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Journal articles on the topic 'Rice – Kenya'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Pinel-Galzi, A., D. Fargette, and R. Hull. "First Report of Rice yellow mottle virus in Rice in Uganda." Plant Disease 90, no. 5 (May 2006): 683. http://dx.doi.org/10.1094/pd-90-0683b.

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Rice yellow mottle virus (RYMV) of the genus Sobemovirus is a major biotic constraint to rice production in Africa. First reported in Kenya in 1966, RYMV was later found in most countries in Africa where rice (Oryza sativa) is grown (2). During July 2000, plants with leaf yellowing and mottling symptoms were observed in Uganda in a subsistence rice field northeast of Lake Victoria, close to the Nile River. RYMV was detected by using enzyme-linked immunosorbent assay with polyclonal RYMV antisera (1) in the four samples collected. Discriminant monoclonal antibodies revealed that the samples contained RYMV serotype 4, a serotype found in eastern Africa (Madagascar, Kenya, and Tanzania) (2). The 720-nt long coat protein gene of two isolates was amplified by reverse transcriptase-polymerase chain reaction and sequenced (1). The two Ugandan isolates had 99% nt sequence identity (EMBL Accession Nos. AM114523 and AM114524). They belonged to a monophyletic group (97% nt identity) containing isolates from eastern Kenya and northern Tanzania (close to the Lake Victoria). These form a sister group (93% identity) of isolates from Lake Malawi Region in western Tanzania and are more distantly related (88% identity) to the basal strains from eastern Tanzania (2). Isolation of the Lake Victoria Region from the rest of the Tanzania by distance, physical barriers, and patchy rice cultivation explains the specificity of the strain. Year-round growth of wild and cultivated rice around the lake ensures host continuity in time and space that facilitates spread that accounts for the homogeneity of the isolates of this area. Knowledge of the presence of RYMV in Uganda is important since rice cultivation is intensified in this country and is planned in neighboring southern Sudan. References: (1) A. Pinel et al. Arch. Virol. 145:1621, 2000. (2) O. Traoré et al. Mol. Ecol. 14:2097, 2005.

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2

Munyua, Joseph Mwangi. "Mwea Irrigation Scheme in Kenya." Jumuga Journal of Education, Oral Studies, and Human Sciences (JJEOSHS) 3, no. 1 (September 27, 2020): 1–11. http://dx.doi.org/10.35544/jjeoshs.v3i1.28.

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History embraces the story of the Supreme Being, humanity, and the Universe. Human history is a silent realm that encompasses creation, fall, concupiscence, and the need for the prophetic voice towards human redemption. This article seeks to examine the Mwea Irrigation Scheme and explore the oppressive situation that was experienced by its rice farmers; and eventually assess the need for prophetic voice as the critical pillar and/or the key tool that ought to have stood as the weapon of addressing the vice. To this end, this article will methodologically draw from the history of Mwea Irrigation Scheme, unfold the origin and growth, the oppression of the rice farmers, and the need for the prophetic voice as the aforesaid tool of empowerment, as it seeks to build on a Kenyan version of liberation and/or political theology. Strictly therefore, the problem that this article wrestles with is the unearthing of the above-mentioned oppression of the Mwea rice farmers and the need for redemptive prophetic voice that is geared towards the ultimate goal, the liberation of the socio-economically oppressed rice farmers. Arguably, working out a liberation theology that addresses the Mwea case compares well with the Asian theologies such as the Burakumin theology for the marginalised and minority peoples of Asia whose reflection from the prophetic role of religion gives solace to their plight. It also compares with the Waterbuffalo theology, as propounded by Kosuko Koyama. In Waterbuffalo theology, a Japanese theologian, Kosuko Koyama, attempts to translate the Christian faith into the Asian tradition in Thailand, a phenomenon where farmers spend substantial amount of time in their respective rice fields without any substantial and/or decent returns. Apart from a theo-historical design, the methodology in this presentation includes: interview schedules, literature review of relevant and existing literature, and the reliance on the modus operandi that is well captured by the biblical Prophet Amos.

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3

Nyang’au, W. O., B. M. Mati, K. Kalamwa, R. K. Wanjogu, and L. K. Kiplagat. "Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model." International Journal of Agronomy 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/849496.

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Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI) in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from each irrigation scheme and their farms were used as research fields. Daily maximum and minimum temperatures and precipitation were collected from the weather station in each of the irrigation schemes while daily solar radiation was generated using weatherman in the DSSAT shell. The study revealed that increase in both maximum and minimum temperatures affects Basmati 370 and IR 2793-80-1 grain yield under SRI. Increase in atmospheric CO2concentration led to an increase in grain yield for both Basmati and IR 2793-80-1 under SRI and increase in solar radiation also had an increasing impact on both Basmati 370 and IR 2793-80-1 grain yield. The results of the study therefore show that weather conditions in Kenya affect rice yield under SRI and should be taken into consideration to improve food security.

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4

Ebere, Rebecca, Jasper Imungi, and Violet Kimani. "Glycemic index values of traditional Kenyan foods: the missing link in the effectiveness of dietary approach in the prevention and management of diabetes mellitus in Kenya." African Health Sciences 21, no. 2 (August 2, 2021): 710–18. http://dx.doi.org/10.4314/ahs.v21i2.29.

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Background: Glycemic index (GI) measures postprandial blood sugar after consumption of carbohydrate-rich foodstuff. Kenya is yet to fully embrace this concept in prevention and management of diabetes mellitus. Objective: To review and tabulate GIs of locally consumed foods in order to improve dietary management of diabetes mellitus. Methodology: A literature search was conducted using Google scholar and PubMed databases which identified 7 articles on glycemic index values of Kenyan foods published between 2002 and 2020. Two articles failed to meet the inclusion criteria and five proceeded for review. Key search words used included GI, glycemic load and glycemic response combined with Kenya. The data was reported depending on whether the testing involved healthy individuals or patients suffering from diabetes mellitus. Results: Nine individual foods and 7 mixed meals were identified. Low GI foods included beans and whole maize ugali consumed alongside cowpea leaves. High GI foods included whole maize ugali eaten with beef, boiled rice, boiled cassava and cassava-sorghum ugali eaten with silver fish. Conclusion: Proper meal mixing is important in diabetes management. Cowpea leaves and beans possess GI lowering po- tential. This information can be used to improve guidance on food choices for diabetes patients. Keywords: Glycemic index; glycemic load and glycemic response; Kenya.

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5

Watanabe, Mamoru, Yutaka Sumita, Issaku Azechi, Kengo Ito, and Keigo Noda. "Production Costs and Benefits of Japonica Rice in Mwea, Kenya." Agriculture 11, no. 7 (July 5, 2021): 629. http://dx.doi.org/10.3390/agriculture11070629.

