South Pacific Studies Vol.43, No.1, 2 2023

Evaluating Sustainable Agribusiness Farming Practice in Markham
Valley of Huon Gulf District, Papua New Guinea (PNG)
Riwasino John1 and William Kerua2

1: 1P O Box 4150, Allotment 16 Section 155, Aquari Ave, East Taraka
Lae 441, Morobe Province
Email: jkriwasino@gmail.com
2: Fiji National University, Department of Agribusiness and Extension.
Email: wkerua69@gmail.com

Abstract
Sustainable farming is based on social, economic, environment and psychological viability
that enhance economic growth and reduce poverty improve farmers livelihood and wellbeing in the
project impact communities. Study intended to investigate the opinions of farmers on tree farming
agribusiness on its impact on their livelihood and wellbeing. Study involves cross-sectional research
design and the primary field data was collected from local communities of PNG Biomass project
impact area in Markham Valley of Huon Gulf District, Papua New Guinea (PNG). Both qualitative andquantitative method are being used to collect primary field data. The main data collection instrument
were survey questionnaires, interview, and field observation and assessment. The study selected 10%of total sampling population of 500 tree farmers in order to collect data, analysis data and provide
solution to the research problem. The primary data from the field were analysised, processed andinterpreted using Ms excel and Statistical Package for Social Sciences (SPSS) software.
Findings about farmers’ view on farm sustainability founds that farming for income was ranked
highest, and farming for improving ecosystem and bio-physical environment were ranked lowest.
Further study into farmers’ household unit living standard and wellbeing using Multidimensional
Poverty Index (MPI) shows that farmers in Markham Valley were found to be multidimensionallypoor.
Study recommends for wider community awareness about importance of PNG Biomass tree
farming project. Study also recommends for financial literacy training that may improve farmers’
knowledge in farm income management, usage and control.
Key words:

agricultural business, farm sustainability, farmers wellbeing, financial literacy training――――――――――――――――――――――――――――――――――――――――――――――
Received: 25 November, 2022
Accepted: 3 February, 2023

12South Pacific Studies Vol.43, No.1, 2 2023

Introduction
Research background
The farm business promotes economic growth, livelihood improvement and wellbeingof the people in the rural communities. According to Kahan (2013) and Singh (2014),
agribusiness and farming is a technology based enterprise in agriculture that provides new
ways of improving productivity and further promote sustainable production to meet themarket demand.
Tree farming is the PNG Biomass project in Markham Valley of Huon Gulf district,
Papua New Guinea. PNG Biomass tree farming is undertaking the development of highvalue, nature-based conservation forests within the Markham Valley, Papua New Guinea,
through the reforestation of underutilized grasslands and used land. The significance of PNG
Biomass project is to reduce greenhouse effect, global warming and climate change throughcarbon sequestration process from planted trees and their biomass. The PNG Biomass tree
farming project also contribute towards rural economy and cash income through land lease
payment, employment opportunities and other spin-off benefits.
PNG Biomass tree farming is a value-added based project that enhances sustainable
land use and promotes food security in the rural communities of Markham Valley. The
project does not only provide employment opportunities but also solve social.
Research problem statement and objectives
PNG Biomass tree farming project started in the year 2011 whereby it provides
enormous monetary benefit for the local communities in the Markham Valley over the years
of project development. However, there is insufficient information available to confirm andverify the impact of project on rural people’s livelihood and well-being. Hence, the study
intended to investigate the farmers’ opinion on role of farming on farmers’ livelihood andwell-being by evaluating farm sustainability and household unit living standard particular
the PNG Biomass project tree farmers (growers) of the Markham Valley in Huon Gulf
District, Papua New Guinea (PNG).

Research Site and Methodology
Study Area
Primary field data was collected from local communities of PNG Biomass project
impact area in Markham Valley of Huon Gulf District, Morobe Province, PNG. Figure 1
shows the map of study area in Markham Valley of Huon Gulf District.

Riwasino John and William Kerua: Evaluating Sustainable Agribusiness Farming Practice in Papua New Guinea

13

Figure 1. Map of study area, PNG Biomass Project in Markham Valley of Huon Gulf District, PNG.
Source: https://www.google.com › earth, (January 2023).

Research design and method
The study involves a cross-sectional research design that provides a statistical database. The cross-sectional design aims at finding out the prevalence of a phenomenon,
situation, problem, attitude or issue by taking a cross section of a population once to givean overall picture (Setia 2016). The cross-sectional study, research design was based on
both qualitative and quantitative research approaches, a mixed research design strategy. The
cross-sectional research design is being instigated by contemporary issues and problems
affecting peoples’ livelihood and wellbeing due to the impact of project development overthe period of time. The focus of cross-sectional research in this study was to systematically
capture primary field data and then further analysis the data in order to provide solution to
the research problem. Both qualitative and quantitative method are being used to collectprimary field data for statistical analysis.
Theoretical concept and conceptual framework
The theoretical framework represents by various variables which include independent,
intervening and dependent variables (Table 1). According to Patel (2009), variables areconcepts, characteristics, or properties that can vary, or change, from one unit of analysis
to another. Leggett (2011), point out that any event, situation, behavior, or individual
characteristic that varies. In scientific research, selection and measurement of variables is
an important task (Guyon and Elisseeff 2003). Guthrie et al. (2004) further elaborate that

14South Pacific Studies Vol.43, No.1, 2 2023

it requires careful selection of units for the collection of, analysis and reporting of the data.
An independent variable is that factor which cannot be manipulate in attempt to ascertain
its relationship to an observed phenomenon whereas a dependent variable is the factor,
which appears, disappears or varies as the researcher introduces, removes and varies theindependent variable (Kaur 2013).
Table 1. The theoretical framework represents by the main variables. The three main variables of
independent, intervening and dependent variables.
Independent Variables•

Socio-economic
characteristics- Age- Education- Farm size
- Family size
- Income- years of farming
experience- Operational landholding

Intervening Variables• improve and sustainable
farming practice andmanagement;• positive behavioral change;• Greater livelihood
improvement.

