Journal of
Agricultural Extension and Rural Development

  • Abbreviation: J. Agric. Ext. Rural Dev
  • Language: English
  • ISSN: 2141-2170
  • DOI: 10.5897/JAERD
  • Start Year: 2009
  • Published Articles: 422

Full Length Research Paper

Farmer preference for selected finger millet (Eleusine coracana) varieties in Rift Valley, Kenya

J. M. Tracyline
  • J. M. Tracyline
  • Department of Crops, Horticulture and Soils, Egerton University, P. O. Box 536-20115 Egerton, Kenya.
  • Google Scholar
P. K. Kimurto
  • P. K. Kimurto
  • Department of Crops, Horticulture and Soils, Egerton University, P. O. Box 536-20115 Egerton, Kenya.
  • Google Scholar
J. J. Mafurah
  • J. J. Mafurah
  • Department of Crops, Horticulture and Soils, Egerton University, P. O. Box 536-20115 Egerton, Kenya.
  • Google Scholar
N. W. Mungai
  • N. W. Mungai
  • Department of Crops, Horticulture and Soils, Egerton University, P. O. Box 536-20115 Egerton, Kenya.
  • Google Scholar
H. Ojulong
  • H. Ojulong
  • ICRISAT Regional Office, Nairobi Kenya, P. O. Box 301265-0001, Nairobi.
  • Google Scholar


  •  Received: 28 September 2020
  •  Accepted: 30 December 2020
  •  Published: 31 March 2021

 ABSTRACT

Lack of awareness and information on the traits of orphan crops such as finger millet is a major constraint to finger millet production. Farmer participatory and varietal selection (FVPS) is an efficient method of achieving productivity through enhancing adoption of improved high yielding varieties. A study was conducted in two major growing areas in central Rift Valley, Agri-ecological zone III (ATC-Nakuru and Bomet), to assess the level of awareness and farmer preference of twenty-five finger millet varieties. Farmer participatory variety selection was conducted at physiological maturity of the finger millets. One hundred farmers assessed and scored their preferred traits and varieties in each site. The scores were ranked on a scale of 1-5 in Focused Group Discussions (FDGs) and analyzed using Kruskal Wallis H-test of non-parametric data using Statistical Package for Social Science (SPSS) while scores collected on variety traits were used to construct a Pair-wise ranking table to find the best traits selected by farmers. The results showed that farmers preferred high yielding varieties with qualities such as uniformity, drought tolerance, tillering ability, big fingers, lodging and folded or straight fingers. They appreciated the snapping varieties for the ease of harvesting using fingers instead of traditional cutting using a knife. Kal 2 Pader (3.9), P-224 (3.9), KatFM1×U151.6.6.3.1.1 (3.9), GBK 027189A (2.8), Snapping green early (3.7) and KatFM1xU151.7.8.2.1 (3.7) were the most preferred varieties while in AEZ III, Bomet ATC KatFM1 (4.3), KNE 741 (4.3), KNE629 (4.2), KatFM1×U151.6.6.3.1 (4.1), Gulu E (3.9), GBK 027189A (3.8) and Kal 2 pader (3.8) were the most preferred varieties in ATC Nakuru. In both sites KatFM1×U151.6.6.3.1.1 (4.0), Kal 2 pader (3.85) and GBK 027189A (3.8), Gulu E (3.75) and P-224 (3.75), were ranked the best. The farmers expressed their interest in accessing the seeds of these improved varieties. FPVS provides a platform for identification of the most preferred traits of finger millet and knowledge dissemination of improved varieties to farmers.

Key words: Finger millet, farmer participatory variety selection (FVPS), farmers preferred traits and varieties.


 INTRODUCTION

Finger millet (Eleusine coracana) is highly nutritious cereal food for the weak and people with low immunity (Takan et al., 2012). It contains nutritional elements which are easy to digest thus a major source of food for pregnant women, the sick, lactating mothers, children and   diabetics   (Singh   and  Raghuvanshi,  2012).  E. coracana is the most important small millet grown for subsistence in Eastern Africa and Asia. In East Africa, it is majorly used for food in form of thin porridge, malting and brewing (Mitaru et al., 1993). In Kenya, finger millet also commonly called ‘wimbi’ is used for making porridge, thick porridge ‘ugali’ and for brewing. Finger millet production has declined over the years from 99000 tons in 2015 to 54000 tons in 2016 and 2017. It is commonly planted in Western Kenya, around Lake Victoria and in Eastern Kenya. Western Kenya has 77,000 ha (29%), Nyanza 57,000 ha (15%) and Rift Valley 65,000 ha (13%) under finger millet production (FAO, 2012).