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From the perspective of national food security, strengthening domestic rice production is an urgent issue for Kenya. For this purpose, it is helpful to consider varieties that generate novel and competitive values different from those of conventional varieties. Recently, domestic japonica rice, which is now being distributed, has become an attractive variety with a high market price and its production is expected to increase. Although it is competitive and promising as a crop for small-scale farmers, the production stage costs and benefits are not clear. Thus, a study was conducted to perform a cost–benefit analysis of japonica rice in comparison to conventional rice at the production stage and evaluate strategies for strengthening the domestic production of rice. We conducted an experimental cultivation of japonica rice in the Mwea region, Kenya, where japonica rice is produced. As a result, although production costs for japonica rice are higher than costs for conventional varieties (24.46 KSh/kg versus 22.63 KSh/kg), when a high-yielding variety is grown (6.44 tons/ha for japonica rice compared to 6.07 tons/ha for conventional rice), a larger net profit can be obtained (65.54 KSh/kg versus 32.37 KSh/kg). We believe that initiatives to improve difficulties at the production stage would make the production of both japonica rice and conventional rice more economically viable and facilitate strengthening of the overall domestic rice production.

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6

Muema, Faith, Patrick Home, and James Raude. "Application of Benchmarking and Principal Component Analysis in Measuring Performance of Public Irrigation Schemes in Kenya." Agriculture 8, no. 10 (October 12, 2018): 162. http://dx.doi.org/10.3390/agriculture8100162.

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The inefficient water use, and variable and low productivity in Kenyan public irrigation schemes is a major concern. It is, therefore, necessary to periodically monitor and evaluate the performance of public irrigation schemes. This prompted evaluation of performance of three rice growing irrigation schemes in western Kenya using benchmarking and principal component analysis. The aim of the study was to quantify and rank the performance of selected irrigation schemes. The performance of the irrigation schemes was evaluated for the period from 2012 to 2016 using eleven performance indicators under agricultural productivity, water supply and financial performance categories. The performance indicators were weighted using principal component analysis and combined to form a single performance score using linear aggregation method. The average performance in the Ahero, West Kano and Bunyala irrigation schemes was 48%, 49% and 56%, respectively. Based on performance score, the Bunyala irrigation scheme is the highest performing rice irrigation scheme in western Kenya. The three irrigation schemes have an average performance. Operation and management measures to improve the current performance of the irrigation schemes are needed.

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Mutiga, Samuel K., J. Musembi Mutuku, Vincent Koskei, James Kamau Gitau, Fredrick Ng’ang’a, Joyce Musyoka, George N. Chemining’wa, and Rosemary Murori. "Multiple Mycotoxins in Kenyan Rice." Toxins 13, no. 3 (March 11, 2021): 203. http://dx.doi.org/10.3390/toxins13030203.

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Multiple mycotoxins were tested in milled rice samples (n = 200) from traders at different milling points within the Mwea Irrigation Scheme in Kenya. Traders provided the names of the cultivar, village where paddy was cultivated, sampling locality, miller, and month of paddy harvest between 2018 and 2019. Aflatoxin, citrinin, fumonisin, ochratoxin A, diacetoxyscirpenol, T2, HT2, and sterigmatocystin were analyzed using ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). Deoxynivalenol was tested using enzyme-linked immunosorbent assay (ELISA). Mycotoxins occurred in ranges and frequencies in the following order: sterigmatocystin (0–7 ppb; 74.5%), aflatoxin (0–993 ppb; 55.5%), citrinin (0–9 ppb; 55.5%), ochratoxin A (0–110 ppb; 30%), fumonisin (0–76 ppb; 26%), diacetoxyscirpenol (0–24 ppb; 20.5%), and combined HT2 + T2 (0–62 ppb; 14.5%), and deoxynivalenol was detected in only one sample at 510 ppb. Overall, low amounts of toxins were observed in rice with a low frequency of samples above the regulatory limits for aflatoxin, 13.5%; ochratoxin A, 6%; and HT2 + T2, 0.5%. The maximum co-contamination was for 3.5% samples with six toxins in different combinations. The rice cultivar, paddy environment, time of harvest, and millers influenced the occurrence of different mycotoxins. There is a need to establish integrated approaches for the mitigation of mycotoxin accumulation in the Kenyan rice.

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8

Lewis, J. E., and I. J. Ndolo. "Estimating moisture availability for rice cultivation in Mwea, Kenya." Agricultural and Forest Meteorology 41, no. 1-2 (October 1987): 87–95. http://dx.doi.org/10.1016/0168-1923(87)90072-4.

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9

Njogu, Paul, Robert Kinyua, Purity Muthoni, and Yusuyuki Nemoto. "Thermal Gasification of Rice Husks from Rice Growing Areas in Mwea, Embu County, Kenya." Smart Grid and Renewable Energy 06, no. 05 (2015): 113–19. http://dx.doi.org/10.4236/sgre.2015.65010.

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10

Evans, A. Atera, N. Onyancha Florence, and B. O. Majiwa Eucabeth. "Production and marketing of rice in Kenya: Challenges and opportunities." Journal of Development and Agricultural Economics 10, no. 3 (March 31, 2018): 64–70. http://dx.doi.org/10.5897/jdae2017.0881.

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11

Fukuta, Yoshimichi, Mary Jeanie Telebanco-Yanoria, Nagao Hayashi, Seiji Yanagihara, Catherine Wanjiku Machungo, and Daigo Makihara. "Pathogenicities of Rice Blast (Pyricularia oryzae Cavara) Isolates From Kenya." Plant Disease 103, no. 12 (December 2019): 3181–88. http://dx.doi.org/10.1094/pdis-04-19-0870-re.

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A total of 99 isolates of rice blast (Pyricularia oryzae Cavara) were collected from 2010 to 2015 from four regions in Kenya: Kirinyaga County and Embu County, Kisumu County, Tana River County, and Mombasa County. The pathogenicities of these isolates were clarified based on the reaction patterns of Lijiangxintuanheigu and differential varieties (DVs) targeting 23 resistance genes. The frequency of virulent isolates was high for DVs for Pib, Pia, Pii, Pi3, Pi5(t), Pik-s, Pik-m, Pi1, Pik-h, Pik, Pik-p, Pi7(t), Pi19(t), and Pi20(t); low for DVs for Pish, Pi9(t), Piz-5, and Piz-t; and intermediate for the remaining DVs for Pit, Piz, Pita-2, Pita, and Pi12(t). These blast isolates were classified into three cluster groups: Ia, Ib, and II. The frequencies of virulent isolates to DVs for Pit, Pii, Pik-m, Pi1, Pik-h, Pik, Pik-p, Pi7(t), Piz, and Pi12(t) differed markedly between clusters I and II, and those of DVs for Pib, Pit, Pia, Pi3, Pita-2, Pita, and Pi20(t) differed between Ia and Ib. The frequencies of cluster groups in the four geographical regions were different. A total of 62 races were found, with 19 blast isolates categorized into one race (U63-i7-k177-z00-ta003), whereas the other races included only some isolates in each.

