(Luận văn thạc sĩ) determinants of water melon production at farm household level in tien giang provice

Research context

Tien Giang's watermelon is a key fruit export to China and Cambodia, yet its production remains unstable In 2007, the watermelon cultivation area was 3,779 hectares with an output of 70,847 tons, but by 2008, the area decreased to 2,954 hectares, resulting in a lower output of 55,754 tons The current cultivation practices lack concentration and specialization, leading to significant price fluctuations and a dependency on wholesalers for market demand, which varies seasonally Producers face a lack of information regarding the economic efficiency and profit contributions of watermelon farming to household income Despite the many unknowns in watermelon cultivation and trade, this article focuses on the supply side, particularly the economic viability of watermelon planting in Tien Giang province.

This research identifies key weaknesses in the watermelon production process that require enhancement These include the low entrepreneurial skills of farmers across all genders and age groups, their capacity to adapt to adverse natural conditions, particularly frequent climate changes, and the overall quality of watermelons available for market.

Research problem

Understanding the factors that influence watermelon yield among farmers remains unclear Different types of farmers respond uniquely to various influences This study aims to identify the key factors affecting watermelon production in Tien Giang by utilizing a production function model, principles of farm household economics, and SWOT analysis.

This study evaluates the effectiveness of various inputs in watermelon production, emphasizing the importance of resources such as land, labor, and capital, which includes both cash and physical assets like fertilizer and seeds Additionally, it highlights the necessity of incorporating market information to ensure adequate supply to specific markets, avoiding both surplus and deficit situations.

Goal and specific objectives of the study

Tien Giang, a key province in Western Vietnam's economic landscape, relies heavily on agriculture for its development This study aims to enhance agricultural productivity and elevate the living standards of farm households in Tien Giang by focusing on increasing watermelon output.

The specific objectives of the study are to:

1 Identify the potential factors which impact strongly to water melon production process in order to indicate the right ways and approaches to gain higher productivity

2 Estimate economic efficiency of different factors of production used in water melon cultivation

3 Make recommendations and strategic suggestions for government policy and farmer groups to enhance the profitability of water melon production to farmers

Research question

The primary aim of this research is to identify key factors influencing watermelon production and to evaluate the economic efficiency of these production factors To achieve this goal, the author poses specific research questions that focus on addressing these objectives.

Which factors that impact potentially on Tien Giang's water melon production? How is economic efficiency of factors that impact to water melon production estimated?

Scope ofresearch

This research focuses on specific factors influencing watermelon production, such as productive area, labor, fertilizer, seeds, market information, and the growing experience of farmers, while acknowledging that other underlying factors may exist Conducted in Tien Giang province, which includes 8 districts, 1 city, and 1 town, the study gathered data through 177 questionnaires from farmers who have cultivated watermelons for at least one year The data collection took place over three months, from October to December 2010, providing a solid foundation for analysis.

The organization of the thesis

Chapter 1 outlines the rationale behind this research, detailing the research context and the specific problem addressed It defines the study's goals and objectives, poses key research questions, and delineates the scope of the research Additionally, this chapter provides an overview of the thesis organization.

Chapter 2 is literature review This chapter provides: (1) theory about farm household economies, production function and production factors of farm household; (2) empirical studies; and (3) analytic framework of this research

Chapter 3 introduces research methodology including analytical framework (the regression model, variable indication, sign expectation, variable description), data collection and sample distribution and analysis methods

Chapter 4 analyzes watermelon production in Tien Giang province, focusing on how input usage affects yield It provides a comprehensive overview of the province, highlighting key factors that influence watermelon cultivation and productivity.

Tien Giang province boasts favorable climate and soil conditions for watermelon production, making it a significant agricultural hub This article explores the competitiveness of watermelon in the market, alongside a comprehensive SWOT analysis of the production landscape in Tien Giang It also includes insights from farm surveys that detail current practices and highlights the impact of various input factors on watermelon yield through econometric analysis.

Chapter 5 IS the last one is presented conclusion and recommendation for provincial authorities to help farmers get a higher productivity and especially get a higher benefit h

LITERATURE REVIEW

Theoretical framework

2.1.1 Theory of farm household economies

Peasant economic behavior can be understood through logical deductions based on prior assumptions about household goals and the market nature influencing their decisions In economic analysis, the farm household is viewed as a single decision-making unit that aims to maximize a single utility function, where profit maximization aligns with utility maximization in fully competitive input and output markets The variations in economic theories stem from differing assumptions about factor and product markets, rather than household goals Additionally, the allocation of household labor time and labor market assumptions play a crucial role in distinguishing between theories Ultimately, household economic behavior is influenced by social relations, which affect how markets function for different peasants.

The agricultural labor force primarily consists of farmers, with the concept of a farm closely tied to farm households, which vary in size In many regions of sub-Saharan Africa and South and East Asia, including countries like Bangladesh, China, and India, the majority of farms are typically under two hectares In contrast, West European countries often feature farms that span thousands of hectares Additionally, farms can be categorized into various types, such as family farms, business farms, and specialized farm enterprises that are fully integrated into the market economy.

Therefore there are still difficulties in making distinctions between farms in term of size of farm resources and nature of production (Boussard 1987) (cited in Tran Tien Khai, 2001 )

Peasant farm households, primarily composed of families utilizing their own labor for agricultural production, are integral to the global population, representing at least a quarter of it In developing countries, they can constitute up to 70% of the national population, highlighting their significant role in these economies These households operate within a broader economic and political framework that influences their production practices, often engaging only partially in imperfect input and output markets (Ellis 1992, cited in Mariapia Mendola, 2007).

Hunt (1991) describes peasant farms as dual-function units that serve both production and consumption purposes A portion of their produce is sold to fulfill cash needs and financial commitments, while another segment is utilized for their own consumption (Mendola, 2007).

One of the primary theories in farm economics is the concept of utility maximization, where farmers make decisions aimed at maximizing their utility Neo-classical economics posits that, under conditions of limited production resources and technical availability, farms exhibit behavior that seeks to maximize this utility function According to Ellis (1993), utility maximization equates to maximizing overall income Brossier et al (1997) further explored the challenge of identifying profit maximization in agriculture, as referenced in Tran Tien Khai (2001).

II=P-CV -CF-KA- WA h

Where: II is the profit

KA and W A are remuneration of capital and family labor

CV is all variable charges of exterior-bought factors

CF is fixed charges paid to interior

It is difficult to identify the KA and W A; so, farmers maximized the function II +

KA + W A (or P - CV - CF) which is considered as the agricultural revenue or revenue

Economy of scale is a conception come from the neo-classical theory of production

Economies of scale refer to the cost advantages that firms experience as they expand their production As output increases, various factors contribute to a reduction in the average unit cost for producers This concept highlights the challenges faced by small farms, which often struggle to compete with larger farms due to their higher unit costs and reduced competitiveness.

Figure 2.1: The relationship between output and average cost Source: http://en.wikipedia.org/wiki(Economies_of_scale

As quantity of production increases from Q to Q2, the average cost of each unit decreases from C to C 1•

Ellis (1993) emphasized the significance of indivisible resources in achieving economies of scale in agriculture An example of such a resource is the power of a tractor, which must be effectively utilized over a sufficient land area to enhance efficiency The optimal use of these indivisible resources leads to cost economies, directly influencing the output volume that minimizes unit production costs in the short run (Tran Tien Khai, 2001).

Production functions are essential in neo-classical economic analysis, defining the relationship between inputs and outputs for firms, industries, or entire economies They illustrate how firms convert various inputs, known as production factors, into outputs or products during the production process For instance, in a bakery, inputs consist of labor (workers), raw materials like flour and sugar, and capital investments in equipment such as ovens and mixers, which collectively enable the production of goods like bread, cakes, and pastries.

Inputs can be categorized into labor, materials, and capital Labor encompasses both skilled workers, such as carpenters and engineers, and unskilled workers like agricultural laborers, along with the entrepreneurial efforts of managers Materials consist of essential goods like steel, plastics, electricity, and water, which are purchased and transformed into final products Capital refers to assets such as land, buildings, machinery, equipment, and inventories that support the production process.

