IJERD – International Journal of Environmental and Rural Development (2022) 13-1

Research article
erd

Impact Assessment of System of Rice Intensification
Adoption - Case from Madagascar MASATO KISHIMOTO*
Construction and Technology Institution, Tokyo, Japan
Email: seatma92@gmail.com

EIJI YAMAJI
Graduate School of Frontier Science, The University of Tokyo, Japan

TAKESHI SAKURAI
School of Agricultural and Life Sciences, The University of Tokyo , Japan
Received 31 January 2022

Accepted 23 April 2022(*Corresponding Author)

Abstract The System of Rice Intensification (SRI) is expected to improve rice yield withminimal impact on harming environment. While many studies have confirmed that the yield
increases with adopting SRI by field surveys, the impact of SRI on household income isstill debatable because SRI is a labor demanding method and may cause labor redistribution
within a household. This study assesses the impact of SRI on the yield, household income,expenditure and caloric consumption in Madagascar, taking into account the endogeneity
between farmer’s capacity and adapting technologies. The authors collect the data forsmall-scale rice producing households in Alaotra-Mangoro region on Madagascar central
highland in 2014 and 2017 by a face-to-face questionnaire survey. The authors find that the
adoption of at least one component of SRI has no significant impact on the rice yield,
income, expenditure and caloric consumption of households on average compared withthem that adopt none of the SRI components, taking account of the endogeneity oftechnology adoption. This study applies Propensity Score Matching (PSM) to take accountof the endogeneity. Then, comparing mean variables with using fertilizer by using PSM, theauthors confirm the positive impact on yield by plot level. However, because households
can’t adopt both SRI and the use of fertilizers for all plots, no significant difference isobserved in household income and expenditure. The findings suggest that a combination of
SRI with fertilizer inputs may increase yield significantly, if more farmers in the area start
using fertilizers in the future. Provision of technical SRI training alongside sales offertilizers is crucial. However, it is needed to conduct further research in our study site to
explore the impact on the household adopted all four of the SRI components which is more
effective, and long-term effects of SRI.
Keywords system of rice intensification (SRI), Madagascar, propensity score matching(PSM), impact assessment, technology adoption, small-scale rice farmers

