selected basket of longan fruits (grading process);
D = Weight of undamaged longan fruits in one basket (grading process);
E = Weight of damaged longan fruits in one basket (grading process);
F = Weight of non-standard size longan fruits in one basket (grading process).
3.3.2. Actual Measurement at Fresh Longan Factory for Export
- 1.
Food loss measurement.
The packed fresh longans in the white basket were transported from longan orchards to the fresh longan factory for export. After fresh longans arrived at the factory, laborers would bring the baskets of fresh longans down from the pickup truck to go through the quality inspection process. The process started with sorting out the damaged longan fruits, regrading, and closing the basket. The damaged longan fruit part was a “quantitative loss” because it would be discarded. This process takes a little time because most of the longan fruit produced was packed by skilled labor in the grower’s grading process. After that, the produce would be taken to receive SO2 fumigation. The research team will weigh the good quality longan fruit produce (N) in the basket and the damaged longan fruits (H) and record. To measure SO2 fumigation losses (), the interview method was used because the SO2 fumigated longan baskets had already been packed on pallets, which had already been packed for loading in a truck container.
- 2.
Food loss calculation.
Food loss percentage during grading of fresh longan factory for export (quantitative) was
where
G = Weight of good quality longan fruit produce;
H = Weight of damaged longan fruits.
3.3.3. Actual Measurement at Agricultural Cooperative
The bunched fresh longans in the basket were transported from longan orchards to the agricultural cooperative. After fresh longans arrived at the cooperative, laborers would sort out the damaged longan fruits and pack them in new packaging according to customer requirements. The damaged longan fruit part was a “quantitative loss” because it would be discarded. After that, the produce will be taken to undergo the SO2 fumigation process. The research team weighed the good quality longan fruit produce (I) in the new packaging and the damaged longan fruits (J) and recorded the weights. To measure SO2 fumigation losses (), the interview method was used.
- 2.
Food loss calculation.
Food loss percentage during grading of fresh longan cooperative (quantitative) is
where
I = Weight of good quality longan fruits;
J = Weight of damaged longan fruits.
3.3.4. Actual Measurement at the Wholesale Level
After fresh longans arrived at the wholesale establishment, laborers would sort out the damaged longan fruits. The damaged longan fruit part was a “quantitative loss” because it would be discarded. The good quality longan fruits would be rearranged in preparation for selling. The research team weighed the good quality longan fruit produce (K) in the new packaging and the damaged longan fruits (L) and recorded the weights. The food loss was caused by the transportation process from the local fresh longan business operator or cooperative to the wholesaler.
- 2.
Food loss calculation.
The percentage of food loss of fresh longan wholesalers (quantitative) was
where
K = Weight of good quality longan fruits;
L = Weight of damaged longan fruits.
3.3.5. Comprehensive Longan Loss throughout the Supply Chain
The comprehensive assessment of longan loss throughout the supply chain commences with the establishment of the initial quantity, designated as 100, for calculation purposes.
Quantitative Loss
The process unfolded in successive steps, starting with the harvesting activity (Activity 1), where the percentage of quantitative loss (FLquant,1) was gleaned from recorded data. Utilizing this percentage, the loss amount in Activity 1 (Loss1) was computed by multiplying the initial quantity (100) by FLquant,1. The remaining quantity after Activity 1 (Rquant,1) was determined through the subtraction of Loss1 from the initial quantity (100).
Advancing to Activity 2, encompassing grading and bunching, the percentage of quantitative loss was determined based on data records. The loss amount for this activity (Loss2) was evaluated by multiplying Rquant,1 by the percentage of quantitative loss in Activity 2 (FLquant,2). Following this, Rquant,2 (the residual quantity after Activity 2) was computed by deducting Loss2 from Rquant,1.
The quantitative loss computation for Activity 3 (grading at fresh longan factory/cooperative), represented in the third step, follows a similar methodology. The loss amount (Loss3) was determined using Rquant,2, and the corresponding percentage of quantitative loss (FLquant,3). Rquant,3 was ascertained by subtracting Loss3 from Rquant,2.