The following production function describes the relationship between input and output A production function indicates that a firm can obtain the highest output Q from every specified combination of inputs:

It relates the quantity of output (Q) to the quantities of the inputs such as capital (X1), labor (X2), materials (X3) and etc (Robert and Daniel, 2009)

A quadratic production function illustrates the relationship between input levels and maximum output, with all points below the curve representing technically feasible production levels Points on the curve indicate the optimal quantity of output achievable given specific input levels.

According to Figure 2.2, the production function increases from points A, B, and C, indicating that as more input units are utilized, output quantity also rises However, at point C, while additional input units are added, the output does not increase; instead, total output starts to decline due to underutilization of inputs.

At point A, increasing inputs leads to a rise in output at an accelerating rate, with both marginal physical product (MPP) and average physical product (APP) on the rise The inflection point, known as point X, marks the beginning of diminishing marginal returns From point A to point C, the output growth slows down as more inputs are added Point B represents the intersection where APP and MPP are tangent to each other.

B, APP is at a maximum and the marginal curve must be below the average curve

Source: http:/ /www.wordiq.com/definition/Production function

The Cobb-Douglas production function is a widely used model that illustrates the relationship between output and inputs Initially proposed by Knut Wicksell, it was later validated through statistical analysis by Charles Cobb and Paul Douglas between 1900 and 1928.

For production, the simplest formula of Cobb-Douglas function 1s (Haughton,

(1) Where: Q is total production, His productive area, Lis labor input a., 1-a are the output elasticity of labor and productive area, respectively

The general productive function is given as follow

Q=AIIXt (2) xi is input variables

Formula (2) is transferred into logarit function as follow

In Q = In A + Ia.i In Xi (3)

One trouble with formula (3) because it does not allow any Xi equals 0 (ln(O) is undefined)

So, solution is the productive function is changed as follow

In Q =In A+ Ia.iln Xi+ I ~izi

Zi are the dummy variables to reflect other influences to total production h

2.1.3 Production factors of farm household

Figure 2.3: The three main factors of production of farm household

Land, labor and capital are referred to as "factors of production" Each factor is plays a unique role in the production of goods

Land plays a crucial role in determining a family's social status within a community, as highlighted by Ellis (1993) It is governed by traditional regulations, including ownership rights, inheritance policies, immigration rules, agrarian policies, and the development of land markets For farmers, land ownership serves as a vital asset, facilitating easier access to financing from banks and financial institutions due to its value as collateral Additionally, research by Tracy (1993) and Price and Palis (1997) indicates that many farmers prioritize owning substantial land, viewing it as a significant inheritance for future generations (cited in Iran Tien Khai, 2001) Thus, land remains an invaluable resource that continues to be highly regarded by individuals today.

Agricultural capital encompasses the production costs associated with both agricultural and non-agricultural resources This includes essential assets like buildings, machinery, equipment, fertilizers, feeds, and inventory of unsold products According to the research by Mundlak, Larson, and Butzer (1997), agricultural capital can be categorized into two types: fixed capital and working capital.

Empirical studies

Tran Tien Khai (200 1) used data of the Project Competitivite de la filiere rizicole dans la region du Mekong, Vietnam including information of rice production from

150 rice farms in four agro-ecological regions during period 1995-1998 Log-linear and Cobb-Douglas models of production and supply function are applied

The production function with log-log is followed:

Ln Q = Ln A+ IaiLnXi + L~iDi and the production function with log-linear is followed:

The equation Ln Q = A + Iaixi + L~iDi represents the rice productivity of a farm household in a given year, where Q denotes the productivity level The angular coefficient, A, plays a crucial role, while Xi encompasses various input variables, including land, labor, and investment costs associated with the farm household for that year.

Di is dummy variables which be able to influent to yielding in terms of farm size, agricultural ecology, etc

To estimate the elasticity of rice supply with rice price and agricultural material price, a simple rice supply function is designed as follow:

The equation Ln Q = Ln A + ∑(xiLnXi) + ∑(Di) represents the factors influencing rice productivity for farm households in a given year In this equation, Q denotes rice productivity, A signifies the angular coefficient, and Xi includes variables affecting rice supply, such as land, labor costs, fertilizer prices, and rice prices Additionally, Di represents dummy variables that impact yield based on factors like farm size and agricultural ecology.

Rice land stock and water availability remain the primary constraints to increasing paddy output While investing in fertilizers yields only marginal returns—except for potash—additional capital investment has minimal impact on enhancing paddy production at the current cultivation level.

In their study "Rice Production," Nguyen Thi Lien, Nguyen Xuan Hai, Pham Hoai Vu, and Trinh Thi Long Huong utilized a productive function similar to that of Iran Tien Khai, represented by the equation Ln Q = Ln A + Ia.iLnXi This research contributes to the understanding of rice production dynamics and highlights the significance of various inputs in the agricultural process.

+ L~iDi to analyze factors which effect to rice productivity

Purano Baneshwor, Kathmandu (2002) used the Cobb-Douglas production function of the following type is estimated:

Y = e'6 Ka Lo-a) U where Y = real GDP, () = constant term (shift factor), L = labor force, K = real capital, U = random error term, and () and a are the parameters to be estimated

This equation assumes constant returns to scale as most empirical growth accounting studies have undertaken A logarithmic transformation of the above equation would be: logY= 8 +a log K + (1- a) log L + U

In the context of Nepal, the primary driver of economic growth is the capital accumulation process Both developing and developed economies experience growth primarily through factor productivity, which is significantly enhanced by intangible elements such as advancements in education and technology, a supportive economic policy environment, and continuous learning.

In the context of Nepal, accurately assessing the contributions of labor and capital to economic growth is challenging due to a lack of clear information on these variables Consequently, the economic growth not attributed to labor and capital cannot be generalized to indicate gains in factor productivity If true accounting standards are applied, factor productivity may actually be a negative contributor to Nepal's economic growth.

Jacklin (2008) in "estimates the production, restricted cost, and restricted profit functions using North Dakota agriculture sector data from 1960-2004" also used the

Cobb-Douglas function to represent the production function characterized as:

Where k = 1 K (number of inputs and time 1 T) Converting the inputs and output into logarithms and adding a stochastic error term, the production function can be represented as:

( } ~ ~ A .n., ' h where a 1, , ak are the input elasticity, and E denotes the error term

Jacklin's thesis employs a quantile regression approach to estimate the Cobb-Douglas production function, contrasting it with ordinary least squares (OLS) regression, which focuses on the mean of the distribution The findings indicate that both traditional OLS and quantile regression yield statistically insignificant parameters regarding the relationship between agricultural inputs and aggregate output for North Dakota agriculture during the period from 1960 to 2004, based on aggregate state-level data.

The Ricardian method, as outlined by Mendelsohn et al (1994), employs a cross-sectional approach to analyze agricultural production, assuming that farmers aim to maximize their income based on the external conditions of their farms This approach highlights that farmland net revenues (V) are indicative of net productivity, encapsulated in a specific equation.

The Ricardian model analyzes how various exogenous factors, including climate variables, water flow, soil characteristics, and economic conditions, influence net revenues in agriculture In this framework, the market price of a crop and its output, alongside a vector of purchased inputs (excluding land), are critical for farmers aiming to maximize their net revenues based on the unique attributes of their farms and prevailing market prices.

The Ricardian approach, as outlined by Mendelsohn et al (1994), serves as the foundational method utilized by J Wang et al (2009) in their analysis, focusing on how farmers select crops and inputs for each unit of land to maximize their returns.

Max rr = IPqiQi (Xi,Li,Ki,IRj,C,W,S)- IPxXi- IPmLi- IPnKi- IPiriRi (5)

Page 15 h where n is net annual income, P qi is the market price of crop i, Qi is a production function for crop i, Xi is a vector of annual inputs such as seeds, fertilizer, and pesticides for each crop i, Li is a vector of labor (hired and household) for each crop i, Ki is a vector of capital such as tractors and harvesting equipment for each crop i,

The vector C represents climate variables, while IRi denotes the irrigation choices made for each crop i W indicates the available water resources for irrigation, and S encompasses the soil characteristics Additionally, P x refers to the prices of annual inputs, and P m signifies the prices associated with various types of labor.

In agricultural economics, Pn represents the rental price of capital, while Pir indicates the annual cost associated with various irrigation systems The expanded Equation (5) builds upon the foundational concepts presented in Equation (4) Key determinants of crop yield and productivity include Li and Ki, which play crucial roles in assessing the physical impacts on agricultural output.