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Muturi, Ephantus J., Charles Mbogo, John Githure, Simon Muriu, Josephat Shililu, Robert J. Novak, Joseph Mwangangi, and Benjamin G. Jacob. "Effect of Rice Cultivation on Malaria Transmission in Central Kenya." American Journal of Tropical Medicine and Hygiene 78, no. 2 (February 1, 2008): 270–75. http://dx.doi.org/10.4269/ajtmh.2008.78.270.

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13

Rahab, Magoti, Mayumi Kikuta, George Chemining’wa, Josiah Kinama, John Kimani, Hiroaki Samejima, Patrick Gicheru, and Daigo Makihara. "Growth of Rice Varieties in Different Kenyan Soil Types Under Water-Deficit Conditions." Journal of Agricultural Science 11, no. 6 (May 15, 2019): 1. http://dx.doi.org/10.5539/jas.v11n6p1.

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The growth of 20 rice varieties, including both lowland and upland varieties, was evaluated in Kenya under well-watered and water-deficit conditions in four different soil types (black cotton, red clay, volcanic ash, and sandy clay) to compare the adaptability of these varieties to the two water regimes. Under water-deficit condition, after terminating irrigation, the reduction in soil water potential differed markedly according to soil type. The rice varieties tested were classified into four groups, which were largely consistent with differences in rice variety ecotype. We confirmed that lowland varieties such as Basmati 370 should not be considered as a candidate for cultivation under rain-fed upland conditions in Kenya. Furthermore, the results revealed that even potentially high-yielding varieties may not attain their yield potential if the cultivation environment is unsuitable. Although we found that five upland varieties (Dular, IRAT109, NERICA 1, NERICA 4, and Yumenohatamochi) presented relatively higher grain yield under water-deficit conditions in all soil types, individual variety’s grain yield depended on the soil type. Their higher yield is attributable to certain root traits and their yield variations to an interactive effect between root development and soil type. Our results indicated that the varieties Dular, IRAT109, NERICA 1, NERICA 4, and Yumenohatamochi are suitable for cultivation under rain-fed upland conditions across the major rice-growing areas in Kenya and that soil type should be considered when selecting varieties for an area’s maximum productivity.

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Njoroge, Francis Karanja. "ROLE OF STAKEHOLDER PARTICIPATION IN GOVERNANCE OF RICE PRODUCTION IN KIRINYAGA COUNTY, KENYA." Human Resource and Leadership Journal 2, no. 2 (May 26, 2017): 108. http://dx.doi.org/10.47941/hrlj.165.

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Purpose: The purpose of the study was to examine the participation of key stakeholders in the governance of rice production in Mwea Irrigation Scheme (MIS) in Kirinyaga County in Kenya.Research Methodology: Data were also collected through interview of farmers and employees of National Irrigation Board and MIAD using a structured questionnaire. The questionnaire was tested using the Cronbach’s Alpha Index and showed a high (+0.8) internal consistency and reliability. The study used multi-stage cluster sampling technique to select one zone from the five zones in MIS and randomly selected a sample of 50 farmers from the selected zone. The employees of National Irrigation Board and MIAD were clustered into management and field/technical staff and a purposive sample of 12 and 8, respectively, was drawn from each cluster. A sample of 60 respondents were interviewed. A time series model was used to generate a trend line for rice production. A regression correlation model, generated using SPSS Version 23, was used to analyze the relationship between variables. Findings: The findings showed that farmer participation in governance has a positive and significant relationship to rice production. Specifically, farmers’ participation in governance has a positive linearly significant influence on rice production. Further, the study found that the governance role of NIB has a positive and significantly influence on rice production. Finally, the role of MIAD was found to be positively and significantly related to rice production. Specifically, the role of MIAD was found to have a positive linearly significant influence on rice production. The three key stakeholders considered explained a significant variation of 58 per cent in rice production, with NIB role explaining more followed by farmer participation and then MIAD. Recommendation: This study has shown that farmers’ participation in governance of rice production has a positive and significant relationship with rice production. It is therefore recommended that their involvement in governance activities be structured so that their participation directly and indirectly through committees or their cooperative is deliberative and meaningful. This means that they participate in discussions, debates and presentations and in making decisions on substantive policy, and operational issues.

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Bii, Lourine Chebet, Kahiu Ngugi, John M. Kimani, and George N. Chemining’ wa. "Genotype by environment analysis of rice (Oryza sativa L.) populations under drought stressed and well-watered environments." February 2020, no. 14(02):2020 (February 20, 2020): 259–62. http://dx.doi.org/10.21475/ajcs.20.14.02.p2112.

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In Kenya, the key abiotic stress affecting rice production is drought stress which is experienced mainly during reproductive phase of the crop. This study evaluated the performance of Kenyan rice populations including 19 generation of crosses, 6 parental and 5 checks under well-watered and drought stressed environment with the aim of identifying the phenotypic traits that confer drought tolerance in rice. The 19 generation of crosses were in F3 when they were evaluated in the short rains season and later advanced to F4 in the long rains season. Nineteen generation of crosses rice (Oryza sativa L.) lines, six parental and five check lines were evaluated for response to drought under drought stressed and well-watered environment. The study was conducted over two seasons in the year 2016/2017 at Kenya Agricultural Livestock Research Organization (KALRO) -Mwea Centre. The experiment was set up in an alpha lattice design with three replications. Drought stress was imposed at panicle initiation by withholding irrigation till physiological maturity meanwhile the well-watered environment continued to enjoy the recommended irrigation regime from planting to physiological maturity. Yield data were scored for drought tolerance. AMMI analysis of variance for grain yield showed that genotypes from crosses of crosses of SARO5XNERICA11, NERICA2XSARO5 and NERICA15XSARO5 expressed high grain yield. AMMI stability Variance (ASV) showed genotypes NERICA15, Duorado Precoce and progenies from crosses of NERICA11XNERICA2, SARO5XKomboka and NERICA2XNERICA11 expressed high stability in both well-watered and drought-stressed environment. GGE analysis showed that Principal Components (PC1) and PC2 accounted for 96.46% and 3.54%, respectively. GGE biplots showed that genotypes from crosses SARO5XNERICA11 and NERICA15XSARO5 were the most stable and high yielding. GGE biplots ranked the rice lines as follows: those above average in performance, the stable ones, unstable and those below average in performance. SARO5XNERICA11 is worth of selection due to its high mean yield value and is stable across the mega-environments.

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Ndiiri, J. A., B. M. Mati, P. G. Home, B. Odongo, and N. Uphoff. "Adoption, constraints and economic returns of paddy rice under the system of rice intensification in Mwea, Kenya." Agricultural Water Management 129 (November 2013): 44–55. http://dx.doi.org/10.1016/j.agwat.2013.07.006.