INTRODUCTION
Sustainable agriculture that reduces environmental load and increases food production has been
attracting attention in recent years. System of Rice Intensification (SRI) is one of such a sustainableagriculture that has been drawing attention. This study focuses on the impact brought about by theuse of SRI in the Republic of Madagascar, the birthplace of SRI.
Madagascar is in Sub-Saharan Africa where population is growing rapidly, and is a major
producer of rice, its staple food. While most of its citizens engage in agricultural activities, thecountry suffers from low rice productivity and depends on imports for approximately 10% of its
consumption. Poverty rate in rural areas is quite high at 78%. Improved rice productivity is
considered to be a contributing factor towards poverty reduction in Madagascar.
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SRI is a rice cultivation method developed in 1993 by Father Laulanié and is based on his
observations of local farming methods as well as his own cultivation experiments (Stoop et al.,2002). SRI is practiced in many countries, particularly developing countries, thanks todissemination activities led by Norman Uphoff and others.
SRI is not a single package but rather a system that combines principles for transplantation as
well as soil and water management, does not require fertilizers and other exogenous inputs, and is
expected to promote tillering in rice plants and increase yield. The following four practices are
considered to be central principles of SRI in many areas where SRI is practiced (Noltz et al., 2012):(1) The use of young seedlings: transplanted within 15 days after germination (care must be
taken to ensure roots are not damaged), (2) Single seedling transplanting: A single seedling istransplanted per hill, (3) Planting at wider spacing: planting at 20cm × 20 cm spacing, (4)Intermittent irrigation: dry the soil moderately instead of ponding at all times. However, ensure thatsoil remains moistened.
While income from rice cultivation due to improved productivity is expected to increase,results vary by regions in terms of the impact of SRI on household income of farmers (Berkhout etal., 2015).
In East Timor, impact of SRI is observed with endogeneity of the adoption of agricultural
technology taken into account. As a result of taking endogeneity into account, SRI was found tohave an effect on the yield increase, but the difference in income between farmers who adopted
SRI and farmers who did not was quite small (Noltze et al., 2012). Similarly, a study thatconsidered endogeneity in Indonesia found that SRI increased yield but did not affect the income of
farmers. This was because the time previously spent by farmers to earn non-agricultural income
was now being spent on the labor required for rice cultivation. (Takahashi and Barret, 2013).
Another study found that SRI increases yield in areas without an irrigation facility but does not
improve income (Alem, 2015).
The impact of SRI on yield varies by region. On the other hand, improved agricultural
productivity affects household budget in various aspects. This includes an increased consumption
at home by farmers and consumption of food with higher nutritional value due to improved income(Pandey et al., 2016). In India, one study has found that farmers who adopted SRI are purchasing
insurance and consuming food with higher nutritional values (Singh et al., 2017). However, no
study has assessed its impact on expenditures and consumption while taking endogeneity into
account.
Madagascar is the origin of SRI, and previous studies have attempted to find a correlation
between SRI and rice yield as well as identify components of SRI that are crucial in increasing theyield (Barison and Uphoff, 2011; Tsujimoto et al., 2009). Another study has investigateddetermining factors that leads to the adoption of SRI as well as inhibiting factors (Moser andBarrett, 2003). On-site surveys have shown that SRI is effective in improving yield compared to aconventional farming method (Barrett et al., 2004, Barison and Uphoff, 2011).
While several studies have investigated factors associated with an adoption of SRI and factorsthat cause an increase in yield, few studies have focused on the impact of adoption of SRI on
farmers in Madagascar, and as far as the author is aware, a study on such an impact that takes
endogeneity of the technical adoption into account is particularly lacking.
OBJECTIVE
The objective of this study was to estimate the impact of SRI on the improvement of productivity
and livelihood of farmers in central highlands of Madagascar. Impact of SRI on the welfare of ahousehold is elucidated through a survey on the household income of farmers as well as theirexpenditure and food consumption.

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METHODOLOGY
Two communes, Ampitatsimo and Ilafy, located in Ambatondrazaka District in the AlaotraMangoro Region of Madagascar, were chosen as study sites. Irrigated area by Lake Alaotra islocated 240km northeast of the capital Antananarivo at 800m above sea level, and its climate is atropical highland climate. Rice cultivation and zebu cattle grazing have been practiced in the region
since the 19th Century (Yokoyama and Sakurai, 2014). Rice production in Lake Alaotra Region isamong the largest in the country and includes District PC15, one of the large-scale irrigated ricecultivation districts from the French colonial era (Fujiki, 2015). Rice cultivation period is long andlasts five to six months, and rice is usually grown once a year.
Fukuda (2015) investigated characteristics of SRI farmers in Ambatondrazaka District.
Farmers in this area combined technologies per plot with respect to varieties, transplantation, and
SRI. SRI was utilized in combination with the conventional practice. Risk preference also
influenced the decision of technologies. Risk-loving husband were more likely to adopt SRI. On
the other hand, more risk-aversive wives tended to choose conventional varieties and sort seeds.
Survey on an Introduction of SRI
A team led by Professor Sakurai of the University of Tokyo conducted a survey of Ambatondrazaka
District in 2014. Survey method is discussed below (Fukuda, 2015). Ampitatsimo consists of eightvillages (fokontany), and Ilafy consists of twelve villages. Average population per village wascalculated by dividing the total population of the commune by the number of villages, and four
villages were selected from Ampitatsimo and six from Ilafy. 40 rice farmer households wererandomly selected from each village (for a total of 400 households), with whom a face-to-facequestionnaire survey was conducted. The survey covered a broad range of topics including
socioeconomic attributes, income, food expenditures of farmers, the use of inputs at a plot level,
adoption of the technology, and yield, and it was conducted twice from May to June in 2014 andagain August 2014.
Number of plots managed by farmers totaled 1,337 plots, of which 732 plots were rice paddies
where rice was being cultivated. Surveyed farmers also participated in risk experiment in order tomeasure their risk preference.
335 households and 646 plots were used as survey data after removing missing values andoutlier data. Data from farmers who could not respond during the second survey period, farmers
whose responses were insufficient, and farmers whose number of cultivated plots increased
between the first and second survey periods were removed.
Survey on Knowledge on SRI and Decision on Its Implementation
Additional survey was conducted in December 2017 to clarify the path of SRI dissemination andthe state of its implementation. A semi-structured interview was conducted with eighteen farmer
households that has partially adopted SRI components, nine households who has not adopted any
SRI components from the previous survey. Additionally, the interview was conducted with two
agricultural bureau staff at the surveyed district, one head of the irrigation association, and one
Japanese specialist staff.
Analysis Framework and Method
Average treatment effect on the treated (ATT) is used to measure the difference of the average
between SRI farmers (i.e. treated group) and non-SRI farmers (non-SRI group) (Wooldridge, 2010).
(1)

