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In addition to the unavailability of modern varieties, their poor threshabilityand thatchability, the requirement for additional capital and labor, excessiveweed infestation, the lack of timeliness or availability of fertilizer, and lack ofcredit along with knowledge and cultural practices may be instrumental totheir slow adoption in this region. The adoption of component technologiessuch as fertilizer and pesticides seems to have been affected by the adulterationprevalent in the market. The input delivery system is very weak inBihar. The region also lacks research and development and appropriate extensionservices. Poor roads, communications, and market infrastructureare also important constraints.Addressing some of these constraints through appropriate research andpolicy intervention could have a large impact on the adoption of modernvarieties and their component technologies.The introduction of high-yielding modern varieties popularly known as seed-fertilizertechnology in Indian agriculture during the mid-1960s has led to a marked increasein the growth rate of agricultural output and has been instrumental in transformingtraditional household agriculture into modern, commercial agriculture in someof the agriculturally developed states. The rainfed rice production system, which islargely confined to the eastern part of India, lagged far behind the Green Revolutionbelt in terms of agricultural development and prosperity. Of late, it has been recognizedthat future sources of agricultural growth lie in this region.The adoption of modern varieties (MVs) and associated technologies seems tooffer an opportunity to increase output and income substantially. But even now, thepattern and pace of adoption of MVs of rice and other component technologies havemet with only partial success, particularly in the rainfed rice system. For instance, therice area under high-yielding varieties (HYV) in Bihar is 60%, whereas it is 94% inPunjab. The conventional wisdom is that constraints to the rapid adoption of innovationsinvolve factors such as the lack of credit, limited access to information, aversionto risk, inadequate farm size, inadequate incentives associated with farm tenure arrangements,insufficient human capital, the absence of equipment to relieve laborshortages (thus preventing timeliness of operations), the chaotic supply of complementaryinputs (such as seed, chemicals, and water), and inappropriate transportationinfrastructure (Feder et al 1985).The purpose of this chapter is to provide an analysis of constraints to the adoptionof MVs of rice in eastern India on the basis of a survey of various studies thathave attempted to explain these constraints and component technologies for MVs aswell as a study of farm-level primary data obtained from eight villages, two eachbelonging to Pusa and Kalyanpur blocks of Samastipur District in the north Biharplains and Pali and Bihta blocks of Patna District in the south Bihar plains, to makethe study more comprehensive and meaningful. Among the major rice-producing statesin eastern India, Bihar was selected because, even after more than three decades of306 Kumar and Jha
the Green Revolution, the coverage of HYV rice area is merely 60%, which is aheadof only Assam (50%).This chapter has two main parts. The first section briefly reviews some of therelevant past work. Because the volume of such published research is overwhelming,we have attempted simply to review some representative work rather than to presentan exhaustive discussion of all work. The second section attempts to identify andanalyze constraints to the adoption of MVs and other component technologies in therainfed lowland ecosystem of Bihar.To summarize the vast amount of empirical literature on adoption constraintssystematically, we organized the review of this work according to the key constraintsto adoption.Biophysical constraintsThe bulk of rice in the rainfed ecosystem is grown in the rainy (kharif) season, inwhich the vagaries of the monsoon, characterized by drought or floods, as well as thereoccurrence of other biotic and abiotic constraints are remarkable. The hot and humidclimate supports the outbreak of several harmful pests and diseases. Since it isnot possible to manipulate nature (climate), we need to incorporate sufficient toleranceand adaptability into the rice varieties to be developed for the rainfed ecosystem.The lack of tolerance in rice varieties for abiotic constraints such as flash floods andfrequent drought as well as biotic constraints such as gall midge, brown planthopper,tungro, sheath blight, and bacterial blight seems to affect the adoption of modern ricevarieties and their component technologies in the rainfed rice ecosystem. Tripathi(1977) identified susceptibility of HYVs to diseases and pests, low germination, ineffectivenessof dry seed treatment, nonavailability of irrigation water in summer forthe nursery, and serious waterlogging in the wet nursery as important constraints incoastal Orissa, whereas Gowda and Jolihal (1969) have reported the unsuitability ofMVs for late planting as an important constraint. The lack of irrigation is also one ofthe most limiting factors affecting the adoption of MVs and their associated technologies.Roy (1976) found inappropriate irrigation facilities as the most important constraintto the adoption of HYVs in the kharif season besides disease incidence and thelack of suitable varieties in West Bengal. Shakya and Flinn (1985) examined factorsinfluencing the adoption of MVs and fertilizer in the Tarai of southeastern Nepal andstated that adoption of MVs is highest where irrigation exists. Because rice lands ineastern India will remain rainfed in the foreseeable future, a greater spread of MVsinto these adverse environments will probably depend on new varieties being bredthat are specifically adapted to these environments.Constraints to the adoption of modern varieties of rice . . . 307
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The International Rice Research Ins
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Monitoring rainfed and irrigated ri
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ForewordRainfed rice areas are asso
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AcknowledgmentsIRRI is most gratefu
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2 Singh et al
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development, for example, provision
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subecosystems were recognized withi
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Table 3. Methods commonly used in e
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Table 4 continued.Scale of analysis
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Table 4 continued.Scale of analysis
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This included standard countrywide
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deepwater rice ecosystems. The rese
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Table 5 continued.Main MethodologyC
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Table 5 continued.Main MethodologyC
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Table 5 continued.Main Scale presen
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levels of involvement. For example,
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●●●ecosystem classifications
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Conclusionsclearly that they are di
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IRRI (International Rice Research I
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Widawsky DA, O’Toole JC. 1990. Pr
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Rice is the staple food crop for mo
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first working group to identify the
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TropicsSubtropicsTemperateSummer/wi
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ferred it for wide adoption by farm
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ing, remote sensing, and computing
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ice environments will be needed to
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Insects and diseasesInsects and dis
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The completeness of characterizatio