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Dianga, Al-Imran, Kamau W. Joseph, and Ruth N. Musila. "Analysis of Combining Ability for Early Maturity and Yield in Rice (Genus: Oryza) at the Kenyan Coast." International Journal of Agronomy 2020 (October 22, 2020): 1–7. http://dx.doi.org/10.1155/2020/6230784.

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The main challenges facing rain-fed rice farming in Kilifi County at the Kenyan coast are inadequate and erratic rainfall, inadequate skills, and poorly developed infrastructure. Of great importance is erratic rainfall that tends to depress towards the end of long rain season, leading to crop failure. Combining ability analysis is one of the most valuable tools used to ascertain gene action effects and help in selecting desirable parents for making crosses and coming up with high yielding and early maturing lines. Combining ability for early maturity and yield has not been studied at the Kenyan coast. This study aimed at determining and identifying good, general, and specific combiners for selecting better parents and better cross combinations in rice crops for developing high yield and short duration lines in rain-fed rice farming. Seven lines were subjected to half-diallel mating design at the Kenya Agricultural and Livestock Research Organization (KALRO), Mtwapa, and at Bahari in Kilifi town. Evaluation for general combining ability (GCA) and specific combining ability (SCA) analysis was done. Combining ability variance and GCA and SCA effects were determined. Based on GCA effects, best parent for early maturity was Dourado Precoce, while for yield, Supaa, Komboka, and NERICA 10. SCA estimates indicated that best crosses for yield were D/S, D/N1, and K/N10, while the best performing cross for early maturity was D/N1.

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Kadipo Kaloi, Francis, Hezron Nyarindo Isaboke, Charles Nyambane Onyari, and Lucy Karega Njeru. "Determinants Influencing the Adoption of Rice Intensification System among Smallholders in Mwea Irrigation Scheme, Kenya." Advances in Agriculture 2021 (March 15, 2021): 1–8. http://dx.doi.org/10.1155/2021/1624334.

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Rice farming has received considerable attention in developing countries and particularly in Kenya due to its impact on smallholders’ income and food security. Irrigated rice is the largest consumer of water, and its sustainability is threatened by water shortage. This has necessitated the development of alternative irrigation water technologies, such as the system of rice intensification (SRI), which are efficient in water use with improved yields. This study analyzed the determinants of adoption of SRI in the Mwea Irrigation Scheme where stratified sampling was used to obtain 364 smallholder rice farmers. A semistructured questionnaire was used to collect primary data, which was then analyzed using a binary logistic regression model. The results showed that age (−0.3%) was significant but with a negative effect on adoption of SRI. Farm size (2.499%), household size (1.895%), distance from the canal (1.354%), off-farm work (3.953%), access to credit services (8.714%), access to extension services (7.809%), and years in rice farming (0.409%) were found positively and significantly influencing factors to the adoption of SRI. Therefore, this study concludes that smallholders attempt to improve rice productivity through adoption of SRI should give a special priority to all significant factors.

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Cheboi, Pius, Shahida Siddiqui, Japheth Onyando, Clement Kiptum, and Volker Heinz. "Effect of Ploughing Techniques on Water Use and Yield of Rice in Maugo Small-Holder Irrigation Scheme, Kenya." AgriEngineering 3, no. 1 (March 3, 2021): 110–17. http://dx.doi.org/10.3390/agriengineering3010007.

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The objective of this study was to determine the effect of paddy rice ploughing techniques on water use and the yield of rice crop, as well as water use efficiency for rice growing in small-holder irrigation schemes. The study was conducted at a farmer’s field in Powo B sub-block of Maugo Irrigation Scheme. The period of study was from July 2019 to January 2020, which is the rice season. The experimental site was located in the vicinity of Olare Shopping Centre, Kamenya Sub-location, Kochia East Location, Kochia Ward, Rangwe Sub-County, Homa Bay County, Nyanza Region, Kenya in Maugo rice scheme in Kenya. In the study, four irrigation tillage practices were applied: ox-plough, conventional ox-plough, hand hoe and tractor ploughing. The results showed that conventional ox-ploughing consumed the highest amount of water at 1240 mm. The highest water use efficiency of 0.49 kg/m3 and highest yield of 5.7 tons/ha were observed for hand hoe ploughing. Use of the hand hoe ploughing technique increased yields by 20 percent, as compared to the conventional ox-ploughing. Therefore, the use of water for ploughing is not necessary in the study area. Future research will be needed to see how farmers are adopting the technology before scaling up to full mechanization, as partial mechanization was not profitable.

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Pili, N. N., T. Kyndt, G. Gheysen, T. Janssen, M. Couvreur, W. Bert, and R. K. Mibey. "First Report of Pratylenchus zeae on Upland Rice from Kwale County, Kenya." Plant Disease 100, no. 5 (May 2016): 1022. http://dx.doi.org/10.1094/pdis-07-15-0743-pdn.

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Rakotomalala, M. R., B. B. Abera, A. Pinel-Galzi, J. Rakotoarisoa, D. Alemu, and D. Fargette. "First Report of Rice yellow mottle virus in Rice in Federal Democratic Republic of Ethiopia." Plant Disease 98, no. 10 (October 2014): 1449. http://dx.doi.org/10.1094/pdis-05-14-0531-pdn.

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Rice yellow mottle virus (RYMV, genus Sobemovirus) is a major biotic constraint to rice production in Africa. First reported in Kenya in 1966, RYMV was later found in most countries in Africa where rice (Oryza sativa, O. glaberrima) is grown (5). In the Federal Democratic Republic of Ethiopia, however, the disease has never been reported in rice fields. In September 2012, plants with leaf yellowing and mottling symptoms were observed near Bahir Dar and in the Fogera district in the northwestern part of the country during a joint survey of scientists from Madagascar (FOFIFA), Ethiopian Institute of Agricultural Research (EIAR), and Japan International Cooperation Agency (JICA). The disease was observed in 2013 in Fogera and Dera districts, where samples were collected, causing small patches of infected plants in ~5% of the fields. Symptomatic leaves of two plants collected in the fields were inoculated on five plants of the susceptible O. sativa cultivar IR64. All inoculated plants reproduced the typical yellow mottle symptoms. Symptomatic leaves of eight plants collected in the fields reacted positively when tested by double antibody sandwich (DAS)-ELISA tests with a polyclonal antiserum raised against a Madagascan isolate of RYMV (2), indicating for the first time the presence of the virus in Ethiopia. Triple antibody sandwich (TAS) tests with discriminant monoclonal antibodies (2) revealed that they all belonged to serotype 4, a serotype found in East Africa and in Madagascar. Total RNA was extracted by the RNeasy Plant Mini kit (QIAGEN, Hilden, Germany) from four samples. The 720-bp coat protein (CP) gene was amplified with reverse transcription (RT)-PCR with the primers 5′CTCCCCCACCCATCCCGAGAATT3′ and 5′CAAAGATGGCCAGGAA3′ (3). The sequences were deposited in GenBank (Accession Nos. KMO17554, KMO14555, KMO17556, and KMO17557). The four sequences showed over 98% nucleotide identity between each other. They shared over 92% nucleotide identity with isolates of strains S4 found in Kenya, Uganda, Tanzania, and Madagascar (4). Agricultural changes associated to rice intensification are known to favor RYMV emergence and spread (5). Recent efforts have been led by the National Rice Research and Development Strategy (NRRDSE) to intensify rice cultivation in Ethiopia (1). Early knowledge of RYMV occurrence in the country is a prerequisite to extended surveys of the disease and implementation of control measures. References: (1) K. Assefa et al. Challenges and opportunities of rice in Ethiopian agricultural development. www.eiar.gov.et/Publications/frgseries2.pdf , 2011. (2) D. Fargette et al. Arch. Virol. 147:583, 2002. (3) A. Pinel et al. Arch. Virol. 145:1621, 2000. (4) M. Rakotomalala et al. Virus Res. 171:71, 2013. (5) O. Traoré et al. Virus Res. 141:258, 2009.