Where yi1 shows the results for treated group, and y0i shows the results for control group. InⒸ ISERD

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this study, y is defined as the income of an SRI farmer or a yield from an SRI plot. Additionally, i is
the identification number assigned to each farmer. Technology is adopted when Di=1 andtechnology is not adopted when Di=0. Since yi1 and y0i cannot be measured at the same timeagainst i-th farmer, E(y0i │ Di=1) is replaced with measurable data from a non-SRI farmer.
Typically, a difference in farm management capability and motivation is assumed between SRI
farmers and non-SRI farmers, and such a difference causes bias in the results. Propensity Score
Matching (PSM) is used to address the bias from replacement (Rosenbaum and Rubin, 1983).
PSM assumes that an adoption of SRI is determined by an observable variable. If the adoption
is determined by an observable variable, the following equation can be derived.
(2)

Where p(xi) shows a probability that SRI is used under observable variable x.
(3)

PSM requires another assumption. Covariance of SRI farmers and non-SRI farmers need togreatly overlap. In another words, 0<p(xi)<1 needs to be satisfied. The following equation isderived from Equation (1).
(4)

From the above equation, the impact of SRI can be evaluated while taking endogeneity into
account. However, in order to minimize the estimation error of PSM, inclusion of every variableassociated with SRI adoption is recommended. If a variable that is not observed affects the
adoption of SRI, a bias may exist in the ATT result as well. Methods for matching treatment groupand control group includes nearest-neighbor matching, stratification matching, radius matching,and kernel matching, among others (Wooldridge, 2010). A matching method that minimizes thepseudo-coefficient of determination and error after estimation was chosen.
Factors that determine SRI adoption were analyzed in order to calculate aforementioned
propensity scores. Farmers presumably combine agricultural technologies independently for eachplot. Therefore, propensity scores were calculated for each plot. Logistic regression was used to
calculate propensity scores.
(5)

Where y is adoption of the technology (y＝1: SRI plot, y＝0: others), β0 is slices, and xk isvariable pertaining to adoption.
Hypotheses
This study asks two research questions: "How does SRI technology affect rice yield" and "howdoes SRI affect farmers?".
A pair of hypotheses are validated. First, fields where SRI is implemented produce greater
yields compared to non-SRI fields. Second, an increase in rice yield leads to an increase in riceincome, resulting in an overall increase in income for the household of the farmer. Over the courseof validating hypotheses, any changes in expenditure and personal caloric consumption are also
noted even when the income of farmers who has adopted SRI has not increased.
RESULTS AND DISCUSSION
Results of Introducing SRIⒸ ISERD