However, in recent years, finger millet has witnessed an expansion in the last 5 year to >200,000 ha (Upadhyaya et al., 2016) due to combined research and promotion efforts that have provided new varieties, improved agronomy, and growing of the crop as an alternative to Maize Lethal Necrosis Disease (MLND) in many areas including Bomet (Mgonja et al., 2007).

Finger millet production is still low due to continuous use of poor unimproved landraces that are mostly susceptible to blast and low yielding, insufficient information on improved varieties, poor dissemination of seeds, post-harvest handling of finger millet and poor attitude linked to the crop (Degu et al., 2009; Molla et al., 2020). This has been a major challenge for adoption of finger millet to farmers in Kenya. High yielding varieties have been developed and released for general cultivation through breeding of exotic and indigenous lines by researchers but adoption is still a challenge (Singh et al., 2016). FPVS  has  resulted  in  positive  impact  with  adoption  of  technology  and improvement of livelihood to both farmers and researchers (Witcombe et al., 2005). It has been successfully done in many crops including rice (Paris, 2011; Panwar et al., 2019; Orlando et al., 2020), beans (Tamene, 2016; Yadavendra et al., 2017), barley (Ferede and Demsie, 2020), wheat (Van Frank et al., 2020), sorghum (Sissoko et al., 2019; Vom et al., 2020), Bambara nuts in Malawi (Pungulani et al., 2012) and finger millet (Ojulong et al., 2017; Tarekegne et al., 2019). Various varieties of finger millet have been up-scaled, released, adopted and disseminated to farmers in countries such as Tadesse, Wama, Degu and ACC#213572 for Delgi and Chilga in Ethiopia (Fentie, 2012), and U-15 and P-224 in Tanzania (Ojulong et al., 2017) through Farmer Participatory Varietal Selection (FVPS). Different environmental conditions, traits of interest, cultural and religious beliefs, gender, marketability and value addition among others influence the choice made by farmers during evaluation (Cleveland et al., 2000). Recent research incorporates farmers for improved uptake, knowledge dissemination and promotion of innovations which can easily be found during FVPS. This study aimed at identifying the most preferred traits and varieties of finger millet identified in AEZ III, ATC Nakuru and Bomet for future breeding, up-scaling and release of the farmer-chosen varieties.


 METHODOLOGY

Site description

The experiment was conducted during the long rain season 2019, January-June and short rain season of June-December, in ATC-Bomet and ATC-Nakuru, respectively. ATC-Bomet, the experiment was done at longitude 35°20’29.62” E and latitude of 0° 46’52.64” N. It is a medium altitude zone with an evenly distributed rain throughout the year and a mean rainfall of 1000-1400 mm. The mean monthly temperature is 17.2°C. Soils are Humic Nitisols. ATC-Nakuru, lies at a longitude of 36°04'0.01" E and a latitude of 0°16'59.99" N with a mean annual rainfall of 1012 to 1800 mm, well distributed and temperature ranging from 15 to 20°C. Soils are Mollic Andosols, well drained dark reddish brown for ATC-Nakuru (Jaetzold and Schmist, 2012).

Experimental layout and management operations

The experiment was laid out in Alpha lattice design with 5 blocks and 3 replications. Each experimental plot was 2 m long by 2 m wide therefore having a gross area of 4 m2. Each block had four rows, each 2 m long. Planting was done by hand drilling both the seeds and the fertilizer at the rate of 20 kg/ha. Fertilizer was applied during planting at a rate of 40 kg/ha N of DAP sourced from Spring fertilizer. 48 kg/ha P2O5 applied during topdressing as CAN during topdressing at tillering stage. Due to differences in maturity which affected tillering stages among the varieties, an interval of two weeks was considered during application to the late maturing varieties.

