Difference between revisions of "WAVES0505"

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(Africa RISING West Africa Virtual Exchange Seminar (WAVES)5 May 2021Virtual via Ms TEAMS)
(Africa RISING West Africa Virtual Exchange Seminar (WAVES)5 May 2021Virtual via Ms TEAMS)
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Onion production faces constraints as indicated in the table below.
  
CONSTRAINTS CAUSES
 
Abiotic Drought in humid season
 
High moisture in humid season (mostly exotics)
 
Post-harvest Onion is perishable during storage
 
Genetic Low diversity
 
Low adaptation
 
Technology transfer Weak national extension system
 
No perennial water resources, animal stray
 
Capacity building Insufficient trained farmers, seed enterprises, technicians and students
 
 
 
 +
----
 +
'''Objective'''
 +
----
 +
 +
To identify adaptable onion genotype for a sustainable production in Africa RISING project intervention zones in northern Ghana and southern Mali.
 +
 +
----
 +
'''Materials and Method '''
 +
----
 +
 +
*Sets of 8onion lines from the WorldVeg onion collection and one commercial check were evaluated during the cool and dry seasons from September to March for three years from 2018, 2019 and 2020.
 +
*The trials with 3 replications were carried out on technology parks and on farm fields under the joint management of farmers and researchers.
 +
*The trial sites were Upper East and Northern regions of Ghana; and Sudan Savannah zones of Mali (Bougouni and Koutiala).
 +
*Plot dimensions were 2m x 2m with planting densities of 20cm and 15cm between and within roles respectively.
 +
*Onion bulb weight was recorded for each plot after harvest
 +
*Separate analysis of variances was performed for each location and season in a complete randomize design.
 +
*Combined analysis of variances (sites x year x genotypes) was made to determine the most stable varieties  using the following stability analysis models:
 +
- AMMI bi-plot
 +
- GGE bi-plot
 +
- Line superiority (Lin and Binns, 1988); and
 +
- Eco valence stability coefficient (Wricke, 1962)
 +
 +
 +
----
 +
'''Results and Discussion '''
 +
----
 +
 +
'''G & E INTERACTION FOR YIELD PERFORMANCE'''
 +
 +
The presentation shows the '''G AND E interaction (AMMI)''' for yield performance t/h-1of onion varieties over years and locations in Ghana and Mali – 2018-2020.
 +
Onion genotypes AVON 1073 and AVON 1074 were old onion lines in Mali in 2012. They are the most performing varieties at the moment. The Check variety is included; it was commercialized in Ghana and Mali.
 +
The combined analysis for variance show that whether by location or variety, the interaction was very significant.
 +
From the general Mean, it is clear that the top three varieties were the most eaten onion varieties with yield more that 30t/h and highly above the average yield of 25.6 t/h. We identified three varieties that were over yielded the old varieties in Mali, but were the varieties used in the ECOWAS countries in 2012.
 +
 +
 +
'''STABILITY ANALYSIS'''
 +
 +
The first model used was the '''AMMI bi-plot analysis''' for onion yield. The outcome of this analysis showed that the most stable lines from the model were the AVON 1325, AVON 1323 and AVON 1317. Only AVON 1325 with yield 13.68 t/h had above average yield (25.61 t/h).
 +
The second model was the GGE: Genotype + G x E interaction (GGE) bi-plot. This analysis shows two mega environments. The Mega Environment 1 has 2 environments in Koutiala, Mali. The Mega Environment 2 on the other hand has six environments in Ghana and Bougouni, Mali. These environments in Ghana and Bougouni, Mali, are quite similar and homogeneous.
 +
Genotype AVON 1308, is the highest yielding and was the best performing variety across locations and years in the Mega Environment 1 including Ghana and Bougouni; while AVON 1310 was stable in Ghana specifically.
 +
AVON 1314 was the winning variety in the Mega Environment 2, in Koutiala over two years.
 +
 +
'''WRICKE’S ECOVALENCE STABILITY COEFFICIENT TEST'''
 +
The ecovalence stability test shows that the wricke ecovalence stability, the higher the stability of the lines. Based on this statement, four genotypes including Check and AVON 1317 were the most stable varieties because they have the smallest stability coefficient.
 +
Two genotypes, AVON 1310 and AVON 1325 were best because they were above average yield (25.61 t/h).
 +
 +
'''LIN AND BINNS SUPERIORITY MEASURE OF GENOTYPE PERFORMANCE''' 
 +
Using this model, the analysis shows some coefficient - the smaller the coefficient, the higher the stability of the lines. According this this model, we have three varieties: AVON 1310, AVON 1308 and AVON1325 which were the most stable varieties.
 +
These genotypes also produced bulb yield, higher than the average mean. This was quite interesting in terms of selection for stability.
  