Dependent Variables• farm practice andmanagement efficiency;• influence of farming on
farmers attitude, behavior
and perception• effect of farming on farmers
livelihood and wellbeing

Source. Author’s own study, (January 2019).

The sustainable farming entrepreneurship conceptual framework (Fig. 2) is basedon evaluating social, economic, environment and pyschological viability. The social
aspect of sustainable farming concern about farmers’ livelihood and wellbeing, economic
sustainability is about financial management particularly farmers income and spending
or expenditure of the tree farming business and environmental aspects that capturesevalauting terrestrial ecology and hydro-biology and, its impact on the human environment.
The psychological evaluation is based on farmers’ attitude, behaviour and perception about
farming entrepreneurship.

Figure 2. The Sustainable Farming Entrepreneurship Conceptual Framework.
Source. Author’s own study, (January 2019).

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Data collection instrument
The main data collection instruments were survey questionnaires, interview, fieldobservation and assessment. The survey questionnaires are being used in this study to collectspecific data of interest for analysis in order to provide answers to the research problem
statement. The two main approaches were distribution of survey questionnaires to the tree
farmers whereby the farmers themselves filled in the blank questionnaire, and interview theconcern tree farmer through face to face interview and then jotted the sediment from thefarmer during the conversation.
The interview was carried out to capture the in-depth stories of respondent throughasking personal questions and opinion about issue experience of the person interviewed inregard to the cause-effect relation of the PNG Biomass project and tree farming business.
During the interview, specific question about the impact of the PNG Biomass project isbeing asked and the interviewee responded to the question by answering and providing
views, opinion and reaction towards the effect of the project in the community.
The interview captures the farmers view and opinion on farm sustainability, farmers
living standard and wellbeing. During the interview process, specific questions were asked
regarding farm sustainability of social, economic, environment and cultural aspects as
indicated on the flow chart (Fig. 3). For example, the farmers’ views on social sustainability
were captured in regard to availability of timber for building and fuel wood.

Figure 3. Sampling Population Flow Chart.
Source: Author’s own study, (January 2019).

Further, the survey and interview were conducted to investigate impact of farming on
farmers living standard and wellbeing. The questions were based on farmers’ householdindicators which include: education level, health status, and the living conditions of farmers.
The underlining factor was to investigate poverty status of the farmers’ household. The data
were processed analysised using Multidimensional Poverty Index (Fig. 4).
After the interview, field observation and assessment were conducted to verify andconfirms farmers’ views and opinion on farm sustainability indicators particular social,economic, environment and cultural aspects. The observation and assessment was carriedout to evaluate the impact of PNG Biomass project in Markham Valley of Huon Gulf
District.

16South Pacific Studies Vol.43, No.1, 2 2023

Sampling Strategy and Sample Size
The purposeful sampling technique was employed to collect primary data fromthe study area. According to Taberdcost (2016), purposeful sampling is an approach
whereby vital information is being obtained from selected site from other choices. In otherwords, primary data from study area were collected through identification and selection of
information-rich cases related to the phenomenon of interest.
The two main sampling techniques applied during the study were criterion and random
purposeful sampling. The purposeful criterion sampling technique was employed tocollect information rich case in which it captured the in-depth stories of respondent during
interview process Patton (2002) point out that “criterion sampling involves selecting casesthat meet some predetermined criterion of importance” (p.238). Palinkas et al. (2015)
further added that criterion purposeful sampling is more applicable for implementation
research which is more consistent with recent or current trend of developments.
The purposeful random sampling for collecting quantified data in a sample population.
It is based on a population of interest and developing a systematic way of selecting casesthat based on advanced knowledge of how the outcomes would appear (Benoot et al. 2016,
Naderifar et al. 2017)
In this study, primary data were collected from 8 clans with total population of 500
people who leased land area for tree farming business. The choosing and selection of sample
size involving randomly selecting 2-3 family units from each clan to represent the whole
population as a sample size.
Data Processing Procedure
The primary data from the field were processed and analysised under farmsustainability, and the farmers’ living standard and well-being.
Farm Sustainability Evaluation
The farm sustainability evaluation was based on four main indicates: social, economic,
environment and cultural effects of farming. The primary data collected from the field wereanalyzed using data reduction and consolidation process.
Process 1: Data Reduction
The data reduction was the first process whereby primary data collected from the field
through field notes, interview transcripts, and observations are being assembled or put
together in order to minimize or reduce and further discard irrelevant data. The reduced data
is being organized through coding using Microsoft excel and Statistical Package for Social
Sciences (SPSS) software and then further summarize to give a manageable size for thedata.
Process 2: Data Consolidation
The second process was data consolidation in which reduced data organized throughcoding in order to establish new data sets. The consolidated data were analyzed using
formulae below to determine the sustainability of the project development and management.