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SILVA, JOÃO VASCO, and JOSHUA J. RAMISCH. "WHOSE GAP COUNTS? THE ROLE OF YIELD GAP ANALYSIS WITHIN A DEVELOPMENT-ORIENTED AGRONOMY." Experimental Agriculture 55, no. 2 (July 5, 2018): 311–38. http://dx.doi.org/10.1017/s0014479718000236.

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SUMMARYYield gaps have become a useful tool for guiding development-related agronomy, especially in the global South. While critics have challenged some aspects of the yield gap methodology, and the relevance of food security advocacy based on yield gaps, very few studies question the actual relevance, application and scalability of yield gaps for smallholder farmers (and researchers) in the tropics. We assess these limitations using two contrasting case studies: maize-based farming systems in Western Kenya and rice-based farming systems in Central Luzon, the Philippines. From these two cases, we propose improvements in the use of yield gaps that would acknowledge both the riskiness of crop improvement options and the role that yield increases might play within local livelihoods. Participatory research conducted in Western Kenya calls into question the actual use and up-scaling of yield measurements from on-station agronomic trials to derive estimates of actual and water-limited yields in the region. Looking at maize yield gaps as cumulative probabilities demonstrates the challenges of assessing the real magnitude of yield gaps in farmers’ fields and of deciding whose yield gaps count for agricultural development in Kenya. In the case of rice-based farming systems, we use a historical dataset (1966–2012) to assess changes in rice yields, labour productivity, gross margin and rice self-sufficiency in Central Luzon, the Philippines. While large rice yield gaps persist here, there appear to be few incentives to close that gap once we consider the position of crop production within local livelihoods. In this context, economic returns to labour for farm work were marginal: labour productivity increased over time in both wet and dry seasons, but gross margins decreased in the wet season while no trend was observed for the dry season. Since most households were rice self-sufficient and further increases in crop production would offer minimal returns while relying increasingly on hired labour, we question who should close which yield gap. Our case studies show the importance of contextualising yield gaps within the broader livelihood context in which farmers operate. We propose that this should be done at farm and/or farming systems level while considering the risks associated with narrowing yield gaps and looking into multiple performance indicators.

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Koudamiloro, Augustin, Francis Eegbara Nwilene, Abou Togola, and Martin Akogbeto. "Insect Vectors of Rice Yellow Mottle Virus." Journal of Insects 2015 (February 2, 2015): 1–12. http://dx.doi.org/10.1155/2015/721751.

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Rice yellow mottle virus (RYMV) is the major viral constraint to rice production in Africa. RYMV was first identified in 1966 in Kenya and then later in most African countries where rice is grown. Several studies have been conducted so far on its evolution, pathogenicity, resistance genes, and especially its dissemination by insects. Many of these studies showed that, among RYMV vectors, insects especially leaf-feeders found in rice fields are the major source of virus transmission. Many studies have shown that the virus is vectored by several insect species in a process of a first ingestion of leaf material and subsequent transmission in following feedings. About forty insect species were identified as vectors of RYMV since 1970 up to now. They were essentially the beetles, grasshoppers, and the leafhoppers. For this review, we presented the chronology of their identification. Also, the biology, ecology, host range, distribution, and caused damage of these insects were briefly summarized.

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Gichuhi, Joseph, Subramanian Sevgan, Fathiya Khamis, Johnnie Van den Berg, Hannalene du Plessis, Sunday Ekesi, and Jeremy K. Herren. "Diversity of fall armyworm, Spodoptera frugiperda and their gut bacterial community in Kenya." PeerJ 8 (March 5, 2020): e8701. http://dx.doi.org/10.7717/peerj.8701.

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Background The invasive fall armyworm, Spodoptera frugiperda (J.E. Smith) is a polyphagous pest that causes widespread damage particularly to maize and sorghum in Africa. The microbiome associated with S. frugiperda could play a role in the insects’ success and adaptability. However, bacterial communities in S. frugiperda remain poorly studied. Methods We investigated the composition, abundance and diversity of microbiomes associated with larval and adult specimens of S. frugiperda collected from four maize growing regions in Kenya through high throughput sequencing of the bacterial 16S rRNA gene. The population structure of S. frugiperda in Kenya was assessed through amplification of the mitochondrial cytochrome oxidase subunit I gene. Results We identified Proteobacteria and Firmicutes as the most dominant bacterial phyla and lesser proportions of Bacteroidetes and Actinobacteria. We also observed differences in bacterial microbiome diversity between larvae and adults that are a likely indication that some prominent larval bacterial groups are lost during metamorphosis. However, several bacterial groups were found in both adults and larvae suggesting that they are transmitted across developmental stages. Reads corresponding to several known entomopathogenic bacterial clades as well as the fungal entomopathogen, Metarhizium rileyi, were observed. Mitochondrial DNA haplotyping of the S. frugiperda population in Kenya indicated the presence of both “Rice” and “Corn” strains, with a higher prevalence of the “Rice” strain.

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MWANGANGI, JOSEPH M., EPHANTUS J. MUTURI, JOSEPHAT I. SHILILU, SIMON MURIU, BENJAMIN JACOB, EPHANTUS W. KABIRU, CHARLES M. MBOGO, JOHN I. GITHURE, and ROBERT J. NOVAK. "ENVIRONMENTAL COVARIATES OF ANOPHELES ARABIENSIS IN A RICE AGROECOSYSTEM IN MWEA, CENTRAL KENYA." Journal of the American Mosquito Control Association 23, no. 4 (December 2007): 371–77. http://dx.doi.org/10.2987/5605.1.

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Niemeijer, Rudo, Marian Geuns, Ted Kliest, Vincent Ogonda, and Jan Hoorweg. "Nutrition in agricultural development: The case of irrigated rice cultivation in West Kenya." Ecology of Food and Nutrition 22, no. 1 (December 1988): 65–81. http://dx.doi.org/10.1080/03670244.1988.9991055.