  

Revision as of 11:58, 10 August 2021

Africa RISING West Africa Virtual Exchange Seminar (WAVES)
5 May 2021
Virtual via Ms TEAMS

Meeting video recording: https://cgiar-my.sharepoint.com/:v:/r/personal/j_odhong_cgiar_org/Documents/Recordings/Monthly%20Seminars%20-%20Africa%20RISING%20ESA%20Project-20210506_120317-Meeting%20Recording.mp4?csf=1&web=1&e=U5pD5h

Attendance

  1. A. Ayantunde – ILRI
  2. A. Berdjour – IITA
  3. A. Folorunso – ICRISAT
  4. A.R. Nurudeen – IITA
  5. B. Boyubie – IITA
  6. B. Kotu – IITA
  7. B. Nebie – ICRISAT
  8. B. Traore – ICRISAT
  9. B. Zemadim – ICRISAT
  10. D. Agathe – ICRISAT
  11. F. Avornyo – CSIR-ARI
  12. F. Badolo – ICRISAT
  13. F. Dokurugu – IITA
  14. F. Gundula – IITA
  15. F. Kizito – IITA
  16. F. Muthoni – IITA
  17. I. H.Zeledon – IITA
  18. I. Mahama – IITA
  19. J. B. Tignegre – WorldVeg
  20. J. Nzungize – ICRISAT
  21. J. Odhong – IITA
  22. K. Jimah – IITA
  23. K. Sanogo – ICRISAT
  24. K. Traore – ICRISAT
  25. M. Diancounba – ICRISAT
  26. M. Magassa – ICRISAT
  27. M. Sidibe – ICRISAT
  28. O. Cofie – IWMI
  29. P. Zaato – WorldVeg
  30. R. Tabo – ICRISAT
  31. S. A. Adebayo – IITA
  32. S. Bedi – IITA
  33. T. Ansah – UDS
  34. T. Minh – IWMI
  35. W. O. Duah – IITA



Agenda

  • Updates from partners
  • Presentation on ‘Bulb yield stability study of onions lines in Ghana and Mali’ by Jean Baptiste Tignegre



Updates / Introductory remarks


  • Zeledon – from the Africa RISING programmatic level, nothing much is happening recently, except for the PCT members who were busy with the drafting of the pre-concept notes for the new ONE CGIAR initiative. This was submitted on 16 April 2021. Ten days later, we got initial feedback from external reviewers which have been addressed and resubmitted. We were told that this week we would informed of the way forward. I have not yet heard anything from the CGIAR office. I was not unhappy about it because we are currently focusing on finalizing the Africa RISING’s 6 months report to USAID; I have been quite busy with it. I hope Fred can submit later today. We all know the process of this report – after my review it will be submitted to the steering committee for their comments and approval. When the steering committee’s comments are addressed, it will be submitted to the professional editor. Jonathan will then do the final formatting, and it will be submitted to USAID.
  • Kizito – Thank you Irmgard for the agreed insights. I’m sure many of us in this virtual meeting have also in one way or another been involved in different independent design teams around the ONE CGIAR. It’s a crazy dust, and I hope it will settle over time. We thank partners who were able to submit their reports on time. I would like to entreat you all on the aspects on the emphasis around what you promised on the SIAF. We had proposed during the drafting of our work plans that we would have:

- a tabular metrics that would show how data would be collected - the kind of metrics you would use to measure the indicators – before and after the indicators But some partners present their reports without necessarily filing in the data, yet, this is embedded in all our work plans. I kindly request that going forward, partners present their reports with the SIAF being taken care of. This is emphasized because it’s a tool that allows you to see the nature of the progress of your work in a more wholistic manner beyond just looking at only yield of productivity. It helps you to see how you are addressing other issues around gender, human nutrition, innovative capacities of farmers to experiment, etc. Let’s see this as positive. If there is any way we can support you in populating the tables based on the data, we have the capacity to do so. Let’s understand that it is something that’s really needed. It will appear awkward if there is inconsistency – some partners have it, and other do not. With regards to that, I’m tempted to debate if this should be included in the report. I hope this will be well noted. Does Birhanu have any addition to that?

  • Zemadim – I think your emphasis is on point. Hopefully, all partners will come to understand this; and we believe in their next reports the information will be included.
  • Kizito – We have been deliberating internally on the date for the Virtual Planning Meeting for West Africa. Thanks to Jonathan, we have a tentative agenda planned out. It will be shared with you during the week. You could have a look at it and submit your comments. The scheduled date is 26 – 27 May 2021. We kindly request that you flag the date in your calendars. We will share the agenda with you.