Data was collected from center two rows to reduce the border effect. All management practices such as thinning and gapping, weeding, and topdressing were performed as required.

All data collected was subjected to Statistical Analysis Software (SAS) and SPSS. Pair-wise comparison, mean tables were then constructed to give the best varieties and traits in both sites. SAS was used to compute univariate procedure to give standard error of the means.

Plant genotypes

Twenty-five finger millet genotypes were planted in Agri-Ecological Zone (AEZ) III in both ATC Nakuru and ATC Bomet. The 25 genotypes were sourced from ICRISAT, Egerton Seed Unit, KALRO, Genebank of Kenya and local varieties. Of the 25 selected varieties, eight are commercial varieties, twelve are advanced breeding lines and five are local varieties (Table 1).

Farmer participatory variety selection

Target population and sampling procedure

The target group of study was smallholder millet farmers in Nakuru and Bomet counties. This group was composed of people of varying gender and age, income groups, lifestyles and education levels. The area had a high concentration of people whose project targets and deliverables were directly impacted on their livelihoods. A sample size was generated using Yamane formula (Yamane, 1973):

n = N / (1 + Ne2)

Where n= corrected sample size, N= population size, e= (0.08)2 the margin of error 30= 300/1+300(0.08)2=102 farmers.

Farmers’ ranking on traits of finger millet

Ranking and selection of best performing varieties and varietal differences was conducted when the crop was at physiological maturity. At this stage, farmers were able to note the agronomic differences of finger millet such as flower type (folded or straight), number of tillers, grain color, uniformity among other traits scored by farmers. Farmers were grouped into Focused Group Discussion (FGD) consisting of 10 farmers and one extension officer assigned to each group. They were then provided with scoring templates that contained the variety numbers (1-25) arranged vertically on the left of the sheet and the scoring traits arranged horizontally. Each of the varieties was scored on a scale of 1 to 5 (very poor to excellent respectively) (ICRISAT, 2011) (Table 2). The scores were then utilized for identification of most preferred traits and varieties. Traits included high yielding-based on agronomic traits of the plant, size of the fingers, high tillering ability, resistance to bird infestation and lodging among others. Early maturity-based on early days to heading, anthesis and physiological maturity. Marketability-based on the color of the grain and ability to be availed to the market on time depending on maturity. Drought tolerance, the ability to mature early and escape drought and high number of tillers. Blast tolerance-ability to resist and tolerate blast disease both on finger and leaf. Big fingers- based on the finger length and finger number. Lodging was based on ability to resist lodging by having strong stems and medium height. Grain color-based on red, black brown and white. Tillering-based on the number of tillers per plant and uniformity-the  ability  to  have   a  uniform height   and  mature uniformly. Varieties were ranked based on the scores received per trait and afterwards the scoring sheet collected and separated according to gender. Both qualitative and quantitative data was then used as an indication of final scoring and selection of traits and varieties chosen by farmers. This data did not only give the best traits and varieties chosen by farmers in both regions but also the overall comments and opinions of farmers on finger millet in both regions. Survey data collected (Table 5) was subjected to Kruskal-Wallis test of non-parametric data and the highest means and ranking was used to obtain the best varieties selected by farmers using Statistical Package for Social Sciences version 20. A pairwise ranking matrix was also done to obtain the best traits selected by farmers. Statistical Analysis Software (SAS) was used in univariate analysis to find the standard error of the means and to check the normality of the data.


 RESULTS AND DISCUSSION

Farmer preference of finger millet traits

Results of the study (Table 3) showed farmers had high preference to varieties with higher uniformity (3.98), drought tolerance (3.80), snapping ability (3.79), tillering ability (3.69), big fingers (3.55) and high yielding (3.54) and resistance to lodging (3.51) in both sites. In Nakuru county, farmers  recognized  good  taste  (2.72), grain color (2.46) and folded or straight fingers (1.73) as least important while in Bomet marketability (3.32), early maturity (3.19) and resistance to diseases (2.19) received the lowest score (Table 2). A pair-wise comparison (Table 4) was done to determine the most preferred trait of finger millet as scored by farmers and the best  traits  selected  and  ranked (Table  4). For the presence of various varieties ranging from commercial varieties, advanced breeding lines and local varieties, there were different opinions of varieties basing on their performance.