Coelli (1996) assessed technical efficiency in agricultural production using the data envelopment analysis (DEA) method The DEA approach offers significant benefits, including the ability to bypass parametric specifications of production technology and the absence of distribution assumptions for inefficiency terms.

Cristina (1998) employed a constant returns to scale production function, incorporating land, labor, and capital, to assess value added in agriculture This model serves as a valuable tool for development, growth, and macroeconomic analysis, with economists frequently estimating production functions that include both primary factors and intermediate inputs While many estimates assume constant returns to scale, some focus solely on labor and capital as production factors Notably, land plays a crucial role in agriculture, distinguishing it from other sectors where its significance may be minimal.

Analytic framework of this research

Conceptual model is constructed by combining factors of production of farm household and some other factors that physical effect to water melon productivity

The author identifies key factors that significantly influence watermelon production, as depicted in Figure 2.4, the "conceptual framework." This framework highlights two main relationships: first, the correlation between watermelon yield and various input variables, including productive area, labor, chemical fertilizer, pesticides, and seeds; second, the impact of dummy variables such as market information and local agri-extension services on watermelon yield.

In the watermelon production process of Tien Giang province, understanding the relationship between input use variables and dummy variables is crucial By analyzing these relationships, farmers can implement effective strategies to enhance productivity while minimizing costs, ultimately leading to increased profits.

•• I igure 2.4: Conceptual framework ource: the author's survey in 2010 h

RESEARCH METHODOLOGY

Analytical framework

Based on the established production function model and the empirical research findings, the regression model is specified as follows: ln Q = ln A + Σ(Lai ln Xi) + Σ(βi zi).

The proposed regression model for analyzing watermelon yield per hectare during the summer-fall crop of 2010 is expressed as lnQ = lnflo + Jl1lnX1 + Jl2lnX2 + Jl3lnX3 + Jl4lnX4 + fl5lnX5 + fl6l~ + fl7DX7 + fl8Xs + fl9X9 + fl10X10 + J.1 This model incorporates various factors influencing yield, allowing for a comprehensive understanding of the determinants affecting watermelon production.

X 1 is productive area squared of 2010's summer-fall crop

X 2 is land rent cost per hectare of 2010's summer-fall crop

X3 is land preparation cost per hectare of 2010's summer-fall crop

)4is labor cost per hectare of 2010's summer-fall crop

X5 is seed cost per hectare of 2010's summer-fall crop

X 6 is fertilizer cost per hectare of 2010's summer-fall crop

X 7 is growing year of producer of 2010's summer-fall crop

X8 is having agri-extension service in location of 2010's summer-fall crop (O=no, 1 =yes)

X9 is having information from agri-extension of 2010's summer-fall crop (O=no, 1 =yes)

X 10 is market information of 2010's summer-fall crop (O=no, l=yes)

The coefficients B1 to B10 represent the impact of various factors on watermelon yield, including productive area, land rent costs, land preparation expenses, labor costs, seed costs, fertilizer costs, the producer's growing experience, and market information.

!l is error terms (regression residual) which means there are other factors that influence which effects to water melon yield

This research aims to evaluate the economic efficiency of various input factors, including productive area, land rent, land preparation, seed, chemical fertilizer, and pesticide use, on watermelon yield variations Specifically, it will analyze the impact of a 1% increase in chemical fertilizer on watermelon yield percentage changes Additionally, the study will examine the influence of dummy variables, such as agricultural extension services and market information, on watermelon yield fluctuations.

./ Dependent variable: water melon yield per hectare (Q)

The study examines various independent variables affecting agricultural productivity, including the productive area (X1), land rent cost per hectare (X2), land preparation cost per hectare (X3), labor cost per hectare (X4), seed cost per hectare (X5), fertilizer cost per hectare (X6), the growing year of the producer (X7), availability of agricultural extension services in the location (X8), access to information from agricultural extension (X9), and market information (X10).

In the initial phase of watermelon cultivation, employing additional labor, fertilizer, or expanding productive area can enhance yields, but these inputs must be used judiciously Excessive labor can lead to increased yields that do not justify the associated costs, making it an ineffective strategy Similarly, surpassing optimal fertilizer levels can actually diminish yields Additionally, while expanding productive area can initially boost output due to economies of scale, there is a threshold beyond which overextension can hinder management and investment capabilities, resulting in reduced watermelon production Ultimately, the goal is to identify the optimal level of input and area to maximize yields while maintaining profitability.

Q Water melon yield (ton/ha)

AREASQUARED Productive area squared (ha 2 ) -

LAND RENT Land rent cost (Million VND/ha) -

LAND PRE Land preparation cost (Million -

LABOR Labor cost (Million VND/ha) +

SEED Seed cost (Million VND/ha) -

FERTILIZER Fertilizer cost (Million VND/ha) +

EXPERIENCE Growing year of producer (year) +

EXTENSION Having agri-extension service in - location O=No

EXTENINFO Having information from agri- + extension O=No

This research focuses on analyzing cross-sectional data regarding inputs and outputs in watermelon production across seven districts in Tien Giang, with data collection conducted in the third quarter of 2010.

The output is the water melon yield of production (Q = Y /ha) Output is measured in tons per hectare

The productive area squared (AreaSquared) is estimated by the cultivated land used for water melon production It is measured in squared hectare

Land rent costs in Tien Giang are measured in millions of Vietnamese Dong (VND) per hectare Watermelon cultivation is challenging in previously cultivated soils due to the prevalence of diseases To ensure successful growth, farmers should utilize new soils or implement intercropping systems that allow for watermelon cultivation every 2-3 years Consequently, farmers are compelled to rent high-quality soil across the region to maintain productive crop cycles.

The land preparation cost (LandPre) for watermelon production is quantified in millions of Vietnamese Dong (VND) per hectare This cost encompasses expenses related to plastic covers, ash, coir, and irrigation Utilizing plastic covers enhances watermelon cultivation by retaining moisture, controlling weeds, and mitigating certain diseases and pests Additionally, ash and coir are incorporated into the soil prior to applying the plastic cover The irrigation cost for watermelon is minimal and is included in the overall land preparation expenses.

The labor cost (Labor) used in the model included the population work in agriculture (hired and household) It is calculated by total cost of each working day

The household labor cost is assessed in millions of Vietnamese Dong (VND) per hectare and is determined by multiplying the total household working days by the opportunity cost In this study, the author uses the hired labor cost as a basis for calculating household labor expenses For example, if hired labor is compensated with 4 million VND for two months, the same amount is applied to calculate the household labor cost.

The seed cost (Seed) 1s measured m million of Vietnamese Dong (VND) per hectare

Fertilizer costs encompass the total weight of nitrogen, phosphate, potassium, complex fertilizers, and cattle manure utilized during various agricultural stages, including land preparation, seedling support, fruit support, and sideline production activities Additionally, this variable accounts for pesticide expenses, which include insecticides, fungicides, herbicides, plant protection products, disease prevention treatments, and growth stimulants The measurement is expressed in millions of Vietnamese Dong (VND) per hectare.

The growing year of producer (Experience) is estimated by year numbers which producer has in their water melon production process It is measured by year number

The having agri-extension service in location (Extension) is measured by dummy variable

The having information from agri-extension is measured by dummy variable as well

Market information is crucial for agricultural production, especially in watermelon cultivation In Tien Giang, farmers often expand their watermelon fields without proper market research, leading to overproduction and subsequently lower prices during peak seasons like New Year Holidays Additionally, watermelon prices are affected by the dynamics of demand and supply in city and nearby provincial markets, highlighting the need for better market insights to optimize production and pricing strategies.

Page 23 h agricultural prices reflects the market risk faced by agricultural producers It is measured by dummy variable

Agricultural production is significantly influenced by various natural conditions, including climate change, unpredictable disasters like floods, and seasonal variations, as well as pest and disease invasions Scientific studies, such as those by Matthews and Wassmann (2003), Parry et al (2004), and Tao et al (2006), provide compelling evidence of the strong impact of climate change on agriculture Consequently, this research does not focus on climate change as a variable.