Presentation from Jean Baptiste Bulb yield stability study of onion lines over locations and years in Ghana and Mali


The presentation is on the results of trials implemented under Africa RISING project on onions. This is one of the 3 – 4 vegetables species being worked on as vegetable trials. Background Onion plays a key role as source of nutrients and income for people in sub-Saharan Africa but few high-yielding varieties are available to farmers. World top producers of onions are china, India, USA, Iran and Russia; world top exporters are Netherlands, India, Mexico, China, Egypt, USA, and Spain; and world top importers are USA, Germany, UK, Russia, Malaysia, Japan, etc. The production, growing areas and yield of onions vary according to countries and how intensive the production system is. The presentation reveals the onion mean yield (t/h) globally from 2005 – 2012. The mean yield of onion is very high above 40t/h for countries like China, Netherlands, Spain and USA; whereas yield is about 20t/h for countries like Mali, Senegal, Niger in West Africa. This shows that the difference is very high. The presentation also depicts imported and exported onions in metric tons in different countries from 2012 – 2016. It is to be noted that India is the top exporter of onions globally, followed by Netherlands and China. Looking at some West African countries such as Niger and Mali, the exportation of onion is very low as compared to the other countries. Importation of onion is even higher in Mali than the exportation.



Key challenges to onion production


Onion production faces constraints as indicated in the table below.



Objective


To identify adaptable onion genotype for a sustainable production in Africa RISING project intervention zones in northern Ghana and southern Mali.


Materials and Method


  • Sets of 8onion lines from the WorldVeg onion collection and one commercial check were evaluated during the cool and dry seasons from September to March for three years from 2018, 2019 and 2020.
  • The trials with 3 replications were carried out on technology parks and on farm fields under the joint management of farmers and researchers.
  • The trial sites were Upper East and Northern regions of Ghana; and Sudan Savannah zones of Mali (Bougouni and Koutiala).
  • Plot dimensions were 2m x 2m with planting densities of 20cm and 15cm between and within roles respectively.
  • Onion bulb weight was recorded for each plot after harvest
  • Separate analysis of variances was performed for each location and season in a complete randomize design.
  • Combined analysis of variances (sites x year x genotypes) was made to determine the most stable varieties using the following stability analysis models:

- AMMI bi-plot - GGE bi-plot - Line superiority (Lin and Binns, 1988); and - Eco valence stability coefficient (Wricke, 1962)



Results and Discussion


G & E INTERACTION FOR YIELD PERFORMANCE

The presentation shows the G AND E interaction (AMMI) for yield performance t/h-1of onion varieties over years and locations in Ghana and Mali – 2018-2020. Onion genotypes AVON 1073 and AVON 1074 were old onion lines in Mali in 2012. They are the most performing varieties at the moment. The Check variety is included; it was commercialized in Ghana and Mali. The combined analysis for variance show that whether by location or variety, the interaction was very significant. From the general Mean, it is clear that the top three varieties were the most eaten onion varieties with yield more that 30t/h and highly above the average yield of 25.6 t/h. We identified three varieties that were over yielded the old varieties in Mali, but were the varieties used in the ECOWAS countries in 2012.


STABILITY ANALYSIS

The first model used was the AMMI bi-plot analysis for onion yield. The outcome of this analysis showed that the most stable lines from the model were the AVON 1325, AVON 1323 and AVON 1317. Only AVON 1325 with yield 13.68 t/h had above average yield (25.61 t/h). The second model was the GGE: Genotype + G x E interaction (GGE) bi-plot. This analysis shows two mega environments. The Mega Environment 1 has 2 environments in Koutiala, Mali. The Mega Environment 2 on the other hand has six environments in Ghana and Bougouni, Mali. These environments in Ghana and Bougouni, Mali, are quite similar and homogeneous. Genotype AVON 1308, is the highest yielding and was the best performing variety across locations and years in the Mega Environment 1 including Ghana and Bougouni; while AVON 1310 was stable in Ghana specifically. AVON 1314 was the winning variety in the Mega Environment 2, in Koutiala over two years.

WRICKE’S ECOVALENCE STABILITY COEFFICIENT TEST The ecovalence stability test shows that the wricke ecovalence stability, the higher the stability of the lines. Based on this statement, four genotypes including Check and AVON 1317 were the most stable varieties because they have the smallest stability coefficient. Two genotypes, AVON 1310 and AVON 1325 were best because they were above average yield (25.61 t/h).

LIN AND BINNS SUPERIORITY MEASURE OF GENOTYPE PERFORMANCE Using this model, the analysis shows some coefficient - the smaller the coefficient, the higher the stability of the lines. According this this model, we have three varieties: AVON 1310, AVON 1308 and AVON1325 which were the most stable varieties. These genotypes also produced bulb yield, higher than the average mean. This was quite interesting in terms of selection for stability.



Bulb yield stability of onion lines in Ghana and Mali - Jean Baptiste Tignegre, WorldVeg Center


  • Download presentation from link in the title above.