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For analysis, an SRI plot is defined as a plot where at least one of the components ((1) Use ofyoung seedlings within 14 days after sowing, (2) Single seedling transplanting, (3) Transplanting
by spacing of at least 20cm, (4) Intermittent irrigation) is adopted because farmer adapting allcomponent is very few. A farmer is identified as an SRI farmer if the household practices SRI in atleast one of its cultivated plots.
Table 1 The results of a comparison based on whether SRI adaptation by plot level
Variable
Cultivated area (ha)Dummy for PC15
Presence of an irrigation facility
Dummy for land ownership
Dummy for land fertility
Weeding frequency
Dummy for transplantation
Dummy for the use of commercial varieties
Seed usage (kg/ha)
Total chemical fertilizer usage (kg/ha)
Total organic fertilizer usage (kg/ha)
Distance to the plot (min)Yield (t/ha)
Rice productivity per person (kg/person)
Revenue from rice (1,000Ar/ha) …A
Fertilizer cost (1,000Ar/ha)
Pesticide cost (1,000Ar/ha)
Herbicide cost (1,000Ar/ha)
Seeds cost (1,000Ar/ha)
Land improvement cost (1,000Ar/ha)
Hired labor cost (1,000Ar/ha)# non-hired laborers (man-days/ha)
Cost of rice cultivation (1,000Ar/ha) …B
Cost incl. non-hired labor (1,000Ar/ha) …B’
Income from rice (1,000Ar/ha)… (C = A – B)
Profit from rice (1,000Ar/ha) … (D = A - B’)Observed
Note: *** p<0.01, ** p<0.05, * p<0.1

SRI ave.
0.60
0.35
0.58
0.64
0.10
1.06
0.96
0.71
147
1.20
1,149
24.1
2.91
19.3
2,120
51.6
6.01
6.677
111
61.4
272
289
509
1,379
1,611
742
112

Non-SRI ave.
0.75
0.14
0.64
0.64
0.15
0.86
0.61
0.78
158
1.17
734
40.5
2.34
28.5
1,703
36.9
4.25
6.675
103
47.6
172
190
371
942
1,333
762
521

Total ave.
0.72
0.18
0.63
0.64
0.14
0.89
0.67
0.77
156
1.17
810
37.6
2.44
26.9
1,777
39.5
4.57
6.676
104
50.0
190
207
395
1,019
1,382
758
633

SRI-Non-SRI diff.
-0.15
0.20***-0.0550.0018-0.0520.21***
0.35***
-0.68
-12
0.033
415*
-16.4**
0.57***-9.23
417***
14.7
1.76*
0.002
8.32
13.8
100***
99**
139***
437***
278*-20.2

Table 1 shows the results of a comparison based on whether SRI is adopted or not at a plotlevel. Significant differences between SRI plots and non-SRI plots were observed for presence ofPC15, weeding frequency, transplantation, amount of organic fertilizer used, distance from home toplots, cost of hired labor, and number of labor days worked by non-hired laborers.
Ratio of transplantation is higher among SRI plots since three of the SRI components(excluding intermittent irrigation) are techniques related to transplantation. Intermittent irrigation
requires an irrigation facility, and the ratio of intermittent irrigation and the ratio of District PC15
was greater for SRI plots. Weeding work was performed more often in SRI plots due to intermittent
irrigation. Greater number of organic fertilizers used in SRI plots was due to recommendations
being made towards the use of organic fertilizers at the time of SRI adaptation. Greater hired andnon-hired labor in SRI plots was also consistent with previous studies, which confirmed thepossibility that SRI is a more labor-intensive farming method.
Yield increased by 0.57 (t/ha) in SRI plots. At the same time, cost incurred by rice cultivation
also increased. Based on the market price for Alaotra-Mangoro Region from 2014, price per kg of
rice was assumed to be 728 (Ar/kg). Rice income per ha was greater in SRI plots at 10%
significance level. Cost of non-hired labor was calculated by assuming the mode of hired labor cost
as the employment wage within the area. Significant difference was not observed in profit
calculated after including a non-hired labor cost. Significant difference was not observed for riceproductivity per person (kg/person), and the adoption of SRI in the area has not improved labor
efficiency. Additionally, farmers who adopted SRI were accounted for 23% of the total households,
and average yield was 2.32 (t/ha).