Data collection and sample distribution

The minimum sample size for this study using the proportional sampling formula in Mason, R.D (1999:292) (cited in Tran Van Long, 2010) where: n = p( 1-p )(Z/E) 2 n = minimum sample size

Z = 1.96 at 95% confidence interval obtained from standard statistical table of normal distribution p = estimated ratio of farm households which plant water melon in Tien Giang (p P%)

(1-p) = q = estimated ratio of farm households which do not plant water melon in Tien Giang (q P%)

Applying the above equation, the minimum needed sample size needed is about 97

So the total 177 respondents is chosen to interview directly is larger than the minimum needed sample size It will be good representative for this research h

The following table is the sample size is distributed according to water melon output in 2008 of each area across Tien Giang province

Table 3.2: Sample size of each district across Tien Giang province

Water melon yield of each district in 2008 Percentage Sample size

Source: Tien Giang's Rural and Agriculture Development Department

Based on Table 3.2, My Tho City and Go Cong Town have a total of only two questionnaires, which is insufficient to significantly impact the research results Therefore, the author will add one questionnaire to the total for Cai Be and one more to the total for Cho Gao.

The Tien Giang Rural Development and Agriculture Department currently lacks statistics on the number of households involved in watermelon cultivation To address this gap, the author employs a proportional sampling framework to select a research sample based on the watermelon output from each district This approach allows for the calculation of sampling distribution proportions, facilitating the collection of essential information regarding which households have planted watermelons and which have not.

14 samples of Tan Phuoc, 53 samples ofCai Be, 30 samples ofCai Lay, 20 samples ofChau Thanh, 33 samples ofCho Gao, 18 samples of Go Cong Tay and 9 samples of Go Cong Dong

3.2.4 Pre-testing of the questionnaires

The questionnaire, developed and pre-tested with 20 experienced watermelon farmers through face-to-face interviews, underwent a thorough refinement process The author dedicated 30 to 45 minutes at each farmer's field to gather valuable insights and calculate costs associated with watermelon production The final version of the questionnaire was completed based on their crucial feedback.

The author reached out to Mr An, the Director of the Agricultural Seed Center in Tien Giang Province, to discuss the research concept Mr An provided valuable guidance on how to approach potential interviewees and facilitated introductions to the district representatives responsible for the study.

The author conveyed the overarching and specific concepts of the research to participants by organizing small meetings with approximately 10 respondents each Over a three-month period from October to December 2010, the primary survey was conducted through face-to-face interviews with farmers, allowing for direct data collection.

3.2.6 Limitation of data source and collection

Farmers in the region often do not maintain detailed records of their crop data, leading to discrepancies during interviews where they must recall information from memory This inconsistency is further compounded by the mobility of farmers, resulting in similar data being reported across different districts, such as Cai Be, Cai Lay, and Go Cong Tay For instance, Mr Nguyen Van Be, who has a decade of experience growing watermelons across various districts in Tien Giang, noted only minor variations in chemical fertilizer usage and labor costs among them It’s important to highlight that a farmer can typically provide insights for 2 or 3 questionnaires across different districts.

Analysis methods

In order to consider several approaches of water melon's yield will be used in this study:

The descriptive statistics is the first method that the author use in this research to analyze the relationship of each independent variable to dependent variable

The author employed linear regression analysis using SPSS (Statistical Package for the Social Sciences) to identify significant and optimal variables Additionally, structured interviews were conducted to gather reliable data on watermelon cultivation, utilizing well-designed questionnaires administered to individuals and representatives of specific organizations The collected information was meticulously analyzed to align with the investigation's objectives.

In addition to the linear regression model, this research employs SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to evaluate watermelon cultivation The author assesses the strengths and weaknesses, as well as the opportunities and threats associated with this agricultural practice The findings from both methodologies will inform the conclusions and recommendations presented in the study.

This research aims to identify the factors that positively and negatively influence watermelon yield in Tien Giang province through a comprehensive literature review and data analysis using linear regression models and SWOT analysis The findings are expected to provide significant insights for farmers, helping them enhance their watermelon production.

The results of this research will suggest suitable policies for government to encourage farmer plants more water melon and improve their living standards h

ANALYSES OF WATER MELON PRODUCTION IN TIEN

Introduction ofTien Giang province and its water melon production

4.1.1 Overview of Tien Giang province

Tien Giang is an agricultural province located in the Mekong River Delta, a vital economic region in southern Vietnam Situated approximately 70 km south of Ho Chi Minh City and 90 km north of Can Tho City, Tien Giang spans coordinates of 105°50' - 106°45' east longitude and 10°35' - 10°12' north latitude The province shares its borders with Long An and Ho Chi Minh City to the northeast and north, Dong Thap province to the west, and Ben Tre and Vinh Long provinces to the south, while the East Sea lies to the east.

Tien Giang province, located along the northern shore of the Tien River, a tributary of the Mekong River, spans 120 km in length Covering a natural area of 2,481.77 km², Tien Giang represents approximately 6% of the Mekong River Delta, 8.1% of the southern key economic region, and 0.7% of Vietnam's total land area.

Tien Giang features a predominantly flat terrain with neutral alluvial soil along the Tien River, covering 53% of the province, making it ideal for diverse plant and animal life As of 2009, the population of Tien Giang was approximately 1.67 million, accounting for about 9.8% of the Mekong Delta's population, 11.4% of the southern key economic region, and 1.9% of the national population Strategically located, Tien Giang is the second province from Ho Chi Minh City, following Long An, and consists of 10 district-level administrative units.

(8 districts, 1 city, 1 town) and 169 commune-level administrative units, of which,

My Tho city is the second grade city

T'en Giang has equatorial and monsoon tropical climate, so the average temperature islhigh and hot all year Annual average temperature is 27- 27.9°C There are two

Tien Giang experiences two distinct seasons: a dry season lasting five months from December to April and a rainy season from May to November The region has low average rainfall, ranging from 1,210 to 1,424 mm per year, with precipitation decreasing from north to south and from west to east The average humidity in Tien Giang is between 80% and 85% Wind patterns are characterized by two main directions: north-east winds during the dry season and south-west winds during the rainy season.

I source: http://www tiengiang gov vnlbando/tiengiang.html

14.1.3 Soil condition fbe total natural land of the province is 236,663 hectare, including major land groups as follows: f I Alluvial soil: 53% of the total natural area (125,431 hectare), accounting for large rarts of the districts such as Cai Be, Cai Lay, Chau Thanh, Cho Gao, My Tho city h and one part of Go Cong Tay where has the fresh (sweet) water source This is the most favorable soil for agriculture and it is used the whole

Salinity soil covers 14.6% of the total natural area, equating to 34,552 hectares, and is predominantly found in Go Cong Dong, Go Cong town, Go Cong Tay, and parts of Cho Gao This soil type, while possessing favorable characteristics similar to alluvial soil, is significantly impacted by saline water from the sea during the dry season.

Acid sulphate soil covers 19.4% of the total natural area, amounting to 45,912 hectares, primarily found in the low-lying regions of Dong Thap Muoi, particularly in the northern parts of Cai Be, Cai Lay, and Tan Phuoc districts.

Mound sandy soil, covering 3.1% of the total natural area (7,336 hectares), is primarily found in the districts of Cai Lay, Chau Thanh, and Go Cong Tay, with the highest concentration in Go Cong Dong This type of soil is characterized by its elevated terrain and light mechanical composition, making it ideal for residential use and the cultivation of fruit trees and vegetables.

The province predominantly features alluvial soil, comprising 53% of its total area, which is beneficial for cultivating high-yield rice fields and orchards Additionally, 19.4% of the land (45,912 hectares) consists of alkaline soil, while 14.6% (34,552 hectares) is classified as saline alluvial soil In recent years, efforts have focused on reclaiming and expanding production areas, as well as enhancing crop diversity through the development and exploitation programs of Dong Thap Muoi and the Go Cong fresh-water initiative, which have successfully increased the productive capacity of the region.

Table 4.1: Land use structure at Tien Giang province

Until now, over 90% the total area was used with following objectives:

:soil type Square Structure Square Structure Square i Structure

:The total square 233.922 100.0 232.609 100.0 236.663 i 100.0 ii Ag;t.i.nllhu-al soil 165.408 70.7 184.883 9.48 181.505 76.69

IL De(lic-ate(l ;o;:oil 10.484 4.48 15.005 6,45 15.887 6.713

Source: http://www.tiengiang.gov.vn/xemtin.asp?idcha5&cap=3&id8

4.1.4 Water melon production in Tien Giang

Watermelon has become a significant cash crop for farmers in various provinces, particularly in the Mekong Delta region, where it serves as an alternative to rice Recent advancements in agricultural practices, such as the use of plastic sheets for soil coverage and the application of specially formulated fertilizers, have contributed to the cultivation of high-yield, widely adapted watermelon varieties.