Selection was based on yield and yield component traits including uniformity, drought tolerance, tillering ability, big finger, lodging and folded or straight fingers; resistance to challenges such as bird infestation and resistance to diseases; and good marketing ability such as good taste, grain color. Farmers selected the best traits of finger millet based on the yield traits and yield performance of the varieties including high yielding, tolerance to diseases and birds, high tillering ability, plant height and early maturity. The  farmers  evaluated  and  ranked the best chosen traits of finger millet through Focused Group Discussions (FDG) and using a pairwise ranking matrix  (Table  3), the  best  trait were selected for future breeding purposes. Pair-wise ranking and farmers’ preference linked to  high  yielding,  high   tillering,   resistance  to diseases, grain color and good threshability (Owere et al., 2014; Watson, 2019; Sibiya et al., 2013).

The farmers had a high preference for uniformity of finger millet (3.91). The response was that non uniform varieties have difficulties in management causing increased labor. Uniformity provides an ease of management activities such as  ease  of harvesting, weeding and spraying for the control of weeds. Farmers also had a high preference to drought tolerant varieties (3.75) especially in Bomet as reported by Owere et al. (2016) who stipulated that height  of  1±0.2 m,  high tillering ability and drought tolerant varieties are most preferred by farmers. Tillering ability and big fingers (3.69 and 3.55, respectively) of the variety were directly linked to high yielding qualities si. The higher  the  number of tillers the higher the plant will produce and the bigger the finger length and number the higher the number of seeds a panicle could carry. Sadreddine (2016) and Hadjichristodoulou (1985) reported that in order to select the high yielding varieties for breeding purposes in multi-environments, one should consider tillering as an important trait. The farmers had major interest on big fingers as compared on folded or straight fingers. They observed that the bigger the fingers whether they have a straight or folded type, could yield more seeds. Therefore, they preferred big-fingered varieties. The folded varieties also had an advantage over the straight varieties. They pointed out that the folded-finger variety could easily escape disease and bird attack as compared to the straight type of varieties. This however did not seem to directly  affect  the traits that led to high yield therefore scoring less compared to other traits.

The farmers assessed the grain color of the varieties and used it to determine the marketability of the varieties. The color of the grain was either reddish brown, brown or white seeded. The scores were then used to calculate the percentages and presented in Figures 1 and 2. The most preferred traits of finger millet were the reddish brown color in Bomet while in Nakuru farmers also preferred the red and brown seeded varieties. It was most preferred because it fetches high prices in the market. The farmers were able to point the fact that it could blend well with other flours such as cassava and sorghum, which is similar to the results by Oduori and Kanyenji (2007). The second best preference for  farmers  was  the  brown  grain  seeded varieties which had similar comments only that it fetched slightly lower prices as compared to the reddish brown. These two varieties were also said to be resistant to blast disease and also they were not preferred by birds because of the bitter taste they contained. The white grained was said to be sweeter and more suitable for brewing. Ravikumar and Jeetharam (1993) reported that the white seeded had higher content of proteins and lower phenols and tannins. This is the reason for birds and blast susceptibility to the variety.

Farmers experienced difficulties in identification of blast disease in the varieties and the only way they could score is by checking the mature heads. Most farmers had not known that it was a disease and had suspects of birds or other pest such as shoot fly. Farmers also had minimal knowledge on differentiating an attack by shoot fly and the blast disease. Also the compact headed varieties were found to be resistant to blast disease as compared to the open and straight finger types. Farmer’s knowledge on blast disease was minimal. The farmers could not differentiate the disease when it was on the leaf. On the head attack the compact fingers projected a higher preference as compared to the straight fingers. These results show similarity with Takan (2004). There was a serious lack of awareness concerning the disease.