Riwasino John and William Kerua: Evaluating Sustainable Agribusiness Farming Practice in Papua New Guinea

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Sustainable Farming Entrepreneurship Index (SFE Index)

Figure 4. Formula and Calculation.
Source. Source: Author’s own study, (January 2019).

The respondents were asked about level of farm sustainability concerning social,economic, environmental and cultural sustainability as shown on Table 2. The respondent
ranked and scored by choosing one of the three: (i) Little (1), (ii) Much (2), (iii) Very Much(3). The figures in the bracket were the weights assigned to each level. For example, theinterviewing farmer was asked, “what is your view and opinion about the impact of tree
farming project on skills and knowledge under social sustainability”? If the farmer respondentand ranked, ‘very much’, it was scored 3 as it is the weight assigned to the level. These also
applied to other indicators for farmers’ view on the social sustainability.
For example, three farmers were interviewed whereby first respondent graded as little,
second farmer level as much and the third respondent ranked as very much in which scoring
were 1,2 and 3 respectively. Using SFE formulae to calculate, the total scoring will be 650
points on SFE index[ (1+4+9) x 100].
3
Table 2. Farm Sustainability Assessment & Evaluation.
1.0 Social Perspective
Timber for building material
Fuel wood source
Aesthetical value
Recreational value
Food and nutrition value through inter-cropping
Knowledge and skills
2.0 Economical Perspective
Cash income through lease and contract payment
Cash income through inter-cropping
Other spin-off monetary benefits
3.0 Environment Perspective
Improve soil fertility
Reduce soil erosion
Biophysical aspects e.g. the land are becomes much better and attract animal life
Improving EcosystemWater storage and supply
4.0 Cultural Perspective
Spiritual richness
Cultural heritage site
Source. Author’s own study, (January 2019).

Ranking18South Pacific Studies Vol.43, No.1, 2 2023

However, the SFE Index with highest value was ranked as the first; next highest as
second and so on in a descending order to the lowest. If FSE index of skills and knowledge
was highest, it may have ranked first followed by other indicators in the social sustainability.
Socioeconomic Characteristics of Sustainable Farming Entrepreneurship (SFE)
The socioeconomic characteristics analysis for sustainable farming was determinedby FSE index calculation and analysis that tabulated on chronological order as shown on
Appendix I (Table 9). From Appendix I (Table 9), the two top highly scored and ranked
sustainable faming indicators were selected to do socioeconomic analysis of sustainable
farming entrepreneurship.
Standard Deviation (SD) Calculation and Process.
The SD calculation is based on formulae (See Fig. 5) and it involves process describe below.
Step 1: Find the mean of the data set, which is represented by the variable μ.
Step 2: Find the distance from each data point to the mean (i.e., the deviations) and squareeach of those distances.
Step 3: The symbol ∑∑sum means "sum", so add up the four values that found in Step 2
Step 4: Divide the result from Step 3 by the variable N, which is the number of data points.
Step 5: Find the standard Deviation (SD) by taking the root square and then round it off tonearest.

Figure 5. Standard Deviation Formula and Calculations.
Source. Retrieved from http://www.khanacademy.org › summarizing-quantitative-data, (January 2019).
Table 3. Mean (Units and Measurement).
Characteristics

Units

Income &years of farming experience

Kina per year

K/Yr

Income & fam size

Kina per hectare

K/Haskills & knowledge, and year of farming experience

Population per year

Not applicable

Skills & knowledge, and farm size

Population per hectare

Not applicable

Source. Author’s own study, (January 2019).

Farm Impact: Farmers Livelihood and Wellbeing
The farm impact on farmers’ livelihoods and wellbeing was evaluated using
Multidimensional Poverty Index (MPI). It was based on three (3) main dimensions of ahousehold characteristic which were health, education and living standard. The dimension
and indicators of analyzing field data are being indicated on Table 10 (Appendix II).

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MPI formula and calculation
Formula.
MPI =H x A
Where MPI is the Multidimensional Index, H is the percentage of people who were MPI
poor (incidence of poverty) and A is the average intensity of MPI poverty across the poor (%).
Figure 6 represent the process of MPI calculation.

Figure 6. The process of Multidimensional Poverty Index (MPI) calculations.
Source. Author’s own study, (January 2019).

The co-relation analysis of main household poverty indicators
The co-relation analysis was carried out in order to analysis the independent variables ofhousehold poverty against dependents variable of Multi-Dimensional Poverty Index (MPI).
In this study, the independent variables of household poverty were based on four mainhousehold indicators: (1) family size, (2) children (< 6 years old), (3) children under (< 18years old) and (4) children (> 6 years old to 18 years old). The dependent variable were
the indicators and off-cut for the main indicators of household poverty and these were: (1)children completed > grade 5, (2) > 6 years old (completed Gr.8 and above), (3) infant dead,(4) no health services, (5) bush material house, (6) no electricity, (7) no access to clean
drinking water, (8) household using firewood, (9) no access to adequate sanitation and (10)household has no car. The result of co-relation analysis is being shown in Table 8.