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Mwadime, R. K. N., A. M. Omwega, N. Kielmann, and R. Korte. "Predictors of nutritional status among participants in a rice irrigation scheme in Kenya." Ecology of Food and Nutrition 35, no. 4 (December 1996): 263–74. http://dx.doi.org/10.1080/03670244.1996.9991496.

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Nyongesa, Benson Ouma, Joseph Bigirimana, Beatrice A. Were, and Rosemary Murori. "Virulence spectrum of populations of Pyricularia oryzae in irrigated rice ecosystems in Kenya." European Journal of Plant Pathology 146, no. 4 (June 1, 2016): 911–22. http://dx.doi.org/10.1007/s10658-016-0969-8.

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Simiyu Mabele, Anthony, Benard Mukoye, and Denis Misiko Mukhongo. "Serological and Molecular Characterization Detects Unique Rice Yellow Mottle Virus Strains in Kenya." American Journal of Plant Biology 5, no. 4 (2020): 120. http://dx.doi.org/10.11648/j.ajpb.20200504.17.

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Gweyi-Onyango, Joseph P., Winnie Ntinyari, Andrew OgollaEgesa, Richard Mose, Symon Njinju, Mekonnen Giweta, and Cargele Masso. "Differences in seasons and rice varieties provide opportunities for improving nitrogen use efficiency and management in irrigated rice in Kenya." Environmental Research Letters 16, no. 7 (June 25, 2021): 075003. http://dx.doi.org/10.1088/1748-9326/ac03dd.

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Veldkamp, A. "Quantitative land evaluation of the Chuka-South area, Kenya." Netherlands Journal of Agricultural Science 36, no. 1 (February 1, 1988): 105–7. http://dx.doi.org/10.18174/njas.v36i1.16701.

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Evaluation of land in the Chuka-South area of central Kenya indicated that there was ample scope for yield increase. Calculated water-limited yield potentials for maize, sorghum, tobacco, cotton, soyabeans, cassava, sweet potatoes, potatoes, rice, Pennisetum americanum, Cajanus cajan and Vigna unguiculata were far above actual yields. Nutrient-limited yield potentials were roughly half the water-limited yield, i.e. natural soil fertility of the Chuka-South area was low. The effects on yield levels of alternative water conservation measures were evaluated for the eastern half of the area. The evaluation indicated that a fair yield increase could be expected from prolonged mulching in the area between 700 and 1000 m. (Abstract retrieved from CAB Abstracts by CABI’s permission)

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Sere, Y., F. Sorho, A. Onasanya, L. Jobe, S. Darboe, Y. Bojang, M. L. Touray, A. Pinel-Galzi, and D. Fargette. "First Report of Rice yellow mottle virus in Rice in The Gambia." Plant Disease 92, no. 2 (February 2008): 316. http://dx.doi.org/10.1094/pdis-92-2-0316b.

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Rice yellow mottle virus (RYMV) of the genus Sobemovirus is a major biotic constraint to rice (Oryza sativa) production in Africa. First reported in Kenya during 1966, RYMV was later found in most countries in Africa where rice is grown (1). In countries in westernmost Africa (The Gambia, Guinea-Bissau, Mauritania, and Senegal), plants with leaf yellowing and mottling symptoms were observed, but RYMV was never isolated. Rice is the staple food in The Gambia. In 2006, four samples were collected from local rice varieties in the Kuntaur Region in the center of The Gambia. Mechanical inoculation with leaf extracts from all samples caused typical yellow mottle symptoms on the susceptible rice varieties BG90-2, Bouaké 189, and IR64. RYMV was detected in the four samples collected by ELISA with polyclonal antisera (2). The 720-nt coat protein gene was amplified for each isolate by reverse-transcriptase-PCR with primers 5′-CAAAGATGGCCAGGAA-3′ (sense) and 5′-CTCCCCCACCCATCCCGAGAATT-3′ (antisense) (2). The RT-PCR products were directly sequenced (EMBL Accession Nos. AM765810, AM765811, AM765812, and AM765813) and then aligned using ClustalW with a pool of RYMV coat protein sequences from West African isolates (EMBL Accession Nos. AJ279905, AJ279901, AJ885137, AJ885124, and AJ279935). Phylogenetic reconstruction by maximum-likelihood with PAUP indicated that the isolates from The Gambia formed a monophyletic group with over 97% nucleotide identity and are closely related to isolates of other countries in West Africa (Burkina Faso, Côte d'Ivoire, Guinea, Mali, and Sierra-Leone) with 91 to 94% identity. Detection of RYMV in The Gambia indicates that RYMV is present in westernmost Africa, which is referred to as the ‘rice belt’ of Africa, and shows that RYMV is widely distributed from eastern Africa (Tanzania) to the western part of the continent. References: (1) N. K. Kouassi et al. Plant Dis. 89:124, 2005. (2) A. Pinel et al. Arch. Virol. 145:1621, 2000.

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Mati, B. M., R. Wanjogu, B. Odongo, and P. G. Home. "Introduction of the System of Rice Intensification in Kenya: experiences from Mwea Irrigation Scheme." Paddy and Water Environment 9, no. 1 (January 11, 2011): 145–54. http://dx.doi.org/10.1007/s10333-010-0241-3.

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CA, Kundu, T. Masunaga, K. Sato, M. Ishii, AYamauchi ., D. Makihara, and RK Wanjogu. "Spatial Variability in Soil Properties and Plant Nutrients of Paddy Rice in Mwea, Kenya." East African Scholars Journal of Agriculture and Life Sciences 3, no. 11 (November 17, 2020): 360–64. http://dx.doi.org/10.36349/easjals.2020.v03i11.003.

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35

Banwo, O. O., M. D. Alegbejo, and M. E. Abo. "Rice yellow mottle virus genus Sobemovirus: a continental problem in africa." Plant Protection Science 40, No. 1 (March 7, 2010): 26–36. http://dx.doi.org/10.17221/1350-pps.

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<I>Rice yellow mottle virus</I> genus <I>sobemovirus </I>(RYMV) was first reported in Kenya in 1966. The disease caused by this virus is fast becoming a major limiting factor in the rice production in Africa and neighbouring islands. It is known to occur in eastern, western and southern African countries and, since very recently, in Central Africa. It is transmitted by insect vectors such as <I>Chaectonema </I>spp., <I>Sesselia pusilla</I> Gerst. and <I>Trichispa sericea</I> Guerin (all <I>Coleoptera</I>) and also by mechanical means. About six strains of the virus now exist. Yield losses caused by the virus range from 20 to 100%. Integrated pest management has been suggested to minimise damage caused by this disease to rice. This paper reviews the characteristics of the virus, symptomatology, host range, distribution, strains, transmission, vector dynamics and virus spread, the economic importance, and management strategies. The need of future research of RYMV is also highlighted.