Transitioning to the fourth step, involving Activity 4 (SO2 fumigation), the calculation was derived from Loss4, which depended on Rquant,3 and the percentage of quantitative loss (FLquant,4). Subsequently, Rquant,4 was calculated by subtracting Loss4 from Rquant,3.
In the culminating step, which corresponded to Activity 5 (Wholesale), the quantitative loss assessment was reiterated. The loss amount (Loss5) was computed utilizing
Rquant,4, and the associated percentage of quantitative loss (
FLquant,5).
Rquant,5 was calculated by subtracting Loss5 from
Rquant,4. Consequently, for
i = 1 to 5 (signifying activities) and with
Rquant,0 = 100 (initial quantity), which could be written the expression as follows:
This concise formula encapsulated the iterative process of computing residual quantities (
Rquant) for each activity within the quantitative loss calculation. Ultimately, the comprehensive Longan Loss throughout the Supply Chain was determined by
Qualitative Loss
In terms of the qualitative loss experienced in exported and locally consumed fresh longans, it was notable that there were two prominent stages involved. The first stage was the farmers’ grading, bunching, and packing process (Activity 2). As a result, the comprehensive assessment of qualitative loss (
FLqual) within the longan supply chain was established using the subsequent formula:
The second was regarding the packing house in the factory. This stage had a little qualitative loss (
FLqual) because most of the fruits were packed and graded by the skilled workers at the farm level, but sometimes the fruits were packed by the owner’s workers teams before the regrading, which caused qualitative loss (
FLqual) at the longan factory level to be significant. As a result, the comprehensive assessment of qualitative loss (
FLqual) within the longan supply chain was established using the subsequent formula:
For this study, all of the longan fruits were sorted, packed, and graded by the skilled workers who were the vendors in the vendor list of the longan factories at the farm level, so the qualitative loss (FLqual) at the longan factory level did not occur. Therefore, qualitative loss (FLqual) at the longan factory level was not used in the calculation.
3.3.6. Economic Loss
The process of assessing economic loss (
EL) involved quantifying the monetary value of food that went to waste due to quantitative losses (
ELquant) and qualitative loss (
ELqual) and understanding the financial impact arising from the deviation from expected normal values due to qualitative losses.
To accurately compute economic loss, it is crucial to have information about the amount of loss, the product’s price, and the extent to which qualitative loss affects its value. The price used for these computations was based on actual market prices observed over the previous three years.
However, there might be challenges in obtaining accurate prices for all activities under certain circumstances. In such cases, this study segmented activities into two categories: those conducted before the SO2 fumigation process and those carried out after it. For quantitative losses, economic loss was obtained by summing up the economic losses before and after SO2 fumigation.
Quantitative economic loss
For quantitative losses, economic loss is obtained by summing up the economic losses before and after SO
2 fumigation. The economic loss before SO
2 fumigation is calculated by multiplying the price of the product before SO
2 fumigation (
P1) by the quantitative loss before SO
2 fumigation (
RT −
Rquant,BEF). The economic loss after SO
2 fumigation is determined by multiplying the price of the product after the SO
2 fumigation process (
P2) by the quantitative loss after SO
2 fumigation (
Rquant,BEF −
Rquant,AFT). The calculation formula can be presented as follows:
where
ELquant = Economic loss;
RT = Quantity of initial product;
Rquant,BEF = Residual quantity of product before SO2 fumigation;
Rquant,AFT = Residual quantity of product after SO2 fumigation;
P1 = Average price of the product before SO2 fumigation over 3 years;
P2 = Average price of the product after SO2 fumigation over 3 years.
Qualitative economic loss
The qualitative loss was found only in pre-SO
2 fumigation activities. Thus, the economic loss is calculated by multiplying the reduced value of the product resulting from the quality loss (
P3) by the qualitative product loss (
RT −
Rqual,BEF). The reduced value of the product (
P3) is calculated from the difference between the price of the product that should have been received and the price of the product that has decreased in quality for 3 years on average. The calculation formula can be shown as follows.
where
ELqual = Qualitative economic loss;
RT = Quantity of initial product (total output in the product supply chain);
Rqual,BEF = Residual quantity of product before SO2 fumigation (from qualitative loss);
P3 = Average reduced value of the product before SO2 fumigation over 3 years.