Rice cultivation in Tien Giang has a long history, yet farmers face low incomes of only 3-4 million VND per hectare due to an average annual production of 14.2 tons per hectare from three rice crops The yields per crop are 4.5 tons for the first, 4.2 tons for the second, and 5.5 tons for the third Additionally, farmers encounter significant risks from pests, diseases, and adverse weather conditions To enhance profitability, recent practices encourage rotating watermelon cultivation with rice, utilizing combinations such as two rice crops and one watermelon crop, or alternating between rice and vegetables Watermelon cultivation can yield an impressive average of 22 tons per hectare per crop, with potential peaks of 25 to 30 tons per hectare under optimal conditions.

- - - - - - - - - - practices So a farmer can get the average net income is 20 - 25 millions VND/hectare after deducting all expenditures Clearly, income from water melon is higher a lots than income from rice

Nowadays, water melon is planted year around and is planted a lots in following seasons: Christmas, Lunar New Year, after Lunar New Year and summer

Table 4.2: Water melon productive area, water melon output in Tien Giang in 2008

Water melon Productive City/District output (ton) area (ha)

Source: Tien Giang's Rural and Agriculture Development Department

Watermelon is cultivated globally, including in Vietnam, driven by high demand for fresh fruit and processed products like canned slices and juice The world’s watermelon production has seen a significant increase, growing from 47 billion tons in 2004 to 93 billion tons in subsequent years.

Page 33 h billion tons in 1996 Production of other melon gained one third of water melon production

China dominates global watermelon production, yielding 60 billion tons in 2002, while other notable producers include Turkey, Iran, the USA, Egypt, and Mexico Additionally, China leads in overall melon production, contributing 50% to the world's supply, with Turkey (6.1%), Iran (4.4%), the USA (4.2%), and Spain (3.9%) following Despite its significant production, China does not export watermelons or other melons due to high domestic demand.

Spain is a leading exporter of honeydew and cantaloupe, with over 300 thousand tons shipped annually, followed by Mexico and Costa Rica While the USA imports melons, it also exported 98.1 billion dollars' worth of melons in 2004, primarily to Canada (85.2 billion dollars) and Japan In Asia, Malaysia emerged as a significant exporter of watermelon, shipping 70 thousand tons in 2003, making it the fifth largest exporter globally, following Spain, Mexico, the USA, and Hungary.

Melon wor1d production source: FAO redr- from USDA H0111culturel &

Source: Do Minh Hien, Nguyen Thanh Tung 2006 h

The United States is a leading importer of melons, with 100.6 billion USD in imports in 2004, primarily from Mexico (91.2%), followed by Costa Rica (2.4%) and Guatemala (3.5%) While the U.S ranks second in overall melon imports, Germany holds the title for the largest importer of watermelons Additionally, France and England are significant importing countries for honeydew and cantaloupe.

Major importing Md exporting countries for melons of the world Source: Horticultural &

Figure 4.2: Major importing and exporting countries for melons of the world

Source: Do Minh Hien, Nguyen Thanh Tung 2006

Analyses of water melon production in Tien Giang province

This chapter discusses the results of the relationship between independent and dependent variables using SWOT analysis and econometric methods The data will be analyzed using SPSS 15.0, focusing on descriptive statistics and linear regression modeling.

SWOT ANALYSIS FOR WATERMELON'S CULTIVATION

• Tien Giang has been one of the leading provinces for water melon cultivation in off-seasons for more than 10 years

• Farmers in Tien Giang have been applying advanced cultural practices as well as new varieties for higher productivity, quality and profitability of water melon

• Many farmers are very experienced in water melon's cultivation

• A large quantity of marketable water melon fruits could be collected and provided to urgent needs of markets at a particular time

• There were still farmers not fully applying advanced cultural practices transferred from training courses due to problem of understanding of these farmers

Farmers often cultivate watermelons on a large scale without market research or expert guidance, leading to oversupply and consequently lower prices during holidays This lack of access to market information from research organizations contributes to the challenges faced by growers in optimizing their investments and yields.

• Price of water melon is very much influenced by fact of demand and supply in city markets h

• It should be considered that market information and planning for cultivated area very important to farmers

The demand for watermelons is significant, yet domestic and exotic varieties from Vietnam face competition in recent years High-quality melons from Thailand, alongside the growing fruit requirements of Malaysia and China—estimated at 140 kg per person in 2010—highlight the potential market However, the cultivated area for watermelons may decline due to risks from pests, diseases, and adverse weather conditions like flooding and drought Despite these challenges, the relatively stable prices for watermelons compared to other fruit crops suggest that farmers could still benefit Additionally, if production meets market demands, there is potential for better pricing in markets such as China, Laos, and Cambodia.

4.2.2 Description of water melon production in Tien Giang through farm survey

Table 4.3 presents key statistics for the 177 participants interviewed, including the minimum, maximum, mean, and standard deviation for each variable The minimum represents the lowest value, while the maximum indicates the highest value observed The mean provides the average value of each variable, and the standard deviation reflects the variability or dispersion of the data points around the mean.

Table 4.3: Descriptive statistics of yield and input uses variable of water melon production

Unit cost of a water melon ton/ha (million VND) 1.68 6.18 3.06 sts other than Fertilizer and Pesticide (million VND) 34.60 55.62 45.80

Land rent cost (million VND) 5.00 25.00 15.40

Land preparation cost (million VND) 3.73 5.80 4.82

Bed making cost (million VND) 3.00 5.63 4.55

Taking care cost (million VND) 5.00 20.00 8.70

Chemical fertilizer cost (million VND) 1.24 9.69 7.59

Nitrogen fertilizer cost (million VND) 40 3.57 2.70

Phosphate fetilizer cost (million VND) 54 4.04 3.00

Potassium fertilizer cost (million VND) 30 2.39 1.89

Stimulation product cost (million VND) 48 10.57 8.73

Age of producer (year old) 20 59 34

Schooling year of producer (academic year) 0 12 7

Growing year of producer (year) 1 17 6

Source: the author's survey in 2010

Watermelon yields range from a minimum of 12 tons to a maximum of 30 tons per hectare, with an average yield of 22.8 tons per hectare The total cost of cultivation varies significantly, with a minimum of 40.37 million per hectare, a maximum of 78.36 million per hectare, and a median cost of 68.27 million per hectare This indicates that while watermelon is a high-yielding crop, it requires careful management and attention.

Among the 177 interviewed farmers, the average age is approximately 35 years, with ages ranging from 20 to 59 Farmers have an average of 7 years of schooling, with educational attainment varying from 0 to 12 years Additionally, the average experience in growing watermelons is around 7 years, with a range of 1 to 17 years These findings highlight the challenges of watermelon cultivation, as the minimum age of farmers is 20, indicating the necessity for time to gain experience and knowledge in this complex agricultural practice.

Various factors influence watermelon yield, including the size of the productive area, land rental costs, labor expenses, fertilizer prices, soil type, and the farmer's age, education level, and experience Additionally, access to market information and agricultural extension services plays a crucial role in optimizing production.

In 2010's summer-fall crop, almost of farmers gain the high yield According to the above figure 4.3, water melon yield gained mainly from 20 to 25 tons/ha

Figure 4.3: The water melon yield of 2010's summer-fall crop

Source: The author's survey in 2010

4.2.2.2 Input uses and other factors of water melon production

Out of 177 interviewers, 56.49% (100 interviewers) consistently prioritize market information, while 43.51% (77 interviewers) do not Among those who do pay attention, price emerges as the most significant factor influencing their market information considerations.

In Tien Giang, located in the Mekong River Delta of Vietnam, agriculture plays a crucial role in the local economy To enhance agricultural productivity, the region has made significant improvements to its agricultural extension services across various districts A recent survey revealed that 55.93% of respondents reported having access to these agri-extension services, while 44.07% indicated they do not.

