Impact of Rainfall Variability on Food production under Rainfed Agriculture in Homa Bay County, Kenya

Ogenga, J. O.; Mugalavai, Edward M.; Nyandiko, Nicodemus O.

doi:10.29322/ijsrp.8.8.2018.p80110

Cited by 9 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Using or fertilizer also has a favorable 10.1 percent effect on wheat production. Similar findings were obtained by (Ogenga et al, 2018). As mentioned under discussion of descriptive statistics, the temperature variability of this area is very small, which is why its effect on the wheat yield of this region is negative but statistically negligible enough to draw any conclusions or devise any strategy.…”

Section: Table6 Zone Wise Impact Of Climate Variations On Wheat Yieldsupporting

confidence: 83%

Climate Variability and Wheat Crop Yield in Pakistan: Analyzing Food Security Prospects in Selected Agro Climatic Zones

Sultana¹

2020

PSSR

View full text Add to dashboard Cite

Section: Table6 Zone Wise Impact Of Climate Variations On Wheat Yieldsupporting

confidence: 83%

Climate Variability and Wheat Crop Yield in Pakistan: Analyzing Food Security Prospects in Selected Agro Climatic Zones

Sultana¹

2020

PSSR

View full text Add to dashboard Cite

“…This is because field Striga infestation levels have been found to strongly and positively correlate with soil Striga seed bank (Samejima et al 2016). Moreover, previous studies have also indicated that host crops may increase the amount of secreted strigolactone in response to moisture stress (Bahadur et al, 2019;Vurro et al, 2019) resulting in high Striga infestation levels evident at Kadel field (Ogenga et al, 2018).…”

Section: Variations In the Sorghum Genotypes' And Fields Levels Of Striga Infestationmentioning

confidence: 96%

“…The soils are classified as ferralic with a pH of 5.9 (Mbogo et al, 2016). Kadel is found at a longitude of 34°24°E, latitude N-0°11'27" S, and an altitude of 1400 m above sea level with an average annual rainfall of 1200 mm (Ogenga et al, 2018). The soils are vertisol with a pH of 7.3 and made of fine loose textured clay soils.…”

Section: Experimental Site Descriptionmentioning

confidence: 99%

Response of selected sorghum (sorghum bicolor (l.) moench) genotypes to striga hermonthica (del.) benth in western Kenya

Gudu¹,

Ochiel²,

Dida³

et al. 2021

J. Plant Breed. Crop Sci.

View full text Add to dashboard Cite

Sorghum is an important staple food crop in Kenya, but its yield is low due to many constraints which include diseases, drought, soil fertility, and pests, notably parasitic weed Striga hermonthica. Twenty elite sorghum genotypes and one resistant check were evaluated in three replications in a complete randomized design in Agar Gel (AG) experiment and randomized complete block design on selected Striga hotspot farms at Kadel and Nyahera in western Kenya. Significant differences (p<0.001) were realized both in the fields (plant height, dry shoot biomass yield, grain yield, field Striga count, and Striga damage ratings) and in the AG experiment with respect to maximum germination distance and numbers of induced germinated Striga seeds. Among the sorghum genotypes evaluated under field conditions, T53B, N57, N68, C26, IESV 92036-SH, T30B, and Uyoma 47 White genotypes had stable yields under Striga infestation in the two sites, whereas Nyadundo 1, Nyadundo 2, and Uyoma 8 were susceptible. In the AG experiment, E117B, T30B, Uyoma 8, Uyoma 42 STR, and T53B induced high numbers of germinated Striga seeds with maximum germination distances (MGD). In contrast, Uyoma 47 Brown, IESV 92038/2-SH, and IESV 92036-SH sorghum genotypes secreted low amounts of SLS suggesting resistance. This study has identified and selected four Striga tolerant (T53B, N68, N57, and T 30B) and resistant (C 26, Uyoma 47 Brown, IESV 92038/2-SH, and IESV 92036-SH) sorghum genotypes which can be utilized in further research programs or adopted to improve sorghum productivity in the highly Striga infested regions of western Kenya.

show abstract

“…Rangwe Sub-County, the condition necessitated the need to use the ICT tools in agricultural extension to ensure the smallholder farmers timely receive cassava information instead of the traditional method, where agricultural extension officers had to travel and physically serve many smallholder farmers demanding the information [10]. A few peasants who used the ICT tools and platforms in agricultural extension received agrarian information faster and easier, which translates to a significant cassava yield [11]. However, the ICT tools' adoption by the peasants is low.…”

Section: Inmentioning

confidence: 99%

Assessment of Information and Communication Technology Tools’ Usage in Agricultural Extension among Cassava Peasants in Rangwe Sub-County, Kenya

Dimo

Wambugu

Ndiema

2022

AJAEES

View full text Add to dashboard Cite

Aims: This study sought to determine selected demographic characteristics, the extent of Information and Communication Technology (ICT) tools’ usage, opportunities in ICT, challenges in the use, strategies to improve the use, and the correlation between the selected demographic factors and ICT tools’ usage among peasants who produce cassava in Rangwe Sub-County, Kenya. Study Design: A correlation research design was used in this study conducted at Rangwe Sub-County, Kenya from 8th December 2021 to 14th January 2022. Methodology: The study gathered data with the aid of pretested structured questionnaire from 106 Cassava Peasants (CPs) who used or not used ICT tools in agricultural extension. Results: The response rate achieved was 100%. The majority of the CPs were female (62%), middle-aged (36-50 years), attained primary education (52%), and earned the lowest average annual income (X ≤ KES160, 000). The majority of ICT tools users in extension were males, elite, higher-income earners, and youths. The largest percentage of ICT tools users mentioned, ICT tools availability as one of the opportunities in ICT, expensiveness as the main challenge in the use, ICT services subsidies as one of the improvement strategies. Spearman’s correlation analysis showed that a correlation between the selected demographic factors and ICT tools’ usage was statistically significant at a 1% level of significance (P=.000). Conclusion: Adoption of ICT tools in agricultural extension services is directly proportional to income, gender equality, and education, while it is inversely proportional to age. The provision of supporting policies for the selected demographic factors, availability of training centers, and subsidized credit interest rate would increase ICT tools usage in extension.

show abstract

Impact of Rainfall Variability on Food production under Rainfed Agriculture in Homa Bay County, Kenya

Cited by 9 publications

References 0 publications

Climate Variability and Wheat Crop Yield in Pakistan: Analyzing Food Security Prospects in Selected Agro Climatic Zones

Climate Variability and Wheat Crop Yield in Pakistan: Analyzing Food Security Prospects in Selected Agro Climatic Zones

Response of selected sorghum (sorghum bicolor (l.) moench) genotypes to striga hermonthica (del.) benth in western Kenya

Assessment of Information and Communication Technology Tools’ Usage in Agricultural Extension among Cassava Peasants in Rangwe Sub-County, Kenya

Contact Info

Product

Resources

About