Farmer preference on the varieties

The findings of the study showed that there was variation in the scoring of the varieties in both sites. In Nakuru ATC, majority of farmers participated in the evaluation process leading to a higher scoring compared to ATC-Bomet. The varieties had different characteristics due to genotype by environment interaction which was evident in the performance and traits of the finger millet (Kebede et al., 2019). Scores ranged from a mean of 3.9 to 2.9 and 4.3 to 2.2 highest to lowest in Nakuru and Bomet, respectively (Table 4). In Nakuru-ATC, Kal 2 Pader (3.9), P-224 (3.93), KatFM1×U151.6.6.3.1.1 (3.9), GBK 027189A (2.8), Snapping green early (3.7) and KatFM1×U151.7.8.2.1 (3.7) were the most preferred varieties (Table 4) while in Bomet-ATC, KatFM1 (4.3), KNE 741 (4.3), KNE629 (4.2), KatFM1×U151.6.6.3.1 (4.1), Gulu E (3.9), GBK 027189A (3.8) and Kal 2 pader (3.8) were the most preferred varieties (Table 6). In both sites KatFM1×U151.6.6.3.1.1 (4.0), Kal 2 pader (3.85), GBK 027189A (3.8), Gulu E (3.75) and P-224 (3.75) ranked the best (Figure 1). On the selection of varieties, the best selected varieties in both areas had a high yielding, high tillering ability, resistance to diseases and pest, high number of tillers and uniformity (Tables 4 and 5).

Kal 2 pader a local variety stood out to be best in both ATCs; this is a local variety. Local varieties such as   Kal  2  Pader,   Ikhulule   and   Otiyo  Brown  are  well adapted to the local environments of farmers. The farmers pointed out that the variety can easily survive extreme temperature and rainfall patterns and therefore receiving better preferences. Kal 2 Pader however was the best as it was high yielding, matured early and had resistance to birds. GRAIN and the Alliance for Food Sovereignty in Africa (AFSA, 2018) supports this after an experiment was done in Uganda. Farmers’ preferred local varieties because of their resilience, taste and local preferences such as cultural and spiritual significance. GBK 027189A is a released variety in Kenya mostly for rift valley regions. It performed highly in both regions because it is modified to adapt to these regions (Manyasa, 2013). They were depicted by its ability to have high yields of 1300 and 900 kg ha-1 in Nakuru and Bomet, respectively. Gulu E and P-2224 are commercial varieties with ability to resist birds and other pests and the agronomic traits. Other varieties that caught the attention of farmers were SMDF 1702, Snapping Green early and snapping purple variety.

In ATC-Nakuru, variety SMDF 1702 an advanced breeding line, had short height, takes long to mature and has a spreading nature with high number of tillers. It had high preference to farmers who kept livestock, they marveled at its ability to produce more feed to cattle. They therefore recommended that the variety was suitable for livestock feed and should be improved as a fodder crop. KNE 741, a commercial variety was among the best varieties selected in ATC-Bomet, because of its high yielding ability and early maturity. Maturing early is considered as an ability to escape drought. The medium height of this variety also makes it to escape lodging a characteristic that is important to farmers from Bomet. In Nakuru however this was entirely opposite of what was expected. This is because the variety had an earlier maturity of 80.5 days (Table 6) which made it more susceptible to birds and blast disease. Farmers evaluated the variety based on what they see and since most of them saw the damage due to disease and birds, hence the least score in Nakuru. In Bomet, the same variety scored among the best. This is because, the plot was carefully guided against birds using a scarecrow and physically chasing them away. KatFM1×U151.6.6.3.1.1 was high yielding and had high number of tillers, early maturing, highly uniform and with good grain qualities. Such was desirable to farmers in both ATCs. Snapping Purple variety had high preference in both ATCs. This is not only because of its highly snapping ability during harvesting but also it is resistant to pests including birds and diseases such as blast. The variety is also high yielding with 800 and 900 kg ha-1 in Nakuru and Bomet-ATCs, respectively. Snapping green early has an ability to snap very early, high yielding with 900 kg ha-1 in both sites. The variety also has numerous tillers, a contributing factor to the high yield. Farmer based selection was dependent on the attributes   of  each  variety  most  importantly  the  high yielding traits. Snapping green early also has an ability to escape drought by maturing early.