20South Pacific Studies Vol.43, No.1, 2 2023

Data Analysis Methods
Data analysis is a process of evaluating raw data from the field using analytical andlogical reasoning, purposely to find out each component of data collected and provided.
Kawulich (2005) describe data analysis as the process in which a researcher uses to convert
the data into a story that describes the phenomenon or participants’ views, using the emic
perspective. In other words, the primary data collected from field is being compiled together
and then analysis to form the database of findings or conclusion to the issue investigated.
In this research, primary field data collected through interview, survey questionnaires, fieldobservation and assessment were analysised, processed and interpreted using Ms excel
and Statistical Package for Social Sciences (SPSS) software in order to provide statistical
database for interpreting the research problem statement.

Result
The results from the study were discussed under farmers’ view on farm sustainability,
socioeconomic characteristics of farmers and the effect of farming on farmers living
standard and well-being.

Farmers’ View on Farm Sustainability
The four main indicators of farmers’ view on farm sustainability in which study
investigated were social, economic, environmental, and cultural aspects.
Social Sustainability of Farming
The farmers view on social sustainability of farming were timber for building, fuelwood, knowledge and skills, shade and recreational value, food and nutrition value, andaesthetical value. Table 4 represents farmers’ views and opinion on social sustainability of
the farming.
The result shows that the knowledge and skill were ranked first and scored 1800 on
Sustainable Farming Entrepreneurship (SFE) index. The second preferred reasons forfarming were timber for building and fuel wood since both scored 1570 on SFE Index.
Table 4. Social sustainability of the farming.
Social Sustainability Indi- Little (L)catorsMuch (M) Very Much (VM) SFE Index Ranking

Knowledge & Skills

10

20

70

1800

1

Timber for Building

10

30

60

1570

2

Fuel wood

10

30

60

1570

2

Recreational Value

50

40

10

380

3

Food & Nutrition Value

50

40

10

380

3

Aesthetical Value

60

30

10

370

4

Source. Author’s own study, (January 2019).

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The lowest ranked reasons for farming were recreational value, followed by food andnutrition, and then the aesthetical value. The farming for recreational value, and food andnutrition were ranked third in which both scored 380 on SFE index. The least and fourthranked social sustainability was the farming for aesthetical value with FSE index of 370.
The statistic also indicates that there was no significance difference between social
sustainability reason of aesthetical, foods and nutrition, and then recreational value sincemost scored lowest between 250 and 400 on SEF Index.
Economic Sustainability of Farming
The four main farmers view on economic sustainability of farming were employment
creation, cash income from land lease areas and contract work (seasonal work) payment andthen income from intercropping of food crop planted within inter-row of newly planted tree
farmed land areas.
The findings of economic sustainability from farming are being shown in Table 5. The
study found that the reason for cash income from land lease payment was ranked first with
SFE index of 1800 and then followed by cash income from contract work (seasonal work)
payment that ranked second with SFE index of 1570. The farming for employment creation
was ranked third with SFE index of 1340.
Table 5. Economic sustainability of farming.
Economic Sustainability Little (L)Indicators

Much (M) Very Much (VM) SFE Index Ranking

Cash Income(Land Lease Payment)

10

20

70

1800

1

Cash Income(Contract Work Payment)

10

30

60

1570

2

Employment Creation

10

40

50

1340

3

Income from intercropping

20

40

40

1100

4

Source. Author’s own study, (January 2019).

The lowest and fourth rank indicator for economic sustainability was farming to
generate income from intercropping practices that scored 1100 on FSE index.
Environmental Sustainability of Farming
Table 6 shows the farmers view on environmental sustainability of farming. Finding
reveals that the reasons for improving soil fertility and reducing soil erosion whereby bothranked first and scored 1570 on FSE index which means there is no significant difference
between them.
The second ranked environment sustainability perspective was found to be reason forimproving the biophysical environment which scored 1340 on FSE index.

22South Pacific Studies Vol.43, No.1, 2 2023

Table 6. The environmental sustainability of farming.
Environmental Sustain- Little (L)ability Indicators

Much (M) Very Much (VM) SFE Index Ranking

Improve Soil Fertility

10

30

60

1570

1

Reduce Soil Erosion

10

30

60

1570

1

Improve Bio PhysicalEnvironment

10

40

50

1340

2

Improve Ecosystem

20

60

20

640

3

Improve water storage &Supply

50

40

10

380

4

Source. Author’s own study, (January 2019).

The lowest and third ranked cultural perspective was preservation of archaeologicalsite in which scored 390 on FSE index.
The study further conducted socioeconomic characteristic analysis to evaluate farmers
two main characters (farm size and farmers’ year of farming experience) with two top
ranked indicators about farmers’ view on farm sustainability which were income from landlease area and skills and knowledge gained from farming.

Socioeconomic characteristics of Sustainable Farming Entrepreneurship (SFE).
The socio-economic characteristic analysis for sustainable farming was based own
two top ranked indicators which were farmers view on cash income from land lease
area payment, and skills and knowledge gained from farming business (Table 9). The
socioeconomic characteristics of farm sustainability for both indicators, farmers view onincome from land lease area payment and, skills & knowledge gained from farming wereanalysised and discussed using descriptive analysis (Table 7).
Farmers View on Income from Land Lease Area Payment
The result from table 7 represents the relationship between farmers’ view on income
from land lease area payment and their years of experience in farming. Findings shows thatmean income from land lease area payment with farming experience (0-2) years was 2.333,
farmers fall under farming experience of (3-4) years was 3.000 and then farming experienceof more than five years was found to be 2. 667.
Further socioeconomic analysis of relationship between farmers’ view on income fromland lease area payment and farm size (operational land holding) indicates that the meanfor farmers with farm size of (0-5) hectares was 2.00, farm size of (6-20) was 2.750 andfarmers’ falls under category of more than 21 hectares (large farm) was found to be 2.500.

