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byGODFRED ANTWIISSER Conference Centre (ISSER New Building)
WASTE AND SPOILAGE TECHNOLOGY OF THE 2000s: An Empirical Study
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Outline of the presentation The Problem Development of improved rice PBV Objective of study Methodology Findings Conclusions Recommendations The way forward References Acknowledgements
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The Problem
Post-harvest losses (waste and spoilage) constitute a major drain on food production and food security in Africa
In Ghana, annual losses of cereals are between 20-30% which is mainly attributed to inadequate postharvest practices and technologies (MoFA, 2010).
The Northern Region is a major producer of rice in Ghana (37%).
Rice produced in the region is mostly parboiled due to harsh climatic conditions(high temperatures and low humidity)
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The Problem cont’d The widespread use of traditional rice-parboiling
technology in Northern Ghana leads to poor quality of final rice which often does not meet consumers’ expectations
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Development of improved rice PBV
iPBV(improved parboiling vessel)
• CPHP 2004 project(FRI and DFID)
• 2mm in thickness and has two chambers
• Parboil about max 100 kg of paddy
• Fuel savings of 30% - 50% • Reduced drudgery in the
parboiling process• Vessel allows uniform heating
(Tomlins et al., 2007).
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Objective of the Study
Assess the impact of an improved rice PBV adoption on household income in Northern region of Ghana.
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MethodologyObjectives Description of the Objective Method of analysis
Objective one Describe the differences in the characteristics of adopters and non adopters households in the Northern region of Ghana.
Descriptive statistics such as mean, minimum, maximum, standard deviation, percentages
Objective Two Determine the factors that influence the adoption of iPBV technology in the Northern region of Ghana.
Logit model(Green 2008; Baidu-Forson, 1999; Feder et al., 1985)
Objective three Estimate the impact of the adoption of iPBV technology on the household income in the Northern region of Ghana
Propensity score matching(PSM)(Rosenbaum & Rubin, 1983; Becerril & Abdulai,2010;Dehejia & Wahba, 2002)
Objective four Determine the major constraints faced by parboiling households in the Northern region
Kendall’s coefficient of concordance
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Variable descriptions of the logit modelVariables Description Measurement Expt. sign ADPT Adoption status Dummy(1= Adopted 0 = Otherwise )
Zugu Dagboni only
Parboiler stays in Zugu Dagboni D(1= stays Zugu Dagboni 0 = Otherwise )
+
Nyohini only Parboiler stays in Nyohini D(1= stays Nyohini 0=Otherwise ) -
Nyankpala only Parboiler stays in Nyankpala D(1= stays Nyankpala 0=Otherw -/+
Education Educational level of respondent D(1= had formal education 0=Otherwise
-/+
Age Age of respondent Continuous(years) -/+
Marital status Marital status D(1=married 0=otherwise) +
Household size No of person being catered for Number of person +
Member of group Member of parboiling organization D(1=member 0=otherwise) +
Experience Years of rice processing experience Years +
Production capacity
Production capacity of the rice processor per month
No of bags +
Contact Contact with developmental organisation
D(1= contact organisation 0=otherwise)
+
Household size Household size of the respondent Number of person +
Hired labour Had used hired labour D(1= hired labour 0=otherwise) +
Household income Per capita income(GHs) Continuous +
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Study Area and Sampling Technique
Region District Community # Processors Total
Purposive Purposive Simple random(lottery method)
Northern
Tamale Metro
Nyohini 50120
Zakariyeli 20
Kpalsi 30
Gbalahi 20
Tolon Kumbungu
Tolon 40120
Gbalahugu 25
Nyankpala 35
Zugu Dagboni 20
TOTAL SAMPLE SIZE = 240
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ResultsLevel of IPBV technology adoption
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ResultsObjective one:
Adopters(n=80) Non-Adopters(n=160) Total(n=240)
VariablesFreq. % Freq. % Freq. %
AgeLess than 36 25.0 31.3 39.0 24.4 64 26.7
36-45 27.0 33.8 65.0 40.6 92 38.346-55 20.0 25.0 47.0 29.4 67 27.9Above 55 8.0 10.0 9.0 5.6 17 7.1Age_Mean 42.2 42.6 42.4