The study provided a need for extension services in the value addition of finger millet, processing and market information. There  were also other socio-economic challenges expressed by farmers such as labor intensive farming practices that includes weeding, post-harvest handling of finger millet, insufficient information of  improved   genotypes,  insufficient  supportive agencies among others which were pointed out by Gurung et al. (2016) and Pudasaini et al. (2016). For promotion and utilization of finger millet, capacity building is necessary for farmers and agricultural extension workers (Mgonja et al., 2017).In general, Nakuru had the highest means in plant height, number of days to maturity and yield in t/ha as compared to ATC-Bomet. Varieties in Nakuru ATC had the highest mean height (0.85 m) with a longer maturity period (97.2 days) and high yield of 1300 kg ha-1 compared to Bomet ATC which had medium height of 0.57 m, lower maturity days of 95.7 days and 0.9 t/ha yield. The best performing varieties in ATC-Nakuru are Kal 2 Pader, P-224, KatFM1×U151.6.6.3.1.1 and GBK 027189A and Snapping green early with higher yield ranging from 1.18 ± 0.0757 to 1.29 ± 0.0757 t/ha, respectively (Table 7) while in Bomet-ATC they are KatFM1, KNE 741, KNE629, KatFM1×U151.6.6.3.1 and Gulu E, GBK 027189A and Kal 2 pader with yield ranging from 0.5 ± 0.0506 to 1.02 ± 0.0506 t/ha, respectively (Table 8).  KNE 629 and IE 2872 had the highest yield in both sites with 2.13 and 1.49 t/ha. IE 2872 was the highest in ATC-Bomet with 1.57 t/ha. The yield could be affected by weather. In Bomet, the yield was quite low 900 kg ha-1 due to high rainfall that settled in the finger millet plots. This interfered with the performance  of  the   varieties   leading  to  low  yields.  In Nakuru, high yield was observed despite the high infestation of birds in the region. This is because of the favorable conditions of the short season period favored by cool and humid climate.


 CONCLUSION

Farmers preferred uniform varieties with high tillering ability, drought tolerant, and varieties with big fingers. KatFM1×U151.6.6.3.1.1, Kal 2 pader, Ikhulule, P-224, Gulu-E, Snapping green early and GBK 027189A were the preferred varieties by farmers from Nakuru while KatFM1, KNE 741, KNE629, KatFM1×U151.6.6.3.1, U-15 and Kal Dokolo were the most preferred varieties for Bomet. The farmers also expressed the lack of awareness on blast disease and pests affecting finger millet. The lack of information on improved varieties was also a major factor that discouraged farmers from growing millets. Further research should be done on Farmer Participatory and Varietal Selection of finger millet in various regions of Kenya in order to increase awareness of improved finger millet varieties and possibly adoption.


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interests.


 ACKNOWLEDGMENTS

The authors thank the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM) under Grain Legume and Dryland Cereals (GLDC) project, for provision to conduct this research and Kihingo Farmers group and Longisa farmer group from Nakuru and Bomet County, respectively for their participation.



 REFERENCES

Cleveland DA, Daniela S, Smith SE (2000). A biological framework for understanding farmers' plant breeding. Economic Botany 54(3):377-394.
Crossref

 

Degu E, Debello A, Belete K (2009). Combining ability study for grain yield and yield-related traits of grain sorghum [Sorghum bicolor (L.) Moench] in Ethiopia. Acta Agronomica Hungarica 57(2):175-184.
Crossref

 

Food and Agriculture Organization (FAO) (2012). Food and Agriculture Organization of the United Nations. 2012. FAO statistical yearbook.

 

Fentie M (2012). Participatory evaluation and selection of improved finger millet varieties in north western Ethiopia. International Research Journal of Plant Science 3(7):141-146.

 

Ferede M, Demsie Z (2020). Participatory evaluation of malt barley (Hordium disticum L.) varieties in barley-growing highland areas of Northwestern Ethiopia. Cogent Food and Agriculture 6(1):1756142.
Crossref

 

GRAIN and the Alliance for Food Sovereignty in Africa (AFSA) (2018). The real seeds producers: Small-scale farmers save, use, share and enhance the seed diversity of the crops that feed Africa.