A survey of 78 interviewers revealed that a lack of agricultural extension services in their area hinders access to essential farming knowledge These services are crucial for guiding farmers on seed selection, fertilizer use, and crop management Conversely, 99 interviewers confirmed the presence of agricultural extension services, with 96 reporting that they received valuable information from these resources, while only 3 indicated they had not accessed agricultural guidance.

4.2.2.2.3 Growing year of farmer (Experience)

Experience plays a crucial role in agricultural development, with 14% of farmers having seven years of experience Additionally, 12% of farmers possess six years of experience, while 10% have three years The distribution continues with 7% of farmers having eight or nine years of experience, and 5% with two or eleven years Furthermore, 3% of farmers have twelve or thirteen years of experience, while 2% have one or ten years Notably, only 1% of farmers have 2.5 years of experience.

4.2.2.2.4 Schooling year of farmer (academic year)

There are 14% farmers with 5 academic years, 13% farmers with 12 academic years, each 12% farmers with 7, 10 academic years respectively, 11% farmers with

In a study of educational attainment among farmers, it was found that 9% have completed 9 academic years, while 7% have 6 academic years Additionally, 6% of farmers have achieved 8 academic years, and 5% have 11 academic years Furthermore, 4% possess 3 academic years, with 3% having 0 or 2 academic years, respectively, and only 1% of farmers have completed 1 academic year.

In the total 177 interviewers, their age from 20 to 25 years old is 11%, from 26 to

The age distribution of farmers shows that 25% are 30 years old, 27% are between 31 and 35, 12% are between 36 and 40, 14% are between 41 and 45, 5% are between 46 and 50, and 6% are over 50 The farmers' ages range from 20 to 59 years, with an average yield of 20 to 30 tons per hectare Notably, a 59-year-old farmer achieves a yield of 30 tons per hectare, while a 20-year-old farmer yields 25 tons per hectare, and a 28-year-old farmer produces only 12 tons per hectare.

4.2.2.2.6 Land type to plant water melon

Weather and soil conditions play a vital role in watermelon production, necessitating crop rotation and careful selection of planting areas Farmers today have the flexibility to choose optimal soil types for their watermelon crops, with three primary options being alluvial soil, dark alluvial soil, and acid sulfate soil.

Watermelon is a demanding crop that requires constant care, which is a primary reason for the stagnation or decline in yield despite an increase in productive area Currently, the productive area spans 36 hectares, yielding only 20 tons per hectare In contrast, smaller productive areas of 4 to 5 hectares can achieve yields of up to 30 tons per hectare, highlighting the importance of intensive management over sheer acreage.

CONCLUSIONS AND RECOMMENDATIONS

Conclusions

Recent findings indicate that increasing inputs is no longer effective in enhancing watermelon productivity, and access to agri-extension services has not significantly impacted yield Farmers often use excessive inputs, necessitating a reevaluation of their usage to optimize costs and increase profits Additionally, provincial authorities should focus on improving the quality of information provided by agri-extension services and organize campaigns to encourage farmers to engage more with these resources.

Currently, soil conditions have not significantly impacted watermelon yields, as producers actively seek the ideal soil types across the province However, without effective methods to mitigate soil diseases and prevent soil degradation, watermelon production may face declining yields in the future.

To ensure optimal watermelon cultivation, it is essential to focus on improving agricultural practices and care rather than simply increasing input usage Excessive fertilizer application does not necessarily lead to higher yields For producers working with acid sulphate soil, it is crucial to apply more phosphate (P2O5) during the land preparation phase Comparative data indicates that the appropriate phosphate fertilizer amount for acid sulphate soil ranges from 74 to 81 kg P2O5/ha, differing from the requirements for other soil types.

To enhance watermelon yields, it is crucial for farmers to select productive areas that align with their growing conditions The research indicates that watermelon production is nearing its maximum potential, highlighting the need for improved cultivation practices to boost productivity effectively.

Page 63 h i practices and the production techniques to a higher level, in which improve seed quality, find out new seeds and use suitable fertilizer level are crucial methods

Producers believe that watermelon production yields higher income than rice, leading them to focus primarily on maximizing yields without considering critical factors such as market demand, supply levels, and competition This oversight can result in market surpluses and subsequently lower prices, diminishing farmers' profits To enhance profitability, farmers should aim to minimize costs and strategically reduce the quantity of watermelons they supply to the market, thereby increasing prices Additionally, provincial authorities must provide updated market information and forecasts, educating farmers on how to access this data to ensure they supply the right quantity of watermelons at optimal times.

Currently, the watermelon varietals in Tien Giang are limited, primarily consisting of Super Roan Chau and Phu Dong, as farmers largely rely on their growing conditions There is a lack of focus on market demand for diverse varieties Aside from these two main types, other watermelon varieties are cultivated in smaller areas due to their vulnerability to diseases and lower yields.

Watermelon cultivation offers stable income opportunities for producers, as it is a short-term crop with a 60-day growth cycle, allowing for timely market supply Additionally, watermelon prices often surpass those of rice, incentivizing farmers to invest in higher yields and cost-reduction strategies As a result, many farmers have significantly improved their livelihoods through watermelon farming.

Recommendations

Tien Giang farmers, known for their extensive experience in watermelon cultivation, achieve high productivity and quality Their self-designed production methods are effective, often meeting established thresholds However, the current practices are largely automated and focused on individual goals To enhance productivity, farmers should refine their cultivation techniques and cultural practices while developing a strategic cultivation plan to supply specific quantities to targeted markets.

Farmers often face losses due to low crop prices, making it essential for them to maximize watermelon yields while minimizing costs to increase profitability This involves using resources efficiently, such as applying the appropriate amounts of chemical fertilizers and pesticides, and enhancing cultivation techniques Additionally, by limiting watermelon production, farmers can create scarcity in the market, potentially driving up prices and improving their profits.

To address the challenges faced by watermelon growers, it is essential for various organizations to offer support in developing tailored cultivation plans and investment strategies This assistance will enable farmers to produce high-quality watermelons that meet market demands, ultimately ensuring profitability Local authorities should play a crucial role in facilitating watermelon development through targeted support initiatives.

Provincial authorities of Tien Giang have considerations "water melon" as potentially fruit for poor farmers gradually to become the wealthy Firstly, they

Page 65 h should orgamze R&D department (Research & Development department) to research all characteristics of family Cucuibitaceae clearly and understand clearly one by one due to profitably sustainable development of water melon Then they should have many plans, many actually supporting programmes to introduce water melon to all farmers Cultivated technical support courses on cultural practices of water melon are organized regularly for all farmers Therefore inexperienced farmers can study knowledge from agricultural engineers and professional growers though training courses and field workshops Objectives of these training courses are to provide basis knowledge of water melon for fresh farmers, to update advanced cultural practices for experienced farmers, especially to help them transfer experience and learn each other In addition to, provincial authorities should have suitable policy to encourage and to support growers and other members such as wholesalers, distributors, retailers

Provincial authorities should analyze the production capabilities of neighboring provinces like Long An, Tra Vinh, and Binh Thuan, while also investigating foreign markets in countries such as China, Thailand, and Spain It is essential to forecast the demand for watermelons during key holidays like Christmas, New Year, and Lunar New Year, as well as to research and predict market prices This will enable farmers to produce the required quantities at competitive prices Additionally, authorities must develop strategies to mitigate the risks of oversupply and low prices.

Provincial authorities must prioritize agricultural extension services in each district, enhancing their quality through skilled human resources By improving the information provided by these services, farmers can achieve greater efficiency and productivity in their agricultural practices.

The national environment and resources department, along with the Tien Giang provincial authorities, must develop effective land use policies to enhance watermelon productivity, as old soils are no longer yielding good crops Currently, farmers are compelled to rent land throughout the province, which may lead to land degradation as they are encouraged to increase cultivation To combat this issue, a land structuring strategy that includes a two-year fallow period should be implemented, and farmers should be incentivized or mandated to adhere to these practices Without these measures, the risk of pests and diseases will escalate, affecting both old and newly cultivated soils due to the continuous planting of watermelons in the same areas.

To enhance market appeal and meet consumer demand, it is essential to study and introduce a diverse range of watermelon varieties to farmers This includes round-shaped fruits, oblong watermelons with green striped skin, red-fleshed varieties, striped fruits with yellow flesh, and particularly high-quality seedless options By diversifying their watermelon offerings, farmers can attract a wider clientele and improve their market presence.