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Impact of Each Variable on the Adoption of SRI
The impact of each variable on the adoption of SRI at a plot level, calculated by using a logit model
which can estimates probability to adapt the SRI. Variables that had a negative impact on the
adoption of SRI were cultivated area, number of family members, female family head, distancefrom home to the field, and the commune in which the farmer lives. Variables that had a positive
impact on the adoption of SRI were availability of irrigation, PC15 dummy, number of years ofeducation, number of traders the farmer knows, and knowledge on intermittent irrigation.
Estimated ATTTable 2 shows the estimated ATT. At a plot level, yield was greater in SRI plots than non-SRI plots
and income, but its difference was not significant. Both hired and non-hired labor were greater in
SRI plots. In particular, non-hired labor was 113 (man-days/ha), which was significantly larger at
10% significance level and showed a much greater need for labor in SRI plots. No significant
differences were observed for other variables, which show that technologies other than adopted SRI(e.g. fertilizer inputs) do not make a difference between SRI and non-SRI plots. At a household
level, no significant difference was observed in yield between SRI and non-SRI farmers. Income
from rice and income for the entire household were greater among SRI farmers, but no significant
differences were observed. Income by means other than labor was the only variable where asignificant difference was observed between SRI and non-SRI farmers; SRI farmers weregenerating a greater amount of income through remittance and land lease. These results indicatethat the adoption of SRI has not had an impact on yield and income in the area at a household level.
Table 2 Estimated results by ATT
Plot level
Variable

ATT result (SRI plots - non-SRI plots)

Standard error

Yield (t/ha)
Cost of rice cultivation (1,000Ar/ha)
Income from rice (1,000Ar/ha)
Profit from rice (1,000Ar/ha)# non-hired laborers (man-days/ha)
Hired labor cost (1,000Ar/ha)
Total chemical fertilizer usage (kg/ha)
Total organic fertilizer usage (kg/ha)
Seed usage (kg/ha)
Observed

0.37
29.2
243
-95.4
113*
44.4
-2.05
113
-9.59
630

-0.32
-65
-153
-212
-70.0
-43
-2.48
-338
-17.2
-

ATT result (SRI farmers -non-SRI farmers)

Standard error

Household level
Variable

Average yield for a household (t/ha)
0.39
0.39
Household income (1,000Ar)
601
609
Income per person (1,000Ar/person)
77.8
126
Income from rice cultivation (1,000Ar)
244
472
Income from crops excl. rice (1,000Ar)
-36.9
104
Income from self-employment (1,000Ar)
-14.3
184
Non-agricultural income (1,000Ar)
-1.99
122
Income from livestock (1,000Ar)
101
87
Non-labor income (1,000Ar)
309***
130
Food expenditure (1,000Ar / week)
1.16
2,41
Total expenditure (1,000Ar/ month)
12.4
24,7
Calorie consumption per person
173.3
-30.2
(kcal/day)Observed
325
Note: *** p<0.01, ** p<0.05, * p<0.1
Plot level uses Kernel matching was used as a matching method. Bandwidth was 0.01, and resampling was iterated
900 times by bootstrap method to obtain a standard error.
Household level uses Radius matching was used as a matching method. Radius was 0.06.
Observed number is different from Table1 because some date is not suitable due to missing parameter.
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Knowledge on SRI and Decision on its Implementation
Fig. 1 shows the timing in which farmers became aware of SRI, and shows components regarded asa part of SRI technology in the studied area. While there were some differences in terms of therecognized techniques that constitute SRI, all 27 farmer households interviewed knew about SRI.
Diverse timing in which farmers became aware of SRI and various paths through which SRI
disseminated indicate that the word "SRI" itself is widely known in the studied area. However,institutions such as JICA and the local agricultural bureau have also disseminated othertechnologies, and it is quite possible that farmers confuse these technologies with SRI.
Highest number of farmers that learned about SRI was recorded in 2000, a year in which
extension workers of an NGO have disseminated the SRI technology in several communes.
Importance of water management was recognized in many households. Many farmers also felt theimportance of using relatively innovative technologies, including the use of chemical fertilizers andpesticides and the use of a rotary weeder. While many farmers said that regular planting and row
planting are important, only three respondents saw increased spacing between rows (a uniquefeature of SRI) as important, four saw single seedling transplanting as important, and two saw theuse of young seedlings as important.
Results suggest that farmers in this area may be recognizing new technologies also as "SRI",in spite of the fact that they are not a part of the four major components that constitute SRI.
0