6. Conclusions and Policy Recommendations
This comprehensive study rigorously amassed data about food loss at every phase of the on-season longan value chain, encompassing fresh longan for export and fresh longan for domestic consumption. The findings illuminated the intricate landscape of food loss within the fresh longan supply chain. Specifically, within the fresh longan intended for export, a quantitative food loss of 13.503%, a qualitative food loss of 14.820% for on-season, and a quantitative loss of 9.85% and a qualitative loss of 6.52% for off-season were recorded. Similarly, for fresh longan designated for domestic consumption, a quantifiable food loss of 14.07% and a qualitative food loss of 11.02% were identified. The study underscored that the crucial stages of harvest and grading/sorting emerged as the focal points of the most pronounced food losses. Late harvesting and insufficient pre-harvest care emerged as the primary factors driving these losses. Importantly, while the pre-harvest process itself did not directly contribute to quantifiable food loss, it significantly influenced longan damage, thereby exacerbating post-harvest food losses.
Therefore, the policy recommendations were as follows. The upstream recommendations are as follows: Water shortage during the fruiting period, a lack of knowledge about fertilizer and plant hormones, and neglect of tree care due to limited capital resulting in cracked longan fruit contribute to smaller-sized and cracked longan fruit. To address this, growers should receive training support in proper irrigation practices and the use of agricultural inputs, and encouraging regular tree care and ensuring consistent water supply through irrigation systems can mitigate this issue. Insects like fruit-piercing moths and oriental fruit flies are attracted to ripe longan fruit, causing rot. Pesticides can serve as a valuable tool to mitigate losses caused by pests and diseases during the pre-harvest phase, ultimately enhancing agricultural output and farm income [
76]. However, concerning longans, research by Kuang et al. [
77] has unveiled the presence of pesticide residues in Chinese samples, with some exceeding acceptable levels. Additionally, a study conducted by Wongta et al. [
78] identified pesticide exposure among villagers, including longan growers, resulting in residue accumulation in their bodies. Thus, responsible pesticide use, alongside other agricultural practices, is vital to maximize effectiveness and minimize adverse impacts. Implementing Integrated Pest Management (IPM) strategies, like using traps and organic insecticides, can effectively control these pests and improve orchard hygiene, thereby reducing qualitative loss. Delaying the harvesting process results in over-ripening, elevated instances of fruit breakage, and an increased likelihood of fruit rot. To address this issue, the Department of Agricultural Extension (DOAE) should launch initiatives focused on improving longan harvesting and grading techniques. By enhancing competency in these crucial aspects, the labor can operate more effectively, leading to enhanced productivity and elevated longan quality.
The establishment of a dedicated fund to support quality longan cultivation was proposed. This fund could catalyze knowledge propagation and provide essential resources for production factors, thereby ensuring a consistent supply of high-quality longans. Collaborative networks foster the exchange of knowledge within the production sphere, encompassing aspects. Additionally, commercial registration of longan growers was suggested to curb the influx of substandard longans into the market, consequently stabilizing market prices. For the Office of Agricultural Economics, the introduction of crop insurance was pivotal to instill confidence and incentivize farmers to invest in cultivating quality longans. Establishing a central agency for overseeing purchase–sales contracts was recommended to enhance trust and transparency in trade interactions between farmers and entrepreneurs.
In the midstream, the Ministry of Industry was encouraged to provide low-interest loans during the long season to offer liquidity support to entrepreneurs. Such financial aid could play a pivotal role in ensuring seamless operations during peak periods. Furthermore, promoting the development of machinery and technology to reduce reliance on manual labor was crucial. This not only improved production efficiency but also aligned with modernization trends in the agricultural sector. A fund dedicated to business enhancement and knowledge propagation should be established to support the growth and development of enterprises, fostering a more robust and competitive industry.
For the downstream, to stimulate domestic consumption, the Ministry of Commerce should focus on establishing a central longan market within the country. This market could serve as a hub for product distribution, effectively channeling longans to consumers and enhancing their accessibility. Embracing these comprehensive policy recommendations could fortify the entire longan value chain, contributing to the perpetuation of high-quality production, improved market dynamics, and the overall advancement of the longan industry.