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Omwenga, Kepha G., Bancy M. Mati, and Patrick G. Home. "Determination of the Effect of the System of Rice Intensification (SRI) on Rice Yields and Water Saving in Mwea Irrigation Scheme, Kenya." Journal of Water Resource and Protection 06, no. 10 (2014): 895–901. http://dx.doi.org/10.4236/jwarp.2014.610084.

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37

Douksouna, Youmma, Joel Masanga, Andrew Nyerere, Steven Runo, and Zachée Ambang. "Towards Managing and Controlling Aflatoxin Producers Within Aspergillus Species in Infested Rice Grains Collected from Local Markets in Kenya." Toxins 11, no. 9 (September 19, 2019): 544. http://dx.doi.org/10.3390/toxins11090544.

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Rice grains can be attacked by a range of pathogens, including Aspergillus species, which can cause the accumulation of aflatoxins and represent a serious threat to the consumers. Aflatoxins are secondary metabolites synthesized by Aspergillus species and naturally occur in various foodstuffs. In this study, we sought to analyze the prevalence of aflatoxin-producing Aspergillus spp. in rice grains currently sold in Kenyan local markets. We analyzed a total of 98 samples randomly collected and primarily analyzed to observe moisture content and fungal growth. We then isolated Aspergillus species, characterized them morphologically and using the Internal transcribed spacer (ITS) primers. Finally, we screened them for aflatoxin-producing isolates targeting Norsolorinic Acid (nor-1) and Versicolorin (ver-1) specific genes involved in aflatoxin biosynthesis. We observed that all tested samples were contaminated. The highest prevalence of Aspergillus species and aflatoxigenic fungal species, had values of 66% and 36.4% for nor-1 and ver-1, respectively. In total, 66% of all isolates were confirmed to be aflatoxin producers. The occurrence of high contamination levels of Aspergillus species points to the possibility of production of aflatoxins in rice grains. This work provides a baseline for future studies on the occurrence of mycotoxigenic fungal species in rice grains being sold in local markets and strategies to control these aflatoxigenic strains at pre- and post-harvest levels.

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Mutero, C. M., H. Blank, F. Konradsen, and W. van der Hoek. "Water management for controlling the breeding of Anopheles mosquitoes in rice irrigation schemes in Kenya." Acta Tropica 76, no. 3 (October 2000): 253–63. http://dx.doi.org/10.1016/s0001-706x(00)00109-1.

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MUTURI, EPHANTUS J., ROBERT J. NOVAK, JOHN I. GITHURE, WEIDONG GU, BENJAMIN G. JACOB, and JOSEPHAT I. SHILILU. "LARVAL HABITAT DYNAMICS AND DIVERSITY OF CULEX MOSQUITOES IN RICE AGRO-ECOSYSTEM IN MWEA, KENYA." American Journal of Tropical Medicine and Hygiene 76, no. 1 (January 1, 2007): 95–102. http://dx.doi.org/10.4269/ajtmh.2007.76.95.

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40

Ouma, Matilda A., Christopher A. Onyango, Justus M. Ombati, and Nelson Mango. "Innovation platform for improving rice marketing decisions among smallholder farmers in Homa-Bay County, Kenya." Cogent Food & Agriculture 6, no. 1 (January 1, 2020): 1832399. http://dx.doi.org/10.1080/23311932.2020.1832399.

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Tyler, Stanley C., Patrick R. Zimmerman, Colin Cumberbatch, James P. Greenberg, Curtis Westberg, and Johanna P. E. C. Darlington. "Measurements and interpretation of δ13C of methane from termites, rice paddies, and wetlands in Kenya." Global Biogeochemical Cycles 2, no. 4 (December 1988): 341–55. http://dx.doi.org/10.1029/gb002i004p00341.

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42

Muturi, Ephantus J., Joseph Mwangangi, Josephat Shililu, Simon Muriu, Benjamin Jacob, Ephantus Kabiru, Weidong Gu, Charles Mbogo, John Githure, and Robert Novak. "Mosquito Species Succession and Physicochemical Factors Affecting Their Abundance in Rice Fields in Mwea, Kenya." Journal of Medical Entomology 44, no. 2 (March 1, 2007): 336–44. http://dx.doi.org/10.1093/jmedent/44.2.336.

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43

Muturi, Ephantus J., Chang-Hyun Kim, Frederick N. Baliraine, Solomon Musani, Benjamin Jacob, John Githure, and Robert J. Novak. "Population Genetic Structure ofAnopheles Arabiensis(Diptera: Culicidae) in a Rice Growing Area of Central Kenya." Journal of Medical Entomology 47, no. 2 (March 1, 2010): 144–51. http://dx.doi.org/10.1093/jmedent/47.2.144.

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44

Onaga, G., R. Murori, G. Habarugira, O. Nyongesa, J. Bigirimana, R. Oliva, C. Vera Cruz, G. Onyango, J. Andaku, and J. Ongom. "First Report of Xanthomonas oryzae pv. oryzicola Causing Bacterial Leaf Streak of Rice in Kenya." Plant Disease 102, no. 5 (May 2018): 1025. http://dx.doi.org/10.1094/pdis-06-17-0846-pdn.

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Pili, Njira Njira, Soraya C. França, Tina Kyndt, Billy A. Makumba, Robert Skilton, Monica Höfte, Richard K. Mibey, and Godelieve Gheysen. "Analysis of fungal endophytes associated with rice roots from irrigated and upland ecosystems in Kenya." Plant and Soil 405, no. 1-2 (July 20, 2015): 371–80. http://dx.doi.org/10.1007/s11104-015-2590-6.

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46

Longué, D. R. S., A. Galzi-Pinel, S. Semballa, I. Zinga, D. Fargette, and O. Traoré. "First Report of Rice yellow mottle virus in Rice in the Central African Republic." Plant Disease 98, no. 1 (January 2014): 162. http://dx.doi.org/10.1094/pdis-04-13-0418-pdn.