LIMITATION

The production function illustrates the non-monetary relationship between physical input variables and the yield of watermelons, focusing solely on the input use without considering prices or costs While it is essential to avoid monetary variables, the author faced challenges in isolating the impact of costs like land rent, land preparation, and labor from the research model.

Farmers often lack the habit of meticulously recording details about their crops, leading to discrepancies in data accuracy The author invested significant time in surveying these farmers, who also struggled to recall precise information about their practices Consequently, this may result in data that is somewhat inconsistent with actual farming conditions.

Results of this research are just suitable in short-run The author has not had enough data to prove those results in long-run h

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Vietnam- Netherlands Programme For M.A in Development Economics

DETERMINANTS OF WATER MELON PRODUCTION FUNCTION OF 2010'S SUMMER- FALL CROP IN TIEN GIANG PROVINCE

I am a student of Vietnam - Netherlands Programme, in my research plan, I come back to Tien Giang to find out the determinants of water melon production process

This article explores the various factors influencing watermelon production at the household level It aims to identify both the positive and negative elements that impact watermelon productivity, with the goal of enhancing overall yields for each household By analyzing these factors, we can develop strategies to improve watermelon farming practices and increase harvest efficiency.

Participation in this discussion is entirely voluntary, with households selected at random The information collected today is solely for research purposes We kindly ask you to answer a few questions below, and we sincerely appreciate your family's cooperation.

Question 1: How many tons of water melon per hectare do you gain in 2010's summer-fall crop?

Unit: tons/ha 2010's summer-fall crop

Question 2: Would you tell me how many hectares you planted water melon in 2010's summer-fall crop?

Unit: ha 2010's summer-fall crop

Question 3: Would you tell me how much your land rent cost per hectare is?

Land rent cost (million VND)

Unit: million/ha 2010's summer-fall crop

Question 4: Would you tell me how much your land preparation cost per hectare is?

Unit: million/ha 2010's summer-fall crop Land preparation cost (million VND)

+ Irrigation fuel cost (electronic, petrol or oil) h i

Question 5: Would you tell me how much your seed cost per hectare is?

Seed cost +Seed amount (seed a.i) +Seed amount (million VND a.i)

Question 6: Would you tell me how much your labor cost per hectare is?

Labor cost (million VND) + Bed making cost + Sowing cost + Pruning cost + Harvesting cost + Transport cost +Taking care cost

Question 7: Would you tell me how much your fertilizer cost per hectare is? Table 1: The fertilizer cost per hectare

Unit: million/ha 2010's summer-fall crop Fertilizer cost (million VND)

+Nitrogen fertilizer cost + Phosphate fertilizer cost + Potassium fertilizer cost + Pesticide fertilizer cost + Insecticide fertilizer cost + Fungicide fertilizer cost

+ Herbicide fertilizer cost + Water melon stimulation fertilizer cost

Table 2: The chemical fertilizer amount per hectare

Unit: kg/ha 2010's summer-fall crop Chemical fertilizer amount

+ Nitrogen amount (N) +Phosphate amount (P 2 0 5) +Potassium amount (K 2 0)

Question 8: Would you tell me which soil type you choose to plant water melon in 2010's summer-fall crop?

2010's summer-fall crop + Alluvial soil

+ Dark alluvial soil + Acid sulphate soil

Question 9: Would you tell me the total cost that you used for 1 hectare is how much?

Question 10: How old is producer/farmer?

Question 11: How many schooling years is producer in? (academic year)

Question 12: How many growing year is producer in? (experience)

Question 13: Is there any agri-extension service in your location?

Question 14: Do you receive any information related to water melon from agri- extension?

Question 15: According to you, is the market information important to your water melon production process? If yes, what information that you care the most?

Yes: Information that you care the most Reasons

Question 16: How did your living standard change since you planted water melon?

I sincerely thank his/her cooperation

Table 1: Correlations among water melon yield and input uses variables u -eott"'• c - ~

- - th ,FotalziO' -omlon lleWt -~oorr -~t ,_,,.,.t ->Wt ,., -~ ""'~VNll ~1 ODG 001 488 00! O:i'O C I h~~~~~-~,db~, ~ -;~~.~~:,== ~ ~.w¥.4 -~~~ ~;~~"J -~:~-~ ~+ -~:~g, J -~+ -~J -~~~r+ -~~!£~+ -:~~~ ~f -~:~~.-+ -:~~~ ~~ ~+ -~+ -~-c ~ ~.- ( - ~~- : ~~ :~~- : ã : : : :~ .113!1 ~: ã : : : : -::i hcm~~~~-; -i~;;~~~~ -r 7 !~~:~ -~.:~,t -~.:~~~ ~:rl -7,,.~,.+ -~.:~~-~ 2 '"~,f -~,*~~ ~~~ -7,.;~~~ ~-~:Hr 7 o~ i -~+ -~-~:Hr -7 ,w~ -~t -7 ,*,f -7,~, -~

117 117 117 ., ~ -~ -11111ã '""" z11ãã 21gãã uzã Mil 1 mãã u1•• -~ã "' '" h~;;'~-~~~~ ~~~-~~~~~ r -~-~~ ~~~ ~-~~ -~-~ -7,ãm~ ~Ơ.4 -d.,~ + -~ ~ ~ -~ • ~.+ -~.:~~~~ -Ơ~ ~ ~ ~-~~ ~~ -7.~:~ ~+ -~+ -~1 ~

~~~~~ ~~~-~~~~~,~ ~ -7,~ -T,~~~+ -~J -:~;:~-~ ~+ -~4 -~ • ~ + -~4 -~:~~:+ -~4 -_*::~ ~-~~:4 -,"~'+ -~.T.,~,t -,:~~,.-~ ~7+ ~:~*r~ ~-~ -~ h~~-. ~"-to~o;F, ~;;~~ r 7.,~~.~ ~ ~ + -~~~"-~. -*,.~ r -~.OM~ ~,~ ~ ~'~"+ -".M~O~ ~+ -"-~~ã:~ -T.~ ~.M~.~ ~+ -.T.:~~ ~.;~~-~ -i.~~' t qt -~.; -~ 81!1-~~ sn 00! 1911 m ooa c h~~~ ~~~~. ~~~~~~=,== ~ -7,~ -7,=~ ~~~,.d. -~~ -~~~.+ -~4 -~ :~".+ -~-~g,.M -~.:~ ~.:~~4 -~:~ ~4 -~~~;+ -~.:~ ~~~u-f -~.:~-+ -~.~~"~. -" 1 ~ ~~~~. -~~~~~~.M; ~ ~:8:4 -~:~ ~-~~,4 -~-~:~ ~-~:~.-+ -7.-.~~~d -~ ~~;+ -~,:~:4 -~+ -~-~~~4 -~:~ ~-~~.~ ~-:~~~+ -.f :~ ~~~"-~ ~-~~~+ -~-~~~~ ~-: -~ h~~~.-~,~. -~';_~M; r 7.~ -T,~ ~-'*"-d -T.~ -T,_,~,t -~~ ~+ -~.,ffi ~ -7 ~~ ~-~~~~ -f.~ ~.:~~~ ,_,f.r~ f,'"~ ~~ i.u~rf -~ • ~.-~ ~; -~

VNll Slg.~l 071 ooa 081 001 031 MI 071 000 000 IIOC 0 ;.-12-t*i~ -:~: 117 • : -~~-ã : : : ã:~;:ã tn 1~ ã ã : ã ã ~ t- _.;;;;;;;;-~,;;;;-~ -i-'-"-= + ~,;f ~.r -~: ;;"~ -,JlF.! f -,J;.;'"-. + -l; £".,f -_,.;;;, r -,; :;;"~ -.¥~;;, r -~::;,~~ -.£~~Hr -,;.:irr ~.ii::.~ ,:iil:~~ -~;;r,-,t -~,:;;::rl r ::: ::;;~~ ~,i;.~rl -7 1 r -::i

VN:IJ S~g.~, 021 m 1 t-~~~ .~~ -::i'i;;;;~ . -t -~~~Hr 7 ,*w~ ~~~ã"r~ -f,.:~ ~~~~~ ~~ "-:~~~ -T,,~Fr ~-'~F~ ~.#:~~ ~-~-:~ ~-~~Hr -,~~;~ -j,~~ ~-ffi,Hrl -::i.,~-9 -~rl -7.~1 r -::f

IMJJ lllg.~J 047 ue: GH an ,12 "" OOl In 091 - c ~ "'"'"'~"'':"""'""'"'-,. -~~1=_=_."~-:~"'.=. 1 ~ • !#:~H -~: *"ã+ -.lli:~-~ ~.:*' + -*+ -~:+ ~- lll O+ -*~ ~ :;J 4 -.* ~ _,'":;,j. -." ~ -: :il";=l ~~=~ ~ *'ã"'+ -i::ou'*"~ -~ffi=lr -i.; -~