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Table 7. The socioeconomic characteristics of farm sustainability.
Characteristics

Range

Categories

Variables
Skills & Knowledge (N=7)

Incom (K) (N=7)

Years of Farming

Farm Size

N

%

Mean

SD

N

%

Mean

0-2 years (low)2292.333 0.577

457

2.667 0.577

3-4 years (medium)

1

14

3.000

1

14

3.000

> years (high)457

2.667 0.577

229

2.333 0.577

0-35 0-5 Ha (small)

0-5

SD

1

14

2.000

1

14

3.000

6-20 Ha (medium)

4

57

2.750

0.5

4

57

2.500 0.577> 21 HA (large)

2292.500 0.707

229

5.000 0.707

Source. Author’s own study, (January 2019).

Farmers View on Skills and Knowledge
Study into farmers’ views on skills and knowledge gained from farming and between
the different categories of farmers’ years of farming shows that the mean of farmers’ yearsof farming under (0-2) years was 2.667, under (3-4) years was 3.000 and then farmers withmore 5 years of farming experience was 2.333.
Further study into relationship between the farmers’ view of acquiring skills andknowledge from farming, and the farm size (operational land holding) shows that the meanof farm size under (0-5) hectare was 3.000, the mean of farm size under (6-20) hectare was
2.500 and farm size more than 21 hectares was found to be 5. 00.

Evaluating Farmers’ Living Standard and Wellbeing using Multidimensional
Poverty Index (MPI)
The study evaluates farmers’ household living standard and wellbeing. The main
assessment tool used for measuring household was Multidimensional Poverty Index (MPI)
which is being developed by University of Oxford in year 2010 (Alkire and Santos2010). The three main indicators were lack of education, poor health and poor conditions ofliving. The process or steps for calculating multidimensional poverty index (MPI) are being
discussed under research methodology (Fig. 6).
According to Multidimensional Poverty Index (MPI) calculation and analysis, the firstprocess in MPI calculation and analysis was to found out the weight count of deprivation.
Finding shows that the weighted count of the deprivations (c) for farmers in a household
was found to be 6.5. The second process was to identify whether household poor or not if
C < 3.3. Since C (weight count of deprivation) was calculated to be 6.5 which means thefarmers house hold was found to be multi-dimensionally poor as it was above the benchmark level of 3.33. The third process involves calculating the head count (H) which was
the proportion of population who were multidimensionally poor. The multidimensional
head count calculated was 1.45. The fourth stage of Multidimensional Poverty Index(MPI) calculation was to calculate the intensity of Poverty (A) that was the proportion of

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South Pacific Studies Vol.43, No.1, 2 2023

dimensions or weighted component indicators “d” across which on average poor people isbeing deprived. Statistical analysis indicates that the intensity of poverty was found to be
5.33. The fifth and final stage was to calculate Multidimensional Poverty Index (MPI) by
multiplying the headcount ration (H) by the intensity of Poverty (A). Finding shows that the
MPI of farmers in Markham Valley was 7.84.
Further research and analysis were carried out about relation between the independent
variable of household poverty and dependent variables of Multidimensional Poverty Index.
The co-relation analysis of main household poverty indicators
Table 8 represents the correlation between the main characteristics of the household
and household poverty. The result indicates the relation between the children’s different age
group and their education level within farmers’ household unit. Finding shows that there wasa highest significant relation between the children under (< 18 years old) and children morethan 6 years’ old who completed grade eight (8) and above, followed by children under (>6 years old to 18 years old) and children more than 6 years’ old who completed grade eight(8) and above. Finding also shows that there was significant correlation between children
completed >grade 5 and no electricity. The study further reveals that there was relation
between bush material house and no electricity, and then followed by relation between
household using firewood and no access to adequate sanitation.
Table 8. Evaluation of Co-relation between Household Indicators and Household Poverty Dimensions
and Off-cuts.
X1
X1

X2

X3

X4

MPI01 MPI02 MPI03 MPI04 MPI05 MPI06 MPI07 MPI08 MPI09 MPI10

1

X2

.048

1

X3

-.447

-.091

1

X4

-.262

.530

.395

MPI01

.032

.130

-.068

.103

1

MPI02

.531

.041 -.912**-.562*

.235

1

MPI03

.195

-.114

-.271

-.155

-.111

.297

1

MPI04

-.057

-.418

-.297

0.000

.026

.184

.272

MPI05

-.178

-.312

.062

-.425

-.040

.042

.365

.284

1

MPI06

-.089

-.312

-.139

-.283

-.566*

.042

.365

.284

.639*

1

MPI07

-.098

-.309

.051

-.310

-.465

.065

.300

.234

.426

.426

1

MPI08

-.386

-.386

.027

-.245

-.245

-.220

.158

.123

.433

.433

-.158

MPI09

-.386

-.386

.027

-.245

-.245

-.220

.158

.123

.433

.433

-.158 1.000**

MPI10

-.057

.171

-.218

0.000

.310

.239

.234

.182

.178

-.284

.272

1

*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

1

1
-.123

1
-.123

1

Riwasino John and William Kerua: Evaluating Sustainable Agribusiness Farming Practice in Papua New Guinea

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Source. Author’s own study, (January 2019).