Number of responses
5
10

15

Adoption of intermittent irrigation
Organic fertilizers
Use of chemical fertilizers
Liquid fertilizers
Pesticides
Regular planting
Row planting
Interrow spacing at or over 10 cm
Interrow spacing of 20 – 25 cm
Single seedling transplanting
Use of young seedlings
Transplantation with care
Use of a rotary weeder
Leveling
Use of good seeds
SRI

Non-SRI(N=27)

Fig. 1 Component techniques of SRI(N=27)

Fig. 2 Period in which farmers know about SRI

Impact of Fertilizer Inputs
Soil fertility in the studied area is low, and phosphorus deficiency is particularly evident (JICA,
2017). For this reason, widening the spacing between seedlings only widens the space and is likely
to reduce yield. In the farmer’s interview, some farmers indicated that farmers also viewed therelationship between land fertility and seedling spacing as important. Fertilizer inputs itself isassumed to contribute greatly to yield improvement. In addition, if seedlings are planted at wider
spacing while fertilizers are applied, merits of SRI such as seed savings and an increase in thenumber of tillers can be expected.
Therefore, differences in yield and income due to whether fertilizer are applied or not as well
as a combination of fertilizer inputs and SRI were verified using data from 2014.
Table 3 shows the results. Estimation after matching shows an increase in average yield due tofertilizer inputs. However, a significant difference in income was not observed due to an increase infertilizer cost and hired labor cost. When fertilizer inputs were combined with SRI, yield increased
by 0.61 (t/ha). While the cost of rice cultivation increased, income per ha also increased due to asignificant increase in yield. However, income did not increase when non-hired labor wasconverted to cost due to an increase in the amount of non-hired labor. At a household level, nosignificant differences were observed in rice yield and thus income from rice cultivation, and no
significant differences were also observed in other incomes.
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Table 3 Impact of fertilizer inputs
by plot
Variable
Yield (t/ha)
Cost of rice cultivation (1,000Ar/ha)
Income from rice (1,000Ar/ha)
Profit from rice (1,000Ar/ha)
Seed usage (kg/ha)
Cost of hired labor (1,000Ar/ha)# non-hired laborers (man-days/ha)
Observed
per household

Estimation by ATT
Fertilizer (Fertilizer = 297)
Fertilizer + SRI (Fertilizer + SRI = 61)
0.37**
0.61***
130***
145***
138
302**
53.0
66.1
20.1*
20.1
36.7**
86.0***
28.4
78.6*
630
630
Estimation by ATT