GenderFemale 80 33.3 160 66.7 240 100Marital statusmarried 74 92.5 149 93.1 223 92.9
EducationNo formal 66 82.5 129 80.6 195 81.3
Education_Mean 1.15 0.68 0.83
Household Size 5.7 6.1 5.9
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ResultsObjective one:
Adopters(n=80) Non-Adopters(n=160) Total(n=240)
VariablesFreq. % Freq. % Freq. %
Residential StatusNative 68 85.0 136 85.0 204 85Migrant 12 15.0 24 15.0 36 15Other occupationYes 55 68.8 81 50.6 136 56.7
No 25 31.3 79 49.4 104 43.3EthnicityDagbomba 156 97.5 79 98.8 235 97.9Religion Muslim 74 92.5 140 87.5 214 89.2
ExperienceLess than 11 33.0 12.5 71 44.4 104 43.511-20 38.0 47.5 68 42.5 106 44.221-30 8.0 10.0 19 11.9 27 11.2Above 30 1.0 1.3 2 1.3 3 1.2
Experience_Mean 12.7 12.6 12.6
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ResultsObjective one:
Adopters(n=80) Non-Adopters(n=160) Total(n=240)
VariablesFreq. % Freq. % Freq. %
Purpose Consume &sale 60 75.0 142 88.8 202 84.2Source of waterPipe borne 65 81.3 109 68.1 174 72.5Quantity of paddy/monthLess than 21 15 19.0 56 35.1
71 29.6
21-30 22 27.6 71.0 44.3 93 38.831-40 30.0 37.5 26.0 16.4 35 14.6Above 40 13.0 16.4 7 4.4 41 17.1
Quatity_Mean 32.3 26.3 28.3Member of PBOYes 74 92.5 39 24.4 113 47.1Credit Yes 42 52.5 45 28.1 87 36.3Contact Yes
73 91.3 106 66.3 127 52.9
Aware of PBV technologyYes
80 100 48 30.0 128 53.3
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Results: Objective two T-Test
:
Variables Measurement Adopters Non-adopters Diff T-testZugu Dagboni only D(1= Zugu Dagboni 0 =
Otherwise )0.150
0.050 0.100 2.670***
Nyohini only D(1=Nyohini 0=otherwise) 0.325
0.150 0.002 3.201***
Nyankpala only D(1= Nyankpala 0=otherwise) 0.263
0.088 0.175 3.709***
Education D(1=formal education 0=otherwise) 0.15 .087.
062 1.469
Age of respondent Continuous(years) 42.6 42.2 0.363 0.267
Marital status D(1=married 0=otherwise) 0.925 0.931 -0.006 -0.177
Household size Number of person 5.8
6.1 -0.310 -0.792
Member of group Dummy (1=member,0=otherwise)
0.925 0.243 0.681 12.965***
Experience Years 12.7
12.6 0.11 0.105
Production capacity No of bags 32.3
26.3 6.050 4.270***
Contact D(1= contact 0=otherwise) 0.913 0.338 0.575 9.977***
Household size Number of person 5.8
6.1 -0.31 -0.792
Hired labour D(1= hired labour 0=otherwise
0.238
0.138 0.053 1.948***
Outcome variablesHousehold income GHS 2916.46 2159.99 756.47 3.705**
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Results: Obj 2 Logit results
:
Variables Coefficient Standard Error P>[Z] Marginal effect
Zugu Dagboni only 4.135*** 0.6134 0.000 0.771
Nyohini only 1.632*** 0.3530 0.000 0.250
Nyankpala only 3.413*** 0.4989 0.000 0.645
Education 0.130** 0.0595 0.029 0.014
Age of respondent 0.040*** 0.0055 0.057 0.008
Marital status -0.296 0.5925 0.617 -
Household size -0.115** 0.0549 0.037 -0.013
Member of PBO 3.948*** 0.4026 0.000 0.514
Experience -0.025** 0.0070 0.029 -0.006
Production capacity 0.032** 0.0033 0.014 0.005
Contact 2.500*** 0.3366 0.000 0.280
Household size -0.115** 0.0549 0.037 -0.127
Hired labour -0.682* 0.3819 0.074 -0.006
Access 0.333 0.3005 0.268 -
Price -0.074*** 0.0310 0.017 -0.008
Other occupation -0.661*** 0.3410 0.053 -0.075
Constant -4.245 2.4381 0.082 -
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Results two Number of observations = 240 Psuedo R2 = 0.62*** LR chi2(16) = 184.12 Prob > chi2 = 0.0000 Log likelihood = -199.7286
*, ** and *** denotes 10%, 5% and 1% significance level respectively
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ResultsObjective three and four:
Variable Matching method
Treated Controls ATT* ATU* ATE* S.E. T-stat
Household income(GHS)
NN 2916.46 2294.69 621.8 519.5 553.6 225.26 2.76***
ATT= Average treatment effect on the treatedATU= Average treatment effects on the untreated ATE= Average Treatment Effect (overall)
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Results Objective four;
Constraints Adopters Non-Adopters
Mean rank score
Rank Mean rank score Rank
Lack of funds 2.32 1st 2.97 1st
Expensive fuel (fire wood) 3.6 2nd 3.4 3rd
Lack of equipment for parboiling3.88 3rd 3.67 2nd
Expensive/unreliable water 4.08 4th 3.93 5th
Lack of drying area 4.5 5th 4.33 4th
Distance to milling place is too far 5.21 6th 4.88 6th
Low storage capacity 5.31 7th 5.36 7th
Weak knowledge of drying operations 7.1 8th 7.47 8th
Kendall's Wa 0.335*** 0.34***
Chi-Square 187.686 381.282
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Findings All of respondents were female
About 53% were aware of the existence of the technology.
