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Adoption, Yield, and Ex Ante Impact Analysis of Swarna-Sub 1

in Eastern India

T. Yamano, M. Malabayabas, and M.K. Gumma

T. Yamano is a senior scientist, M. Malabayabas is an assistant scientist, and M.K. Gumma is anassociate scientist at the International Rice Research Institute (IRRI).

STRASA wasestablished by IRRIand Africa Ricewith a view toreducing povertyand stabilizing riceproduction indrought and floodplagued and poorsoiled rainfedecosystems inSouth Asia and

Africa through theuse of moderntechnology.

STRASA is funded

by the Bill &Melinda Gates

Foundation.

STRESS-TOLERANT RICE

FOR AFRICA AND SOUTH

ASIA

STRASA Economic Briefs, No. 2 (March 2013)

1. Introduction

India has the largest rainfed lowland area in the world, with flooding being considered as

one of the most important abiotic stresses to rice production, after drought and weeds.

Flash floods are highly unpredictable, and may occur at any growth stage of the rice crop,

with the frequency of floods being expected to increase in the future because of climate

change. The International Rice Research Institute (IRRI) and its collaborators have

developed a submergence-tolerant rice variety, called Swarna-Sub1, which has been

distributed to rice farmers in eastern India since 2008. The seed distribution of Swarna-

Sub1 expanded significantly when the National Food Security Mission included Swarna-

Sub1 in its eastern India programs in 2010. About 38,000 tons of seed were distributed,

reaching an estimated 1.3 million farmers in 2012 alone.

Swarna-Sub1 survives full submergence for up to 14 days because it was developed by

introgressing a single quantitative trait locus (QTL) that causes submergence tolerance in

Swarna, a popular rice variety in eastern India. Under normal conditions, Swarna-Sub1 is

considered to show no significant differences in agronomic performance, grain yield, or

grain quality compared with Swarna. Few studies document the adoption and

performance of Swarna-Sub1 among farmers in nonexperimental settings and conduct ex

ante impact analyses of Swarna-Sub1 based on its estimated yield advantages under

different submergence conditions. To overcome this knowledge gap, we conducted farmer

surveys in eastern Uttar Pradesha (EUP) and Odisha in 2012, inquiring about rice

production during the 2011 kharif season. In this brief, we describe the information

obtained from the household surveys and present the results of an ex ante impact analysis

at the district level.

2. Data

The data used in this paper originate from surveys conducted in April to June 2012 in

EUP and Odisha. The same sampling procedures were employed in both states to

facilitate comparison. We selected these two states because they belong to different agro-

climatic systems and are less likely to be subject to submergence in a given season. This

condition is important for assimilating data under different submergence conditions in a

given season. In EUP and Odisha, we selected six and two districts, respectively, that are

prone to submergence and where local nongovernment organizations (NGOs) have been

distributing Swarna-Sub1 seeds. From local NGOs, we received lists of villages whereSwarna-Sub1 seeds had been distributed. Then, we randomly selected 36 villages in EUP

and 16 villages in Odisha.

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Table 1. Sample villages and households in Uttar Pradesh and Odisha.

Number of

sample

villages

Number of

sample

households

Number of sample

households Swarna-Sub1

users among

neighborsOriginal

usersNeighbors

(A) (B) (C) (D) (E)State % of (D)

Uttar Pradesh 36 570 134 436 34.7

Odisha 16 233 40 193 8.8

Total 52 803 174 629 22.7

Next, from the lists of farmers that received Swarna-Sub1 seeds, we randomly selected

up to four Swarna-Sub1 users per village. In this report, we refer to these farmers as

original users. In total, we interviewed 134 and 40 original users in EUP and Odisha,respectively (Table 1). In addition, we randomly selected an additional 12 villagers who

resided in the same villages as original users. Hence, we interviewed 363 and 192

randomly selected households in EUP and Odisha, respectively. To distinguish the

additional villagers from original users, we referred to them as neighbors, because they

resided in the same villages as original users. In total, we interviewed 803 households.1

When NGOs search for farmers that might agree to use Swarna-Sub1, they tend to

contact progressive farmers. Thus, original users should not be regarded as representative

farmers. Instead, we should regard neighbor households as representative households of

the sample areas. We find that the adoption rate of Swarna-Sub1 among neighbor

households is about 35% in EUP and about 9% in Odisha. The adoption rate is high in

EUP because government agencies have also distributed Swarna-Sub1 seeds in our

survey areas.

3. Swarna-Sub1 yields under submergence conditions

Figure 1 presents the average yields of Swarna-Sub1 and Swarna under different

submergence conditions, which are grouped according to the period of full submergence.

In 2011, severe floods occurred in Odisha, affecting almost all the sample households in

this state. In EUP, only a small number of sample households experienced floods in the

same year. By combining the data from the two states, we obtain rice yield data under

different submergence conditions and find that Swarna-Sub1 has yield advantages of 0.7

and 1.5 tons/ha over Swarna when the length of full submergence lasts from 1 to 7 days

and 8 to 14 days, respectively. The differences are statistically significant. When the

length of full submergence is longer than 14 days, the yield difference becomes small

because even Swarna-Sub1 cannot survive submergence durations greater than 14 days.