View

 

Gurung A, Haverkort JW, Drost S, Norder B, Westerweel J, Poelma C (2016). Ultrasound image velocimetry for rheological measurements. Measurement Science and Technology 27(9):09400.
Crossref

 

Hadjichristodoulou A (1985). The stability of the number of tillers of barley varieties and its relation with consistency of performance under semi-arid conditions. Euphytica 34(3):641-649.
Crossref

 

Jaetzold R, Hornetz B, Shisanyi C, Schmidt H (2012). Farm management handbook of Kenya Vol I-IV (Western Central Eastern Nyzana Southern Rift Valley Northern Rift Valley Coast). Nairobi: Government Printers.

 

Kebede D, Dagnachew L, Megersa D, Chemeda B, Girma M, Geleta G, Gudeta B (2019). Genotype by environment interaction and grain yield stability of Ethiopian black seeded finger millet genotypes. African Crop Science Journal 27(2):281-294.
Crossref

 

Manyasa EO (2013). A study of the diversity, adaptation and gene effects for blast resistance and yield traits in East African finger millet (Eleusine coracana (L.) Gaertn) landraces (Doctoral dissertation).

 

Mitaru BN, Karuga JT, Munene C (1993). Finger Millet Production and Utilization in Kenya. In: K.W., Riley, S.C Gupta, A., Seetharam and J.N., Mushonga (Eds), Advances in Small Millets. New Delhi, Oxford and IBH Co. PVT Ltd. pp. 247-254

 

Mgonja MA, Lenne JM, Manyasa E, Sreenivasaprasad S (2007). Finger millet blast management in East Africa Creating opportunities for improving production and utilization of finger millet. 
Crossref

 

Mgonja MA, Lenne JM, Manyasa E, Sreenivasaprasad S (2017). Finger millet blast management in East Africa Creating opportunities for improving production and utilization of finger millet. 
Crossref

 

Molla A, Beuving J, Ruben R (2020). Risk aversion, cooperative membership, and path dependences of smallholder farmers in Ethiopia. Review of Development Economics 24(1):167-187.
Crossref

 

Oduori C, Kanyenji B (2007). Finger millet in Kenya. Importance, Advances in Rand D, challenges and opportunities for improved production and profitability. Finger Millet Blast Management in East Africa: Creating opportunities for improving production and utilization of finger millet, Proceedings of the First International Finger Millet Stakeholder Workshop, Nairobi, Kenya pp. 10-22.

 

Ojulong H, Letayo E, Sakwera L, Mgonja F, Sheunda P, Kibuka J, Manyasa EO (2017). Participatory Variety Selection for enhanced promotion and adoption of improved finger millet varieties: a case for Singida and Iramba Districts in Central Tanzania. African Journal of Rural Development 2(1):77-93.

 

Orlando F, Alali S, Vaglia V, Pagliarino E, Bacenetti J, Bocchi S (2020). Participatory approach for developing knowledge on organic rice farming: Management strategies and productive performance. Agricultural Systems 178:102739.
Crossref

 

Owere L, Tongoona P, Derera J, Wanyera N (2014). Farmers' Perceptions of Finger Millet Production Constraints, Varietal Preferences and Their Implications to Finger Millet Breeding in Uganda. Journal of Agricultural Science 6(12):126.
Crossref

 

Owere L, Tongoona P, Derera J, Wanyera N (2016). Combining Ability Analysis of Blast Disease Resistance and Agronomic Traits in Finger Millet [Eleusinecoracana(L.) Gaertn]. Journal of Agricultural Science 8(11):138-146.
Crossref

 

Panwar AS, Shamim M, Babu S, Ravishankar N, Prusty AK, Alam NM, Pasha MD (2019). Enhancement in Productivity, Nutrients Use Efficiency, and Economics of Rice-Wheat Cropping Systems in India through Farmer's Participatory Approach. Sustainability 11(1):122.
Crossref

 

Paris T, Manzanilla DOR, Vergara GV, Ismail AM, Pandey S, Labios RV, Siliphouthone I (2011). Submergence risks and farmers' preferences: implications for breeding Sub1 rice in Southeast Asia. Agricultural Systems 104(4):335-347.
Crossref

 

Pudasaini N, Sthapit SR, Gauchan D, Bhandari B, Joshi BK, Sthapit BR (2016). Baseline Survey Report: I. Jungu, Dolakha. Integrating traditional crop genetic diversity into technology: using a biodiversity portfolio approach to buffer against unpredictable environmental change in the Nepal Himalayas.

