The impact of smallholder farmers’ participation in avocado export markets on the labor market, farm yields, sales prices, and incomes in Kenya

Amare, Mulubrhan; Mariara, Jane; Oostendorp, R.A.B.; Pradhan, Menno

doi:10.1016/j.landusepol.2019.104168

Cited by 56 publications

(46 citation statements)

References 30 publications

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“…The study was carried out in Muranga county (0°43′ 0.01″ N, 37°08′60.00″ E) in the Central Region of Kenya, one of the major avocado producing areas [ 39 ]. The altitude ranges from 1071 m to 3353 m above sea level (asl) along the slopes of Aberdare forest in the west of the county ( Figure 1 ).…”

Section: Methodsmentioning

confidence: 99%

Landscape Vegetation Productivity Influences Population Dynamics of Key Pests in Small Avocado Farms in Kenya

Toukem

Yusuf

Dubois

et al. 2020

Insects

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Avocado (Persea americana Mill.) production contributes to the economic growth of East Africa. However, poor fruit quality caused by infestations of tephritid fruit flies (Tephritidae) and the false codling moth, Thaumatotibia leucotreta (Meyrick), hampers access to lucrative export markets. Remote sensing and spatial analysis are increasingly applied to crop pest studies to develop sustainable and cost-effective control strategies. In this study, we assessed pest abundance in Muranga, Kenya, across three vegetation productivity classes, viz., low, medium and high, which were estimated using the normalised difference vegetation index at a landscape scale. Population densities of the oriental fruit fly, Bactrocera dorsalis (Hendel) and T. leucotreta in avocado farms were estimated through specific baited traps and fruit rearing. The population density of T. leucotreta varied across the vegetation productivity classes throughout the study period, although not significantly. Meanwhile, B. dorsalis showed a clear trend of decrease over time and was significantly lower in high vegetation productivity class compared to low and medium classes. Ceratitis cosyra (Walker) was the most abundant pest reared from fruit with few associated parasitoids, Pachycrepoideus vindemmiae (Rondani) and Toxeumorpha nigricola (Ferriere).

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Section: Methodsmentioning

confidence: 99%

Landscape Vegetation Productivity Influences Population Dynamics of Key Pests in Small Avocado Farms in Kenya

Toukem

Yusuf

Dubois

et al. 2020

Insects

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“…Monocropping is predominantly practiced for commercial purposes and mixed cropping mostly for subsistence consumption. However, some crops such as avocado, grown in mixed cropping patterns by smallholder farmers in Murang'a, are also used for commercial purposes [48]. Murang'a County is a major avocado producing area in Kenya and is a horticultural crop whose export value has increased during the past decade [49].…”

Section: Study Areamentioning

confidence: 99%

Cropping Pattern Mapping in an Agro-Natural Heterogeneous Landscape Using Sentinel-2 and Sentinel-1 Satellite Datasets

et al. 2021

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The quantity of land covered by various crops in a specific time span, referred to as a cropping pattern, dictates the level of agricultural production. However, retrieval of this information at a landscape scale can be challenging, especially when high spatial resolution imagery is not available. This study hypothesized that utilizing the unique advantages of multi-date and medium spatial resolution freely available Sentinel-2 (S2) reflectance bands (S2 bands), their vegetation indices (VIs) and vegetation phenology (VP) derivatives, and Sentinel-1 (S1) backscatter data would improve cropping pattern mapping in heterogeneous landscapes using robust machine learning algorithms, i.e., the guided regularized random forest (GRRF) for variable selection and the random forest (RF) for classification. This study’s objective was to map cropping patterns within three sub-counties in Murang’a County, a typical African smallholder heterogeneous farming area, in Kenya. Specifically, the performance of eight classification scenarios for mapping cropping patterns was compared, namely: (i) only S2 bands; (ii) S2 bands and VIs; (iii) S2 bands and VP; (iv) S2 bands and S1; (v) S2 bands, VIs, and S1; (vi) S2 bands, VP, and S1; (vii) S2 bands, VIs, and VP; and (viii) S2 bands, VIs, VP, and S1. Reference data of the dominant cropping patterns and non-croplands were collected. The GRRF algorithm was used to select the optimum variables in each scenario, and the RF was used to perform the classification for each scenario. The highest overall accuracy was 94.33% with Kappa of 0.93, attained using the GRRF-selected variables of scenario (v) S2, VIs, and S1. Furthermore, McNemar’s test of significance did not show significant differences (p ≤ 0.05) among the tested scenarios. This study demonstrated the strength of GRRF in selecting the most important variables and the synergetic advantage of S2 and S1 derivatives to accurately map cropping patterns in small-scale farming-dominated landscapes. Consequently, the cropping pattern mapping approach can be used in other sites of relatively similar agro-ecological conditions. Additionally, these results can be used to understand the sustainability of food systems and to model the abundance and spread of crop insect pests, diseases, and pollinators.

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“…In addition, the production for export was declining before COVID-19 export cut-offs. This challenge arises from low quality, incapacitated institutions of small-scale farmers, high regulatory standards in the export market, insufficient capacity, and co-ordination of fruit exports (Amare et al 2019). Muthoka et al (2008) found that a macadamia tree can yield 10-20 Kg per year in small-scale farms, while in medium and large farms, where acceptable agronomic practices have been adopted, it can yield 80 Kg per year.…”

Section: Lifestyle Changesmentioning

confidence: 99%

COVID-19 containment measures of the Government of Kenya: Impact on food security and farmers’ socio-economic life

Kinuthia

Susanti

2021

MKP

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Agriculture is the backbone of Kenya’s economy. The majority of the population earn their living through agricultural activities, large-scale and small-scale farming. This study seeks to reveal how the government’s COVID-19 containment measures have affected the agricultural sector and their impact on farmers’ lifestyle changes. This study employed qualitative research methods, with primary and secondary data sources, and conducted in-depth interviews with 12 farmers and agricultural producers of Gatanga Sub-county in Murang’a County, Kenya. This study shows that the farmers experienced economic shocks owing to the fluctuated farm gate prices and projected resource scarcity. In contrast, their lifestyle changed due to income decrease and adjustment of commodity priorities and socio-demographic factors. The severity of COVID-19 impact on agriculture in the Gatanga Sub-County has been doubled by crop destruction, planting delays, and heavy rains that influence scarcity of food commodities. The study recommends other research to evaluate alternative solutions to supply the county’s food outputs other than those already in co-operatives, like tea, coffee, milk, and avocados. Moreover, perhaps the question for other future researchers should now be directed toward the vulnerable families’ daily consumptions to fulfill their food needs.

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The impact of smallholder farmers’ participation in avocado export markets on the labor market, farm yields, sales prices, and incomes in Kenya

Cited by 56 publications

References 30 publications

Landscape Vegetation Productivity Influences Population Dynamics of Key Pests in Small Avocado Farms in Kenya

Landscape Vegetation Productivity Influences Population Dynamics of Key Pests in Small Avocado Farms in Kenya

Cropping Pattern Mapping in an Agro-Natural Heterogeneous Landscape Using Sentinel-2 and Sentinel-1 Satellite Datasets

COVID-19 containment measures of the Government of Kenya: Impact on food security and farmers’ socio-economic life

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