Education, Age ,member of PBO, contact with developmental organisation, access to credit, targeted communities and high production capacity increases the probability of adopting the iPBV technology
Price of paddy, having other occupation, household size,using hired labour and having a lot a experience reduces the probability of adopting iPBV technology
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Findings Adopting the improved rice PBV technology increases
the annual household income by 622 GHs
The major constraints facing the parboilers were lack of funds, expensive fuel (fire wood) and lack of equipment for parboiling.
Distance to milling place , Low storage capacity and weak knowledge of drying operations had minimal impact on their operations
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Conclusion
Improved rice PBV technology increases the household income for households who adopted the technology
Constraints facing the parboilers were lack of funds, expensive fuel (fire wood) and lack of equipment for parboiling.
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Recommendations Local artisans (such as welders, etc) and other stakeholders
should pick up the technology and produce more iPBV with local resources ;this will even reduce the cost of the technology.
Also stakeholders should encourage microfinance institutions to support rice parboilers with credit (since they are now creditworthy as a result of using the new technology which increases their incomes).
Institution such as FRI, CSIR and Universities should develop alternate source of fuel (such as one the can use rice husk) to reduce the cost of fuel for processing rice.
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The way forward
In principle the new technology offer an increase in income to the parboilers but it is expensive;
I. More developmental agencies should partner these women in other to acquire more of the technology for the women which has positive impact on their livelihood.
II. Microfinance institutions should also be challenge to provide these women with credit at low interest to enable them to purchase this technology as to improve their income.
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Some References A. Smith, J., & E. Todd, P. (2005). Does matching overcome LaLonde’s critique of
nonexperimental estimators? Journal of Econometrics (Vol. 125, pp. 305–353). doi:10.1016/j.jeconom.2004.04.011
Abdulai, A., Owusu, V., & Bakang, J.-E. a. (2011). Adoption of safer irrigation technologies and cropping patterns: Evidence from Southern Ghana. Ecological Economics, 70(7), 1415–1423. doi:10.1016/j.ecolecon.2011.03.004
Abebaw, D., & Haile, M. G. (2013). The impact of cooperatives on agricultural technology adoption: Empirical evidence from Ethiopia. Food Policy, 38, 82–91. doi:10.1016/j.foodpol.2012.10.003
Diagne, M., Demont, M., & Diagne, A. (2009). Adoption and impact of an award winning post-harvest technology : The ASI rice t hresher in the Senegal River Valley.
Dehejia, R. H., & Wahba, S. (2002). Propensity Score-Matching Methods for Nonexperimental Causal Studies. Review of Economics and Statistics. doi:10.1162/003465302317331982
Dandedjrohoun, L., Diagne, A., & Biaou, G. (2012). Determinants of diffusion and adoption of improved technology for rice parboiling in Benin. Review of Agricultural and Environmental Studies, 93, 171–191. Retrieved from http://www.raestud.eu/pdf/171-191-ncho.pdf
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Thank you for your attention
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Acknowledgements
Dr. (Mrs.) Irene S. Egyir and Dr. John Baptist D. Jatoe
AfricaRice African Development Bank(AfDB) Food Research Institute(FRI) The Economy of Ghana Network (EGN)