 

Pungulani L, Kadyampakeni D, Nsapato L, Kachapila M (2012). Selection of high yielding and farmers' preferred genotypes of bambara nut (Vigna subterranea (L.) Verdc) in Malawi.
Crossref

 

Ravikumar RL, Seetharam A (1993). Character Association in segregating populations of finger millet (Eleusine coracana) in blast-epidemic regions. Indian Journal of Agricultural Sciences 63(2):96-99.

 

Sadreddine BEJI (2016). Yield and quality of dual-purpose barley and triticale in a semi-arid environment in Tunisia. African Journal of Agricultural Research 11(30):2730-2735.
Crossref

 

Sibiya J, Tongoona P, Derera J, Makanda I (2013). Farmers' desired traits and selection criteria for maize varieties and their implications for maize breeding: A case study from KwaZulu-Natal Province, South Africa. Journal of Agriculture and Rural Development in the Tropics and Subtropics 114(1):39-49.

 

Singh J, Lal C, Kumar D, Khippal A, Kumar L, Kumar V, Sharma I (2016). Widening the Genetic Base of Indian Barley through the Use of Exotics. International Journal of Tropical Agriculture 34(1):85-94.

 

Singh P, Raghuvanshi RS (2012). Finger millet for food and nutritional security. African Journal of Food Science 6(4):77-84.
Crossref

 

Sissoko M, Smale M, Castiaux A, Theriault V (2019). Adoption of New Sorghum Varieties in Mali through a Participatory Approach. Sustainability 11(17):4780.
Crossref

 

Takan JP, Chipili J, Muthumeenakshi S, Talbot NJ, Manyasa EO, Bandyopadhyay R, Brown AE (2012). Magnaporthe oryzae populations adapted to finger millet and rice exhibit distinctive patterns of genetic diversity, sexuality and host interaction. Molecular biotechnology 50(2):145-158.
Crossref

 

Takan JP (2004). Finger millet blast pathogen diversity and management in East Africa: A summary of project activities and outputs. International Sorghum and Millets Newsletter 45:66-69.

 

Tamene L (2016). Participatory Yield Assessment of Climbing and Bush Beans under Different Management Options in Malawi.

 

Tarekegne W, Mekbib F, Dessalegn Y (2019). Performance and Participatory Variety Evaluation of Finger Millet [Eleusine coracana (L.) Gaertn] Varieties in West Gojam Zone, Northwest Ethiopia. East African Journal of Sciences 13(1):27-38.

 

Upadhyaya HD, Dwivedi SL, Singh S, Sahrawat KL, Singh SK (2016). Genetic variation and postflowering drought effects on seed iron and zinc in ICRISAT sorghum mini core collection. Crop Science 56(1):374-383.
Crossref

 

Van Frank G, Riviere P, Goldringer I (2018). A participatory approach to breeding for diverse and adapted wheat mixtures on farm. In Symposium on Breeding for Diversification.

 

Vom Brocke K, Kondombo CP, Guillet M, Kaboré R, Sidibé A, Temple L, Trouche G (2020). Impact of participatory sorghum breeding in Burkina Faso. Agricultural Systems 180:102775.
Crossref

 

Watson D (2019). Adaptive Crop Management. Sustainable Solutions for Food Security: Combating Climate Change by Adaptation 191 p.
Crossref

 

Witcombe JR, Joshi KD, Gyawali S, Musa AM, Johansen C, Virk DS, Sthapit BR (2005). Participatory plant breeding is better described as highly client-oriented plant breeding. I. Four indicators of client-orientation in plant breeding. Experimental Agriculture 41:299-319.
Crossref

 

Yadavendra JP, Gadade O, Dash S (2017). Scaling Niche Specific Common Beans (Phaseolus vulgaris L.) Varieties Based on Participatory Varietal Selection in Western Kenya. International Journal of Pure of Applied Biosciences 5:1161-1169.
Crossref

 

Yamane T (1973). Statistics: An introduction analysis. Harper and Row.

 




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