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Table 7. Levels and scales for agro
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Jamin JY, Andriesse W. 1993. Discus
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Tools and methodologiesfor biophysi
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Effect of climate, agrohydrology,an
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to water deficit because the crop
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for different periods of the year:
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depth scenarios (shallow, medium, a
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Water table depth (cm)500Shallow wa
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Simulated yield (kg ha -1 )6,0005,0
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Perception, understanding,and mappi
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and rice yield at regional or more
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SubareaSampling sites:GridTransectR
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was approximately 2,000 m with a to
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kg -1 in 50% of the topsoil and sub
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Table 3. Class medians were calcula
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Hard point dataClay, silt, sandHard
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A. Silt (%) B. 0.5 ccdfC. 0.2 ccdf
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In summary, the chosen geostatistic
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elated over slightly longer distanc
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Miura K. 1990. Genetic features of
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Rainfed lowland rice, growing with
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tively. In 1993, following dry till
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Rainfall (mm)Water table depth (cm)
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Saturated hydraulic conductivity (c
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in the uncompacted C0 plots (6.7 wk
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Clay classified≤ 2% 50 ha (2% but
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NotesAuthors’ addresses: D. Harnp
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target area of a breeding program.
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which is calculated from the estima
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hence grain yield. The three major
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ainfall data for each location. Mea
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such as 1980 and 1996, yield was hi
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Table 1 shows the results of the se
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Grain yield (t ha -1 )3UBN 19942103
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decreased with the use of old seedl
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The use of five genotypes with diff
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Mackill DJ, Coffman WR, Garrity DP.
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In rainfed agriculture, crop perfor
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GrainSite Year Code Group yield San
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Criteria considered for selecting r
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Table 1. Characteristics of the ref
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equired as the quality of the repro
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Cooper M, Rajatasereekul S, Immark
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144 Amien and Las
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As Indonesia’s staple food, rice
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Soil and climate of rainfed lowland
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isky when the crop is planted late.
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The decrease in harvested area only
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than in tidal swamp rice, for which
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Monitoring rainfed and irrigated ri
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and, indirectly, methane emission f
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Radar backscatter (dB)-7ERS windsca
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ERS SAR imageseries2. RSpreprocessi
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Fig. 6. Supervised classification o
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ConclusionsMonitoring of rice crops
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Characterizing soil phosphorusand p
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Table 1. Area and distribution of s
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Table 2. Lowland area (ha) classifi
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Fig. 1. Extractable soil P map (25%
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Characterizing soil phosphorus and
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Table 4. Recommendations for P appl
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Fig. 4. Extractable soil K map of t
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Fig. 5. Extractable soil K map of t
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● acidic pH (< 6)● low organic
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trials, K recommendations for uplan
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O’Brien DT, Blair G, Lefroy R. 19
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Planning and managing rice farmingt
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lowlands is submergence-prone. Ther
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situations and the allocation of re
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estimation of drought were determin
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Table 2. Effect of date of sowing,
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from October to February and a summ
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Table 3. Promising areas for ground
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1. There are possibilities of growi
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mmmm450350250150ASoil moisture useS
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Table 9. Yield a of preflood ahu (a
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Grain yield (t ha -1 )6Farmers’ l
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ReferencesIRRI (International Rice
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network (Sastry 1976). Temperature
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Temperature (°C) and solar radiati
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Table 1. Characterization of rainfa
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in eastern Uttar Pradesh under norm
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fluctuations/variations in rainfall
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the desirable rainfall period at 50
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The radiation values range from les
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not affect the growth and developme
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Agrohydrologic and drought riskanal
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Analytical procedureThe nature and
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late because of low rainfall at the
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Probability (%)10080604020Vegetativ
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15 August), which may happen twice
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texture), then once in two years (5
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Characterizing biotic stresses
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Characterizing biotic constraintsto
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included in these studies. Later st
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Average number of insects per sweep