~~~~~ -l'i;;;;.,-~ + -.¥~~ ~~~~d -~-~::+ ~~ -i~ ~-~::+ ~~~~"Hr ~.!#~;~ ~ ~~4 -*:~-r -l~~-+ -.!#:Hr - m rl -l.:fr.-~ ~'+ ~mrl -:.~ •• Hr ~~c ~

Table 2: The relationship between water melon yield and land type

Land type N 1 alluvial soils 91 22.69 dark alluvial soils 16 22.71 acid sulphate soils 70 23.10

The article discusses the display of means for groups categorized into homogeneous subsets, highlighting that the harmonic mean sample size is 34.178 It notes that the group sizes are unequal, necessitating the use of the harmonic mean of these sizes However, it is important to mention that the Type I error levels cannot be guaranteed in this context.

Table 3: The relationship between water melon yield and having information from agri-extension

Having information Std Error from agri-extension N Mean Std Deviation Mean

Yield (ton/ha) no 81 23.16 3.450 383 yes 96 22.59 3.615 369

Eaualitv of Variances !-test for Eaualitv of Means

95% Confidence Interval of the Mean Std Error Difference

F Sia I df Sia 12-tailedl Difference Difference Lower Upper

Yield (ton/ha) t:qual variances

Table 4: The relationship between water melon yield and having agri-extension service in location

Having agri-extension Std Error service in location N Mean Std Deviation Mean

Eaualitv of Variances !-test for Eaualitv of Means

F Sio t df Sio (2-tailedl Difference Difference Lower Upper Yield (ton/ha) Equal variances

Table 5: The relationship between water melon yield and having market information

Having market Std Error information N Mean Std Deviation Mean

Eaualitv of Variances t-test for Eaualitv of Means

F Sig t df Sia 12-tailedl Difference Difference Lower Upper

Yield (ton/ha) Equal variances

Table 6: The relationship between the total cost and land type

Total cost/ha (million VND)

Squares df Mean Square F Sia

Total cost/ha (million VND)

Land type N alluvial soils 91 acid sulphate soils 70 dark alluvial soils 16 Sig

The article presents the means for groups within homogeneous subsets, highlighting that the harmonic mean sample size is 34.178 due to the unequal group sizes It is important to note that the use of the harmonic mean for group sizes may not ensure guaranteed Type I error levels.

Table 7: The relationship between the total cost and having information from agri-extension

Equality of Variances !-test for Enualitv of Means

F SiCl I df Siq (2-tailedl Difference Difference Lower Upper Total cosVha Equal variances

Table 8: The relationship between the total cost and having agri-extension service in location

Equality of Variances !-test for Equality of Means

F Sig t df Sig (2-tailed) Difference Difference

Total cosl/ha Equal variances

Table 9: The relationship between the total cost and having market information

Equality of Variances t-test for Equality of Means

F Sig t df Sig (2-tailed) Difference Difference Total cosl/ha Equal variances

Table 10: The relationship between the taking care cost and land type

Taking care cost (million VND)

Squares df Mean Square F SiQ

95% Confidence Interval of the Difference Lower Upper -1.06782 1.85693 -1.10743 1.89654

95% Confidence Interval of the Difference Lower Upper -.41563 2.49914 -.35326 2.43677 h

Taking care cost (million VND)

Landty_l)e N 1 alluvial soils 91 8.4371 acid sulphate soils 70 8.7770 dark alluvial soils 16 9.9580

The article presents the means for groups categorized into homogeneous subsets, noting that the Harmonic Mean Sample Size is 34.178 It highlights that the group sizes are unequal, necessitating the use of the harmonic mean of these sizes However, it is important to mention that Type I error levels are not guaranteed in this context.

Table 11: The relationship between taking care cost and having information from agri-extension

Equality of Variances !-test for Equality of Means

F Siq I df Sig (2-tailedl Difference Difference Lower Upper Taking care cost Equal variances

Table 12: The relationship between taking care cost and having agri-extension service in location

Having agri-extension Std Error service in location N Mean Deviation Mean

Eaualitv of Variances !-test for Equality of Means

F Sig t df Si!l (2-tailed) Difference Difference Taking care cost Equal variances

Table 13: The relationship between taking care cost and having market information

Equality of Variances t-test for Equality of Means

F Sig t df Sig (2-tailed) Difference Difference Taking care cost Equal variances

95% Confidence Interval of the Difference Lower Upper -.48818 1.39184 -.51937 1.42303

95% Confidence Interval of the Difference Lower Upper -1.01827 86915 -1.01988 87076

Table 14: The relationship between chemical fertilizer amount and land type

Squares df Mean Square F Sig

Land type N 1 2 alluvial soils 91 782.2802 dark alluvial soils 16 788.2500 acid sulphate soils 70 863.9571

The article presents the means for groups categorized into homogeneous subsets, highlighting that the harmonic mean sample size is 34.178 It notes that the group sizes are unequal, necessitating the use of the harmonic mean of the group sizes However, it also cautions that Type I error levels are not guaranteed.

Table 15: The relationship between phosphate fertilizer amount and land type

Land type N 1 alluvial soils 91 296.4176 dark alluvial soils 16 303.6250 acid sulphate soils 70

The article discusses the display of means for groups within homogeneous subsets, highlighting that the harmonic mean sample size is 34.178 It notes that the group sizes are unequal, necessitating the use of the harmonic mean to account for this disparity However, it also cautions that the Type I error levels are not guaranteed in this context.

Table 16: The relationship between chemical fertilizer amount and having information from agri-extension

Chemical fertilizer no 81 818.0679 137.47129 15.27459 amount (kg a.i) yes 96 812.6354 122.80227 12.53345

Equalitv of Variances t-tast for Equality of Means

F Sig t df Sig (2-tailed) Difference Difference Lower Upper Chemical fertilizer Equal variances

Table 17: The relationship between chemical fertilizer amount and having agri-extension service in location

Equalitv of Variances !-test for Equalitv of Means

F Sig t df Sig (2-tailed) Difference Difference Lower Upper Chemical fertilizer Equal variances

Table 18: The relationship between chemical fertilizer amount and having market information

Having market Std Std Error information N Mean Deviation Mean

Equality of Variances !-test for Equalitv of Means

F Sig t df Sig (2-tailed) Difference Difference Lower Upper c ;nemicel fertilizer Equal var1ances

Table 19: The relationship between pesticide cost and land type

ANOVA Pesticide cost (million VND)

Pesticide cost (million VND) Duncan a,b

Land type N 1 2 dark alluvial soils 16 14.3833 alluvial soils 91 14.4406 acid sulphate soils 70 15.5539

The article discusses the display of means for groups within homogeneous subsets, noting that the harmonic mean sample size is 34.178 It highlights that the group sizes are unequal, necessitating the use of the harmonic mean of these sizes However, it is important to mention that the Type I error levels cannot be guaranteed in this context.

Table 20: The relationship between pesticide cost and having information from agri-extension

Levene's Test for Equality of Variances t-test for Equality of Means

F Sig t df Sig (2-tailed) Difference Difference Lower Upper Pesticide cost Equal variances

Tiêu đề	Determinants of Water Melon Production at Farm Household Level in Tien Giang Province
Tác giả	Luong Thi My Duyen
Người hướng dẫn	Dr. Tran Tien Khai
Trường học	University of Economics Ho Chi Minh City
Chuyên ngành	Development Economics
Thể loại	thesis
Năm xuất bản	2011
Thành phố	Ho Chi Minh City

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Số trang	94
Dung lượng	2,9 MB