Discussion
The study discussed two main views of famers about tree farming agribusiness inMarkham Valley were farm sustainability and the effect of farming on farmers’ living
standard and well-being.

Farmers View on Farm Sustainability
The study discussed the farmers view on four main farm sustainability indicators whichwere social, economic, environmental, and cultural aspects.
Social Sustainability of Farming
The farmers’ view on social sustainability of farming (Table 4) shows that the skill
and knowledge was ranked first. This finding indicates that the farmers acknowledged andappreciated tree farming business as part of improving their skills and acquiring knowledge
for large scale farming practices. According to Robinson- Pant (2016), transfer skills
and knowledge in agricultural improve rural livelihood through social change and ruraltransformation process. In other words, the empowerment of farmers by developer with
innovative and strategic approach towards farming may have a positive impact and influenceon farmers’ attitude and behaviour toward farming business.
The next preferred reasons for farming were timber for building and fuel wood dueto the biophysical environment of savannah grassland and shortage in timber and fuelwood in the community. Finding also shows that aesthetical, food and nutrition value, andrecreational value for tree farming is being defined by the farmers as least important in termsof social sustainability. This was perhaps due to limited knowledge and understanding about
aesthetical value, food and nutrition and recreational as well as other benefits derived fromtrees. Lunenburg (2010) point out that individual person may have different perceptive,knowledge, belief and opinion toward development project. However, the World Bank
(2007) reports about agriculture and rural development, emphasis that agriculturalcommercialization through farming and food production improves nutritional outcomes forthe farmers’ livelihood and wellbeing.

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South Pacific Studies Vol.43, No.1, 2 2023

Economic Sustainability of Farming
Study investigated about farmers’ view on economic sustainability of farming.
According to findings, cash income from farming through land lease area and contract work
payment were ranked highest due to the fact that focus of farming is being defined by thebenefit of cash income (money) generated by the PNG Biomass project to the landowners,
the tree farmers (growers) of Markham Valley. Richardson et al. (2013) stress that leasearrangements enhance farmers’ farming business operation growth and sustainability.
According to UNDP (2015) report, contract farming is commercially viable farmer–
enterprise relationships built on equity, mutual trust, and shared benefits.
The farming for employment creation was ranked next highest because the landowners
already engaged and involved in participation of farming through paid wage employment
on a full time basis and also cash income generate from contract work (seasonal work)
engagement.
The least reason for economic perspective for tree farming was found to be off-farmbenefits such as intercropping of food crop within inter-row of newly planted tree crops
since the farmers observed as occasional in which it was regarded as the least importantreason for the economic sustainability of farming. Dary and Kuunibe (2012) describe nonfarming economic activity which include off farm income activity as seasonal and low return
activities. However, Bubela (2016) stress that off-farm income such as intercropping offood crop planted within newly planted tree rows shift from supplementary income source
to an important risk management tool for new farming business ventures. In other words,
intercropping practice contribute towards generating supplementary income, however, it
helps offset short term financial constraints and need for newly established farm businessenterprise.
Environmental Sustainability of Farming
Study shows that farmers view the reasons for improving soil fertility and reducing soil
erosion as highest rank environmental sustainability. This was due to the fact that farmers
considered both reasons for venturing into farming business. Faleyimu and Akinyemi (2010)
point out that planting a tree helps conserve soil on land by reducing soil erosion, increasing
soil organic matter, improving soil structure and further assist in nutrient cycling.
The reason for improving the biophysical environment was the next highly ranked
environment sustainability perspective. This finding affirms about the farmers’ aspiration
for changing the bio-physical environment of savannah grassland into forest land area that
improves the surrounding environment which create conducive for living. Collins (2012)
explains that innovation in farming influence landscape design and change of landscapefeatures.
The environmental sustainability reason for improving water storage and improving
ecosystem were the least and not favoured by farmers, due to lack of understanding about
ecosystem and biophysical relationship between trees, the environment, and surroundings.
Further, the farmers’ lack understanding about the carbon sequestration process of trees andthe environment that contributes towards reducing the greenhouse effect, global warming,

Riwasino John and William Kerua: Evaluating Sustainable Agribusiness Farming Practice in Papua New Guinea

27

and climate change. According to containment theory of Walter Reckless (1961) andFlexon (2014), human perspective and behaviour towards social outcome is the interplay
between internal and external forces. External force is one of the contributing factors toward
perceptual barriers. In other words, limited information and knowledge contribute toward
misunderstanding about the importance of tree farming and Biomass project at larger scale.
In this case, publicity through awareness program can help farmers improve understanding
about importance of tree farming and environmental sustainability.
Cultural Sustainability of Farming
Statistical analysis shows that reason for preserving cultural heritage was ranked
highest due to the fact that farmers view tree farming associated with their cultural linkage.
According to informal interview with Kelly Jim of Tararan village in Huon Gulf district
reveals that their clan name (‘Feref’) is associate and derived from native tree species
known as Nonnie tree (Morinda citrifolia).
The spiritual richness was ranked next highest due to the fact that forest andenvironment have spiritual significance and connection with cultural norms and values ofthe Markham Valley society. According to informal interview with Sam Meyab of Chivasing
village in Huon Gulf District, rural people in Markham Valley have traditional believethat they acquire spiritual power from the sacred forest land areas. The archaeologicalsignificant is being ranked the least due to the fact that cultural sites are being scarce andfound only on certain anointed sites or grounds which made it as least important. Further
research and analysis were done on the socioeconomic characteristics of sustainable farming
entrepreneurship.