Variable
Fertilizer (Fertilizer = 181)
Fertilizer + SRI (Fertilizer + SRI = 50)
Household income (1,000Ar)
82.6
588
Income per person (1,000Ar/capita)
5.29
136
Income from rice cultivation (1,000Ar)
197
416
Average yield for a household (t/ha)
0.26
0.33
Income from crops excl. rice (1,000Ar)
11.0
34.0
Income from self-employment (1,000Ar)
-123
-112
Non-agricultural income (1,000Ar)
28.9
47.8
Income from livestock (1,000Ar)
0.875
91.1
Non-labor income (1,000Ar)
-31.5
111
Food expenditure (1,000Ar / 1 wk)-0.361-0.098
Total expenditure (1,000Ar/ month)
16.9
-16.8
Calorie consumption per person (kcal/day)
17-37
Observed
325
325
Note: *** p<0.01, ** p<0.05, * p<0.1
By plot level uses radius in radius matching for fertilizer use was 0.04, and radius for fertilizer + SRI was 0.01
Per household level uses radius in radius matching for fertilizer use was 0.05, and radius for fertilizer + SRI was 0.06.

As a result, the difference in household income due to fertilizer inputs was not significant.
This result was also the same for a case in which the use of fertilizers and SRI were combined.
Lack of difference in yield and income at the household level may be due to the fact that thetechnologies were not being applied across all cultivating plots.
Comparison of average yield difference between years 2016/2017 and 2013/2014 showed areduction in average yield for 2017 by 0.68 t/ha. This is likely due to a dearth of rainfall in
2016/2017, which led to a poor harvest for the year with a significant reduction in average yield.
Weather conditions such as rainfall were not controlled, but they suggested that an increase in yield
between 2014 and 2017 was unlikely.
CONCLUSION
This study investigated the impact of SRI on yield and living expense among rice farmers in two
communes in Ambatondrazaka District of Madagascar. In the analysis, yield, household income,and expenditure were compared by using data obtained by on-site surveys. PSM was used toaccount for selection bias and compare average yield between SRI and non-SRI plots, whichshowed that yield was greater in SRI plots but without a significant difference. Improvement in riceincome due to an adoption of SRI was not observed. While the household income was greater for
SRI farmers, there were no significant differences between two groups. Differences due to SRI
adoption were not observed with regards to a week's worth of food expenditure and expenditure permonth by the farmer. Similarly, consumed calories were calculated based on food consumption by
farmers, but no difference due to the adoption of SRI was observed.
Interview results from 2017 showed that the term "SRI" is widely known among farmers.
However, details of the technology recognized by farmers varied greatly, which implied that SRI is
a technology whose name is well-known, but its details are not accurately known.
Considering low soil fertility of the studied area, wider spacing between seedlings may reduceyield. On the other hand, high yield may be achieved by improving soil fertility through fertilizerⒸ ISERD

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inputs and adoption of SRI. Survey results from 2014 also confirmed that yield increases when SRI
is combined with fertilizer inputs. In this case, cost incurred to cultivate rice increased at a plotlevel, but income also increased, thereby indicating the importance of combining fertilizer inputs
with SRI components. Even in this case however, because households were unable to adopt both
SRI and the use of fertilizers for all plots, no significant difference was observed in income fromrice cultivation and household income.
In the future, a combination of SRI with fertilizer inputs may increase yield significantly, if
more farmers in the area start using fertilizers. Provision of technical SRI training alongside salesof fertilizers is crucial.
Future Research
Among farmers surveyed in this study, only one household adopted all four of the SRI components.
In the analysis, farmers who have adopted some of the SRI components were defined as farmers
who have adopted SRI. SRI is considered to be most effective when all of the components are
adopted (J-SRI, 2011). For this reason, any area nearby the site for this study where SRI is widelypracticed may have adopted all components of SRI and thus increased the yield. In addition,comparison per SRI component was not possible due to the sample size, and an identification ofcomponent(s) that is important for the study site could not be conducted.
This study did not consider the number of years through which SRI is continually practiced.
One study has suggested that farmers who have continued to practice SRI for a number of years areaccustomed to the technology and thus able to improve their productivity (Moser and Barrett 2003).
An analysis that accounts for the number of continuously practiced years would be important inmeasuring long-term effects of SRI.
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