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Rice yellow mottle virus (RYMV, genus Sobemovirus) is a major biotic constraint to rice production in Africa. First reported in Kenya in 1966, RYMV was later found in most countries in Africa where rice (Oryza sativa, O. glaberrima) is grown (4). In the Central African Republic, the disease has never been reported in rice fields. In October 2011, plants with leaf yellowing and mottling symptoms were observed in large irrigated rice production schemes about 30 km west of Bangui, the capital of the Central African Republic, and in lowland subsistence fields in Bangui outskirts. Disease incidence was estimated at 5 to 10%, causing small patches in the fields. Mechanical inoculation with extracts of symptomatic leaves reproduced the typical yellow mottle symptoms on the susceptible O. sativa cultivar BG90-2 6 to 9 days after inoculation. Symptomatic leaves of 12 cultivated plants collected in seed beds or in fields reacted positively when tested by ELISA with polyclonal antisera raised against a Madagascan isolate of RYMV (1). Discriminating monoclonal antibodies showed that the samples contained RYMV serotype 1, a serotype found in West and Central Africa (1). Total RNA was extracted by the RNeasy Plant Mini kit (QIAGEN, Hilden, Germany) from six samples. The 720-nt RYMV coat protein gene was amplified by reverse transcriptase (RT)-PCR with primers 5′CTCCCCCACCCATCCCGAGAATT3′ and 5′CAAAGATGGCCAGGAA3′ (2). RT-PCR products were directly sequenced and sequences were deposited in GenBank (Accession Nos. KF054740 through KF054745). These six sequences showed over 98% identity with each other, and were found to be closely related to sequences of isolates from Chad and Cameroon in Central Africa (3). Knowledge of the presence of RYMV in the Central African Republic is important since rice cultivation has intensified in this country. In addition, rice is also increasingly considered as one of the main staple crops in the country. References: (1) D. Fargette et al. Arch. Virol. 147:583, 2002. (2) A. Pinel et al. Arch. Virol. 145:1621, 2000. (3) O. Traoré et al. Plant Dis. 96:1230, 2001. (4) O. Traoré et al. Virus Res. 141:258, 2009.

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Ndikumana, I., A. Pinel-Galzi, Z. Negussie, S. N'chimbi Msolla, P. Njau, R. K. Singh, I. R. Choi, J. Bigirimana, D. Fargette, and E. Hébrard. "First Report of Rice yellow mottle virus on Rice in Burundi." Plant Disease 96, no. 8 (August 2012): 1230. http://dx.doi.org/10.1094/pdis-03-12-0293-pdn.

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Since the mid-1980s, rice cultivation has expanded rapidly in Burundi to reach approximately 50,000 ha in 2011. In 2007, leaf mottling, reduced tillering, and stunting symptoms were observed on rice at Gatumba near Bujumbura, causing small patches in less than 10% of the fields. Rice yellow mottle virus (RYMV, genus Sobemovirus), which has seriously threatened rice cultivation in Africa (1) and was recently described in the neighboring Rwanda (3), was suspected to be involved because of similar symptoms. To identify the pathogen that caused the disease in Burundi, a survey was performed in the major rice-producing regions of Burundi and Rwanda. Six locations in Burundi and four in Rwanda were investigated in April and October 2011. Disease incidence in the fields was estimated to be 15 ± 5%. Symptomatic leaves of 24 cultivated rice plants were collected and tested by double antibody sandwich-ELISA with polyclonal antibodies raised against the RYMV isolate Mg1 (2). All tested samples reacted positively. Four isolates were inoculated on susceptible Oryza sativa cultivar IR64 (2). The typical symptoms of RYMV were reproduced 7 days after inoculation, whereas the noninoculated controls remained healthy. Total RNA was extracted by the RNeasy Plant Mini kit (QIAGEN, Hilden, Germany) from 12 samples. The RYMV coat protein gene was amplified by RT-PCR with primers 5′CGCTCAACATCCTTTTCAGGGTAG3′ and 5′CAAAGATGGCCAGGAA3′ (3). The sequences were deposited in GenBank (Accession Nos. HE654712 to HE654723). To characterize the isolates, the sequences of the tested samples were compared in a phylogenic tree including a set of 45 sequences of isolates from Rwanda, Uganda, western Kenya, and northern Tanzania (2,3). Six isolates from western Burundi, namely Bu1, Bu2, Bu4, Bu7, Bu10, and Bu13 (Accession Nos. HE654712 to HE654716 and HE654718), and the isolate Rw208 (HE654720) from southwestern Rwanda, belonged to strain S4-lm previously reported near Lakes Malawi and Tanganyika. They fell within the group gathering isolates from the western Bugarama plain of Rwanda (3). The isolates Bu16 (HE654719) and Bu17 (HE654717) from Mishiha in eastern Burundi belonged to strain S4-lv previously reported around Lake Victoria. However, they did not cluster with isolates from the eastern and southern provinces of Rwanda. They were genetically more closely related to isolates of strain S4-lv from northern Tanzania. Overall, the phylogeography of RYMV in Burundi and Rwanda region was similar. In the western plain of the two countries, the isolates belonged to the S4-lm lineage, whereas at the east of the two countries at midland altitude, they belonged to the S4-lv lineage. The presence of RYMV in Burundi should be considered in the future integrative pest management strategies for rice cultivation in the country. References: (1) D. Fargette et al. Annu. Rev. Phytopathol. 44:235, 2006. (2) Z. L. Kanyeka et al. Afr. Crop Sci. J. 15:201, 2007. (3) I. Ndikumana et al. New Dis. Rep. 23:18, 2011.

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Momanyi, Kennedy Moseti, James Wanjohi Muthomi, and John Wangai Kimenju. "Fusarium Wilt of Banana in Kisii County, Kenya." Current Agriculture Research Journal 9, no. 1 (May 31, 2021): 16–26. http://dx.doi.org/10.12944/carj.9.1.03.

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Banana categorized as third in world’s key starch crops after cassava and sweet potatoes and it is the fourth most widely grown crop after rice, wheat and maize. The crop accounts for over 70 % of farmer’s earnings in Kisii county of Kenya. Farmers growing the crop are facing several challenges including depletion of soil fertility, low yields and diseases especially Fusarium wilt caused by Fusarium oxysporum f.sp. cubense (Foc). A study was conducted to determine the status of this disease in Kisii County. Ten farms were sampled in each Agro-ecological zone and in each farm four symptomatic and four non-symptomatic mats were sampled. Incidence was determined by relating banana seedlings affected and the total number of banana seedlings planted while severity was determined by measuring the extent of the damage/brown discoloration of the stem in length. Banana roots and pseudostem cuttings that were infected with the disease were used for isolation of the pathogen.Fusarium wilt is common in banana producing regions of Kisii County, however, the management practices are poor and do not meet the required strategies for controlling the disease. It was established that only; wood-ash and poultry manure were used by a few farmers in managing this disease. Present report is an attempt to improve the understanding of distribution and diversity of Foc in banana producing regions of Kisii County thereby aiding formulation of appropriate mitigation measures which the farmers can adopt locally.

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Otieno, Nickson Erick, Alex S. Mutati, Cynthia Akoth, Daniel Ogwanjg, Timothy Mwinami, Philip Alaro, and Jeremy Njoka. "Role of Invertebrate Prey Abundance on Waterbird Distribution Across Rice Field Growth Stages in Western Kenya." Waterbirds 38, no. 1 (March 2015): 47–57. http://dx.doi.org/10.1675/063.038.0107.

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Momo, J. A., W. M. Thagana, and Mukiri Githendu. "Effect of Withholding Irrigation Water after Complete Heading on Rice Yield and Components in Mwea-Kenya." Journal of Agricultural Sciences 4, no. 2 (December 2013): 69–75. http://dx.doi.org/10.1080/09766898.2013.11884703.

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