Socioeconomic Characteristics of Sustainable Farming Entrepreneurship (SFE)
The discussion for socioeconomic characteristic of sustainable farming
entrepreneurship was based on two main indicators, which were farmers view on cash
income from land lease area payment, and knowledge and skills gained from farming
business (Table 9).
According to the result from socioeconomic characteristic analysis about farmers’ viewon income from land lease area payment (Table 5) shows that farmers’ years of experiencein farming business does not influence any farm income since their average means isinconsistent throughout the different category of farming experience. Further socioeconomic
analysis of relationship between farmers’ view on income from land lease area payment andfarm size (operational land holding) indicates that farm income increase with farm size andthen gradually reduce income with more than 21 hectares of land area. The findings also
reveal that farmers’ income was inconsistent with the years of farming and farm size. The
main factor that affects farmers’ income were farm activities and operational land holding(farm size). The farmers generate more income when they involved in more activities
for farm operation per year. The farmers’ income also influences by number of land arealeased to the developer. Those farmers who increased their land lease over the years offarming tend to benefit from land lease payment whereas farmers provide less, have reduced

28South Pacific Studies Vol.43, No.1, 2 2023

income. Munć and Božić (2017) point out that increase farm size and field crop production
contributed towards increase income per active members of family household employed inagriculture.
Study into farmers’ views on skills and knowledge gained from farming and between
the different categories of farmers’ years of farming shows that those farmers under (34) farming years of experience agreed that farming improve their skills and knowledge infarming. The main factor that contributes towards inconsistent response from farmers undervarious categories of farming years’ experience was due to timing and development stage of
farming. The farmers who provide the land during the stage whereby the developer improve
farm management practice tends to participate and learnt modern techniques in farming.
Japan International Cooperation Agency (2009) emphasizes that leaning to improveskills and knowledge about agricultural innovation can be influenced and motivated byapplying innovation to their own situation or current trend of living.
Further study into relationship between the farmers’ view of acquiring skills andknowledge from farming, and the farm size (operational land holding) reveal that those
farmers with more than 21 hectares of farm land agreed about improving their skills andknowledge in farming. This result shows that farmers who provide more land area forfarming spend more time in farm activities and practices thus improve their skills andknowledge. In other words, farm activities increase with increased farm land area whereby
a farmer participates in more farm activities that increase their skills and knowledge infarm management practices. Study was also conducted on the influence of farm income on
farmers’ living standard and wellbeing using Multidimensional Poverty Index (MPI).

Evaluating Farmers’ Living Standard and Wellbeing using Multidimensional
Poverty Index (MPI)
Multidimensional Poverty Index (MPI) is the important tool for measuring andevaluating effect of farming on farmers’ livelihood and wellbeing. It is a recent techniquesdesign to capture the poor people’s experience of poverty deprivation experience. AKIREand Santos (2010) point out that MPI is design to focus on income to reflect the multiple
deprivations that a poor person faces. Dotter and Klasen (2014), stress that MPI provide ahousehold – level multidimensional poverty measure.
This study evaluates farmers’ household living standard and wellbeing, and reveals
about the status of farmers’ household living conditions. The result shows that most
farmers’ household found to be at poor stage regardless of income earning from the farming
business. The finding also reflects the farmers’ characteristic and attitude toward managing
their income and also budgeting including their approach towards spending. Finding reveals
about farmers lack of understanding towards the budgeting of their income and spending
meaningfully to sustain their livings. Klinefelter et al. (2008) point out that budgetingis part of risk management strategy that aim towards achieving long- term goal, that is thelong term recurrent needs and sustainable living standard and livelihood. Further research
and analysis was carried out about relation between the independent variable of household
poverty and dependent variables of multidimensional Poverty Index.

Riwasino John and William Kerua: Evaluating Sustainable Agribusiness Farming Practice in Papua New Guinea

29

The co-relation analysis of main household poverty indicators
The correlation analysis was carried out between the main characteristics of thehousehold and household poverty (See table 8: result section). Finding shows that there
was a highest significant relation between the children under (< 18 years old) and children
more than 6 years’ old who completed grade eight (8) and above, followed by children
under (> 6 years old to 18 years old) and children more than 6 years’ old who completed
grade eight (8) and above. This finding reveals that children under (> 6 years old to <18 years old) completed grade eight (8) and above in a farmers’ household unit. In otherwords, children age group falls under (6 -18) years old have completed or attending bothprimary and secondary education as well as tertiary education This result reveals that most
farmers intended to invest the income (money) from farming business into their children’s
educations. The livelihood studies by Morton and Kerven (2013) indicate that the highpriority needs in a community were found to be adequate water, health care, and access to
education.
Finding also shows that there was significant correlation between children completed>grade 5 and no electricity. This indicates that more children of farmers completed grade
five (5) lives in the house condition without electricity or completed their primary educationfrom the household that does not access to electricity. Cook et al. (2007) stated that rural
electrifying is linked to development prosperity in terms of energy uses and poverty
reductions.
Further study reveals that there was relation between bush material house and noelectricity, and then followed by relation between household using firewood and no accessto adequate sanitation. This result confirms about the status of farmers’ households. The
key indicators of the house build from bush material without electricity, usage of firewood
for cooking, and not access to adequate sanitation shows that farmers in Markham Valley
were found to be multidimensionally poor. The findings affirm the poverty status of the
farmers regardless of financial impact of the farming business. Dorward et al. (2001) stressthat the lack of livelihood asset is the symptoms of poverty. According to Krants (2001)
and Neely et al. (2004) poverty reduction is stage where improvement in the lives of rural
poor is achieved by increasing and improving income levels, basic household needs andservices including access to productive resources, increase agricultural yields and changes
in household food security.

