| 000 | 02998nam a22005297a 4500 | ||
|---|---|---|---|
| 001 | G74281 | ||
| 003 | MX-TxCIM | ||
| 005 | 20211006084813.0 | ||
| 008 | 121211s ||||f| 0 p|p||0|| | | ||
| 020 | _a92-9146-065-6 | ||
| 040 | _aMX-TxCIM | ||
| 072 | 0 | _aE14 | |
| 072 | 0 | _aF04 | |
| 090 | _aCIS-2927 | ||
| 100 | 1 |
_aSalasya, B.D.S. _uMaize Production Technology for the Future: Challenges and Opportunities. Proceedings of the Eastern and Southern Africa Regional Maize Conference, 6; Addis Ababa (Ethiopia); 21-25 Sep 1998 |
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| 110 | 2 | _aCentro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT), Mexico DF (Mexico) | |
| 245 | 0 | 0 | _aAn assessment of adoption of seed and fertilizer packages and the role of credit in smallholder maize production in Western Kenya |
| 260 |
_aAddis Ababa (Ethiopia) _bCIMMYT*EARO : _c1999 |
||
| 300 | _ap. 357-360 | ||
| 340 | _aPrinted | ||
| 520 | _aData from informal and formal surveys in Kakamega and Vihiga districts were analyzed to describe maize farmers' circumstances and practices, identify socioeconomic and technical factors affecting the adoption of improved maize seed and fertilizer packages and the role of credit. The methodology used to collect and analyze the data is described. About 51% of the farmers grew improved maize varieties, mainly because they were high yielding. The major constraint to using improved varieties was the high price of maize seed. About 46% and 23% of adopters and non-adopters, respectively, used inorganic fertilizer, but the amount used per unit area was very low. Fertilizer use was constrained by its high price. Less than 10% of the sample farmers had used credit due mainly to lack of the required land collateral. Results of the logistic regression model showed that the use of hired labor, number of cattle owned, extension, Division and secondary education had statistically significant effect on the probability of adopting improved maize varieties. Use of hired labor, division, number of cattle owned, membership of organization and use of organic manure had statistically significant impact on the probability to adopt fertilizer. | ||
| 536 | _aGlobal Maize Program | ||
| 546 | _aEnglish | ||
| 591 | _a0103|AL Maize Program|AGRIS 0102|AJ|3|SEP archives 2 | ||
| 594 | _aINT1320 | ||
| 595 | _aCSC | ||
| 650 | 1 | 0 | _aCredit |
| 650 | 1 | 7 |
_aCrop management _gAGROVOC _2 _91061 |
| 650 | 1 | 7 |
_aFertilizers _gAGROVOC _2 _91111 |
| 650 | 1 | 7 |
_aInnovation adoption _gAGROVOC _2 _91160 |
| 650 | 1 | 0 | _aInput output analysis |
| 650 | 1 | 0 |
_aKenya _91167 |
| 650 | 1 | 7 |
_aMaize _gAGROVOC _2 _91173 |
| 650 | 1 | 0 |
_aPlant production _91212 |
| 650 | 1 | 0 | _aProduction factors |
| 650 | 1 | 0 | _aSeeds |
| 650 | 1 | 0 | _aSemiarid zones |
| 650 | 1 | 7 |
_aSmall farms _gAGROVOC _2 _91260 |
| 650 | 1 | 0 |
_91801 _aSowing _gAGROVOC |
| 650 | 1 | 0 | _aSowing rates |
| 653 | 0 | _aCIMMYT | |
| 650 | 1 | 0 |
_91314 _aZea mays _gAGROVOC |
| 700 | 1 | _aCIMMYT|EARO | |
| 700 | 1 |
_aMwangi, W.M., _ecoaut. _9616 |
|
| 700 | 1 |
_aVerkuijl, H., _ecoaut. |
|
| 942 | _cPRO | ||
| 999 |
_c9989 _d9989 |
||