Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka
Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is hetero...
Ausführliche Beschreibung
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| Autor*in: |
Sankalpa, J. K. S. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Malaysian Rubber Board 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of rubber research - [Singapore] : Springer Singapore, 2019, 24(2021), 5 vom: 02. Nov., Seite 719-734 |
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| Übergeordnetes Werk: |
volume:24 ; year:2021 ; number:5 ; day:02 ; month:11 ; pages:719-734 |
| Links: |
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| DOI / URN: |
10.1007/s42464-021-00127-2 |
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| Katalog-ID: |
SPR046217584 |
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| 520 | |a Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. | ||
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| 700 | 1 | |a Wimalaratana, W. |4 aut | |
| 700 | 1 | |a Ishani, P. G. N. |4 aut | |
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10.1007/s42464-021-00127-2 doi (DE-627)SPR046217584 (SPR)s42464-021-00127-2-e DE-627 ger DE-627 rakwb eng Sankalpa, J. K. S. verfasserin (orcid)0000-0002-4412-692X aut Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Malaysian Rubber Board 2021 Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 Wijesuriya, W. aut Wimalaratana, W. aut Ishani, P. G. N. aut Enthalten in Journal of rubber research [Singapore] : Springer Singapore, 2019 24(2021), 5 vom: 02. Nov., Seite 719-734 (DE-627)1049383931 (DE-600)2963165-8 2524-3993 nnns volume:24 year:2021 number:5 day:02 month:11 pages:719-734 https://dx.doi.org/10.1007/s42464-021-00127-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 5 02 11 719-734 |
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10.1007/s42464-021-00127-2 doi (DE-627)SPR046217584 (SPR)s42464-021-00127-2-e DE-627 ger DE-627 rakwb eng Sankalpa, J. K. S. verfasserin (orcid)0000-0002-4412-692X aut Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Malaysian Rubber Board 2021 Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 Wijesuriya, W. aut Wimalaratana, W. aut Ishani, P. G. N. aut Enthalten in Journal of rubber research [Singapore] : Springer Singapore, 2019 24(2021), 5 vom: 02. Nov., Seite 719-734 (DE-627)1049383931 (DE-600)2963165-8 2524-3993 nnns volume:24 year:2021 number:5 day:02 month:11 pages:719-734 https://dx.doi.org/10.1007/s42464-021-00127-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 5 02 11 719-734 |
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10.1007/s42464-021-00127-2 doi (DE-627)SPR046217584 (SPR)s42464-021-00127-2-e DE-627 ger DE-627 rakwb eng Sankalpa, J. K. S. verfasserin (orcid)0000-0002-4412-692X aut Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Malaysian Rubber Board 2021 Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 Wijesuriya, W. aut Wimalaratana, W. aut Ishani, P. G. N. aut Enthalten in Journal of rubber research [Singapore] : Springer Singapore, 2019 24(2021), 5 vom: 02. Nov., Seite 719-734 (DE-627)1049383931 (DE-600)2963165-8 2524-3993 nnns volume:24 year:2021 number:5 day:02 month:11 pages:719-734 https://dx.doi.org/10.1007/s42464-021-00127-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 5 02 11 719-734 |
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10.1007/s42464-021-00127-2 doi (DE-627)SPR046217584 (SPR)s42464-021-00127-2-e DE-627 ger DE-627 rakwb eng Sankalpa, J. K. S. verfasserin (orcid)0000-0002-4412-692X aut Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Malaysian Rubber Board 2021 Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 Wijesuriya, W. aut Wimalaratana, W. aut Ishani, P. G. N. aut Enthalten in Journal of rubber research [Singapore] : Springer Singapore, 2019 24(2021), 5 vom: 02. Nov., Seite 719-734 (DE-627)1049383931 (DE-600)2963165-8 2524-3993 nnns volume:24 year:2021 number:5 day:02 month:11 pages:719-734 https://dx.doi.org/10.1007/s42464-021-00127-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 5 02 11 719-734 |
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10.1007/s42464-021-00127-2 doi (DE-627)SPR046217584 (SPR)s42464-021-00127-2-e DE-627 ger DE-627 rakwb eng Sankalpa, J. K. S. verfasserin (orcid)0000-0002-4412-692X aut Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Malaysian Rubber Board 2021 Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 Wijesuriya, W. aut Wimalaratana, W. aut Ishani, P. G. N. aut Enthalten in Journal of rubber research [Singapore] : Springer Singapore, 2019 24(2021), 5 vom: 02. Nov., Seite 719-734 (DE-627)1049383931 (DE-600)2963165-8 2524-3993 nnns volume:24 year:2021 number:5 day:02 month:11 pages:719-734 https://dx.doi.org/10.1007/s42464-021-00127-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 24 2021 5 02 11 719-734 |
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S.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-4412-692X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Malaysian Rubber Board 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. 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Sankalpa, J. K. S. |
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Sankalpa, J. K. S. misc Rubber-based farming misc Multivariate statistical technique misc Non-farm income misc Household misc Farm typology Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka |
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Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka Rubber-based farming (dpeaa)DE-He213 Multivariate statistical technique (dpeaa)DE-He213 Non-farm income (dpeaa)DE-He213 Household (dpeaa)DE-He213 Farm typology (dpeaa)DE-He213 |
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utilizing a farm typology for the development of rubber-based farming: a case from moneragala district, sri lanka |
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Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka |
| abstract |
Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. © The Malaysian Rubber Board 2021 |
| abstractGer |
Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. © The Malaysian Rubber Board 2021 |
| abstract_unstemmed |
Abstract Rubber-based farming has been introduced mainly in the non-yielding phase of rubber to generate farm income. However, the effectiveness of rubber-based farming is not at an acceptable level in smallholder rubber lands due to the poor adoption of technologies. The farming community is heterogeneous and the adoption of technologies is determined by the socioeconomic setting of farmers. This study aims to categorise the adoption of food crops or dairy cattle farming in immature rubber lands using the socioeconomic characteristics of farm households and to identify constraints for the adoption of rubber-based farming. Farm households with different socioeconomic characteristics were categorised into groups based on their homogeneity using a multivariate statistical technique. The results indicated the heterogeneous nature of rubber-based farming and revealed six predominant rubber-based farm types. Six groups were disassociated from each other due to significant differences among the variables, including credit access, market access, non-farm income, farm extent, investment in rubber intercropping, use of machines in cultivation, household size, and age of rubber trees. Six groups were termed as medium resource endowed moderate financing farmers, intensive urbanized farmers, low return on intercropping aged farmers, diversifiers into non-rubber farm income, extensive farmers, and high resource endowed farmers with the small size of households. While the mixed-method approach demonstrating the categorisation of rubber-based farming, it facilitates identifying enabling factors and barriers in technology adoption and further development of rubber-based farming. The outcome of this study assists in evidence-based technology transfer in rubber expansion in non-traditional rubber growing areas. The mixed data analysis approach used in this study can be useful in other similar farm typology studies. © The Malaysian Rubber Board 2021 |
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5 |
| title_short |
Utilizing a farm typology for the development of rubber-based farming: a case from Moneragala district, Sri Lanka |
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https://dx.doi.org/10.1007/s42464-021-00127-2 |
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| author2 |
Wijesuriya, W. Wimalaratana, W. Ishani, P. G. N. |
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Wijesuriya, W. Wimalaratana, W. Ishani, P. G. N. |
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10.1007/s42464-021-00127-2 |
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2024-07-03T21:07:49.126Z |
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| score |
7.398713 |