Conclusion and Policy Implication
Conclusion
The farmers view on farm sustainability founds that the focus of farming was basedon cash income from land lease area, and improving their skills and knowledge in farming
through participation in farm activities in which both scored 1800 on SFE index. Regardless,farmers lack clear understanding of tree farming and their co-relation with ecosystem andthe environment particularly the role of tree plants toward carbon sequestration process andtheir bio-physical relation with environment which contribute towards minimize climate

30South Pacific Studies Vol.43, No.1, 2 2023

change effect and global warming.
Socio-economic analysis shows that farm income increases with farm size. Those
farmers who provide more leased land area for farming tend to earn more income fromfarming. Study into farmers’ views on skills and knowledge shows that those farmers withmore than 21 hectares of farm land agreed about improving their skills and knowledge infarming. This result shows that farmers who provide more land area for farming spend moretime in farm activities and practices thus improve their skills and knowledge.
Further study into farmers’ living standard and wellbeing using multidimensional
poverty index found to be multidimensionally poor with MPI value of 7.84, which is far
above 3.0 benchmark and cut-off mark for world standard poverty classification. This result
confirms about poverty status of the PNG Biomass project farmers in Markham Valley
regardless of positive impact through monetary benefits (cash income from land lease area
payment) and improving skills and knowledge of farm management practice. The farmers
continue to struggle to live a decent life that accommodates improve living standard andwellbeing. This was due to fact that the farmers lack clear understanding of budgeting fromfarm income in order to spend meaningfully to sustain their living.

Policy Implication
The study recommends for wider community awareness about the importance of PNG
Biomass tree farming project and the non-monetary benefits such as carbon sequestrationthat contribute towards reducing climate change effect and global warming. The study also
recommends for financial literacy training in order to improve farmers’ knowledge in farmincome management, usage and control.

Acknowledgement
The authors would like to acknowledge PNG Biomass project management team andlandowners’ owners of Markham Valley for providing vital information toward the researchstudy.

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Appendices
Appendix I: Farm Sustainability
Table 9. The farmers view on farm sustainability.
Little
(L)

Much
(M)

Knowledge & Skills

10

20

70

1800

1

Cash Income(Land Lease Payment)

10

20

70

1800

1

Timber for Building

10

30

60

1570

2

Fuel wood

10

30

60

1570

2

Cash Income(Contract Work Payment)

10

30

60

1570

3

Improve Soil Fertility

10

30

60

1570

3

Reduce Soil Erosion

10

30

60

1570

3

Employment Creation

10

40

50

1340

4

Improve Bio Physical-Environment

10

40

50

1340

4

off-farm benefits(Income from intercropping)

20

40

40

1100

5

Shade

20

60

20

640

6

Improve Ecosystem

20

60

20

640

6

Cultural Heritage

20

60

20

640

6

Spiritual richness

30

60

10

400

7

Archaeological site

30

70

10

390

8

Creational Value

50

40

10

380

9

Food & Nutrition Value

50

40

10

380

9i

Improve water storage & Supply

50

40

10

380

9

Aesthetical Value

60

30

10

370

10

Sustainability Indicators

Very Much SFE Index(VM)

Ranking

Source. Author’s own study, (January 2019)

Appendix II. Multidimensional Poverty Index (MPI)
Table 10. The Dimension and indicators of the farmers’ living standard and wellbeing using Multidimensional Poverty Index (MPI). Table 10 shows the three (3) main indicators and ten (10)Dimension of multidimensional Poverty Index (MPI). The table also provides brief explanation of each dimension.
Dimensions

Indicators

Explanation

A Health

Each indicator is weighted equally at 1/6
Child Mortality

1

Child mortality: deprived if any child has died in
the family in past 5 years

Nutrition

2

Nutrition: deprived if any adult or child for whomthere is nutritional information is stunted

34

BSouth Pacific Studies Vol.43, No.1, 2 2023

Education

Each indicator is weighted equally at 1/6
Years of Schooling3Years of schooling: deprived if no household member has completed six years of schooling

School attending

4Child school attendance: deprived if any schoolaged child is not attending school up to class 8

C Living standard

Standard of Living (each indicator is weighted
equally at 1/18)
Cooking Fuel

5

Toilet (Sanitation)

6

deprived if the household’s sanitation facility is
not improved (according to MDG guidelines), or it
is improved but shared with other households

Water (drinking)7

deprived if the household does not have access tosafe drinking water (according to MDG guidelines)
or safe drinking water is more than a 30-minute
walk from home round-trip

Electricity

8

deprived if the household has no electricity

Floor

9

deprived if the household has a dirt, sand or dung
floor

Assets10 Assets ownership: deprived if the household does
not own more than one of: radio, TV, telephone,
bike, motorbike or refrigerator and does not own a
car or truck