Under normal conditions (i.e., without submergence), we find only a negligible

difference between the yields. Our findings are consistent with agronomic studies such as

Ismail et al (2013). Although Swarna-Sub1 survives full submergence for up to 14 days,this cultivar still requires additional time to re-grow and generate grains after a flooding

event. In Odisha during 2011, submergence occurred mostly late during the rice

The household data used in this report were collected by NEFORD, an NGO based in Lucknow,

nd A.I.D., an NGO based in Bhubaneswar. We thank Dr. R.K. Singh, Dr. J.K. Roy, and staff at the

two NGOs for their excellent survey work.

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Fig. 1. Yields of Swarna and Swarna-Sub1 under submergence in eastern India.

growth process, in the panicle initiation and flowering periods. This partly explains the

decline in Swarna-Sub1 yield as the length of full submergence extends; however, its

yield under submergence is consistently higher than that of Swarna.

4. Ex ante impact analysis

Thus, we know that rice farmers could reduce crop losses caused by medium-duration

submergence by 1 ton/ha if Swarna-Sub1 is adopted. However, at the time of planting,

farmers do not know the risk of flooding in a given year. Hence, farmers must select rice

varieties, a priori, based on the subjective probability of medium-duration submergence.

We calculate the expected gain from adopting Swarna-Sub1, instead of Swarna, as

E(Gain) = Pr(S0) x YA0 + Pr(S1-7) x YA1-7 + Pr(S8-15) x YA8-15

E(Gain) represents the expected gain, Pr(Sx) represents the probability of submergence

for x days, and YAx represents the yield advantage of Swarna-Sub1 over Swarna for x

days of submergence. To calculate the expected gain, we must determine the probability

of medium-duration submergence. To obtain this figure, we rely on remote-sensing

techniques, which use moderate-resolution imaging spectroradiometer (MODIS) of 8-

day composite surface reflectance products. If we detect one location under

submergence in one image but not in the consecutive image, which was taken 8 days

later, we assume that the length of submergence was of short duration. If we detect one

location under submergence for two consecutive images, we term the length of

submergence as medium duration. If we detect submergence at one location for three

consecutive images or more, the length of submergence is considered as long duration.

By using MODIS data from 2000 to 2010, we calculate the probability of different

lengths of submergence, for short-, medium-, and long-duration submergence, at thedistrict level and obtain the expected gain of adopting Swarna-Sub1 based on the above

equation. We present the results of the district-level expected gain in Figure 2, which

clearly shows that the areas that would benefit most from Swarna-Sub1 are

For more information, please visit www.irri.org and http://strasa.org

7/30/2019 STRASA Economic Brief 2: Adoption, Yield, and Ex Ante Impact Analysis of Swarna-Sub 1 in Eastern India

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INTERNATIONAL RICE RESEARCH INSTITUTE

Los Banos, Laguna, Philippines DAPO Box 7777 Metro Manila

For more information please visit www.irri.org ; http://strasa.org

INTERNATIONAL RICE RESEARCH INSTITUTE

Los Baos, Laguna, Philippines, DAPO Box 7777, Metro Manila

For more information, please visit www.irri.org; http://strasa.org

Copyright International Rice Research Institute 2013. This material is copyrighted by the International Rice Research Institute and is

licensed for use under a Creative Commons Attribution-Non Commercial-ShareAlike 3.0 License (Unported).

Fig. 2. Expected gains (kg/ha) from adopting Swarna-Sub1.

lowland areas along the Ganga River at the border of Uttar Pradesh and Bihar and

northeast coastal areas of Odisha. The 10 districts with the highest expected gains are

Bhabua, Bhojpur, Buxar, and Rohtas in Bihar; Kendrapara, Baleshwar, and Bhadrak in

Odisha; East Midnapore and South 24 Parganas in West Bengal; and Chandauli in Uttar

Pradesh. The results shown in Figure 2 could be used to guide future seed distribution.

5. Concluding remarks

In this report, we clearly demonstrate the yield advantage of Swarna-Sub1 under

medium-duration submergence. The ex ante analysis presented in this report can be used

to guide seed distribution programs for Swarna-Sub1. However, caution must be taken in

the interpretation of the results. First, we use the yield data from just one kharif season in

2011. We must continue collecting yield data to obtain more accurate yield advantages

of Swarna-Sub1. Second, to shift from expected gains to expected production at an

aggregated level, that is, the state level, we must estimate the adoption rates of Swarna-

Sub1 at an aggregated level. Finally, the adoption rate of Swarna-Sub1 was just 9%

among our Odisha samples in 2011, although almost all sample households in Odishasuffered from severe floods. Significant amounts of rice could have been saved among

the nonadopters if they had adopted Swarna-Sub1. Further studies are required to

facilitate the faster dissemination of Swarna-Sub1.

References

Ismail AM, Singh US, Singh S, Dar MH, Mackill DJ. 2013. The contribution of

submergence-tolerant (Sub1) rice variety to food security in flood-prone rainfed areas in

Asia. Field Crops Research, forthcoming.