Page 250 and 251: Table 2. Categorization of weed and
Page 252 and 253: Table 5. Properties of individual c
Page 254 and 255: ResultsRelations among pests and cr
Page 256 and 257: Start hereInterview farmers todocum
Page 258 and 259: Table 10. Information used to prior
Page 260 and 261: Interpreting the results of indepen
Page 262 and 263: level. Again, we augment our databa
Page 264 and 265: NotesAuthors’ address: Cambodia-I
Page 266 and 267: in soil nutritional status, especia
Page 268 and 269: flora. The range in elevation acros
Page 270 and 271: Table 1. Soil characteristics of th
Page 272 and 273: Table 3. Weed species recorded and
Page 274 and 275: Proportional abundance (log scale)%
Page 276 and 277: 1.0Echi_colCype_iriMoll_penLind_spp
Page 278 and 279: +3.0Echi_cruMars_creEcli_albLept_ch
Page 280 and 281: indicates the need to deploy broad-
Page 282 and 283: ReferencesBangun P, Pane H, Jatmiko
Page 284 and 285: Socioeconomic characterization
Page 286 and 287: The role of characterizationin ex a
Page 288 and 289: ApproachThe following steps were ta
Page 290 and 291: PriceDS 0S 1P 0P 1dS 0S 1acbD0 Q 0Q
Page 292 and 293: Table 1. Ex ante assessment of rese
Page 294 and 295: Table 2 continued.Ranked byResearch
Page 296 and 297: Table 3. Research resource allocati
Page 298 and 299: NotesAuthors’ address: National C
Page 302 and 303: Socioeconomic constraintsFarm sizeF
Page 304 and 305: found that a higher rural labor sup
Page 306 and 307: Table 3. Rice area under HYVs from
Page 308 and 309: Rice varieties in farmers’ fields
Page 310 and 311: Table 9. Constraints for low adopti
Page 312 and 313: vehicle for realizing the untapped
Page 314 and 315: Parthasarathy G, Prasad DS. 1978. R
Page 316 and 317: Appendix. Agroclimatic zones of Bih
Page 318 and 319: such that losses are reduced during
Page 320 and 321: P = 0.5 R [a 2 C r2+ 2 a (1 - a) g
Page 322 and 323: and Itgaon, however, the plot-level
Page 324 and 325: espectively, to farmers’ income.
Page 326 and 327: Factors determining the adoption of
Page 328 and 329: mining whether or not modern variet
Page 330 and 331: irrigation schemes in the study are
Page 332 and 333: Using gender analysis in characteri
Page 334 and 335: lytical tool used to identify or di
Page 336 and 337: However, household members have cer
Page 338 and 339: Table 1. Village characteristics of
Page 340 and 341: taking care of dairy cattle. On the
Page 342 and 343: The biophysical environmentThe perf
Page 344 and 345: Table 3. Seasonal calendar and gend
Page 346 and 347: Table 4. Crops grown during the kha
Page 348 and 349: Table 7. Labor input (person-days h
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Table 8. Labor input (person-days h
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Table 10. Cost and returns of rice
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Gender roles in animal husbandryWhe
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farm activities, 25% in nonfarm act
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for rice but also for cash crops su
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Table 15. Access to agricultural in
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Hossain M. 1995. Recent development
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Agricultural commercializationand l
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Conceptual frameworkPopulation pres
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tional average of 18% 1 , and most
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The Dzao live in medium-altitude ar
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Table 1. Selected districts and com
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Table 2. General characteristics of
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markets for their food needs. With
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ther “extensification” in the u
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the productivity of lowland rice ca
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Boserup E. 1981. Population and tec
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Economics of intensive rainfed lowl
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Area (ha)50,00040,000Irrigated30,00
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The economic characterization and i
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Table 1. Rice varieties planted (19
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Table 4. Yield and input use of maj
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TFP, output and input indices200160
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Lynam JK, Herdt RW. 1989. Sense and
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406 Garcia et al
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Increased rice production had alway
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Table 1. Total rice area, average y
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use of water by avoiding seedbed pr
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water often brought with it a varie
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Table 4. Distribution of farm house
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Soil types found in the villages we
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Table 10. Ownership of agricultural
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in a group) at the rate of $60 per
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Table 13. Pattern of loan use (% of
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Labor and employmentTable 16 presen
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Table 17. Incidence of child labor
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Cumulative proportion of income1.04
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Table 21. Cost and return analysis
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Table 22. Estimated rice yield and
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were often burned for disease contr
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landless population reaching 50-60%
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Integration of biophysical andsocio
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opinion regarding what socioeconomi
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1995-96 Rice production (t)TvRd6Rd1
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Farm-gate price of agricultural goo
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ming the distance of all line segme
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Description of the study areaWe com
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Table 1 continued.Variable Unit1994
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CambodiaFig. 4. Main transport rout
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Table 2. Accessibility indicators f
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ice and the model is applied to exp
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Table 3. Summary of estimates of la
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estimation of a system of multinomi
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The availability of low-saline irri
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Table 5. Simulation of effects of i
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NotesAuthors’ address: Social Sci
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that they synthesize fragmented agr
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Framework for exploratory and predi
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and quantify the spatial distributi
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Seventeen different agricultural pr
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self-sufficiency in rice production
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al warming since maintaining or cre
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eturns to purchased inputs due to u
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Francisco SR, Navarrete Jr. RL, Dim
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Wade L. 1998. Nutrient research on
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