Adaptation and Agronomic Performance of Domesticated Moroccan Oat (Avena magna ssp. domestica) Lines under Subsistence Farming Conditions at Multiple Locations in Morocco

Abstract

Common hexaploid oat (Avena sativa L.) is an important global cereal crop. A Moroccan tetraploid sister species, A. magna Murphy et Terrel, was exclusively a wild species until recently. The goal of domestication was to exploit its superior groat-protein content and climatic tolerances. We set up replicated trials of 41 domesticated A. magna lines on eight Moroccan farms during the 2017–2018 and 2018–2019 growing seasons. Twenty traits were measured and analyses of variance detected significant differences among lines. The highest grain yield was at Berrechid in 2017–2018 (63.56 q/ha), with an average annual yield across sites of 43.50 q/ha, the site factor explaining 82% and the genotype-environment interaction explaining 15% of the variability. In the second year, El Kebab recorded the highest yield at 20.03 q/ha over the annual average of 14.78 q/ha. In this second year, the site factor was highly significant, explaining 42.25% of the variation, with the genotype-environment interaction explaining 26.61% of the variability. An additional main effect and multiplicative interaction analysis of the eight two-year trials identified several accessions with good yield stability. Twelve lines exhibited a ASVs ≤ 1.50, with five accessions (A34, A40, A23, A05, A04) exceeding the overall average yield of 29.53 and A34 having the greatest mean grain yield and stability. The versatility and stability of A. magna can provide a sustainable protein source and an economic resource for farmers seeking products that are resilient to climatic instability.

1. Introduction

The oat genus Avena L. (x = 7) includes the seventh most important cereal worldwide: common or white oat (A. sativa L. 2n = 6x = 42; AACCDD subgenomes). Other domesticated taxa include red oat A. byzantina C. Koch (AACCDD), a fodder oat grown in mild winter-production conditions; Ethiopian endemic oat A. abyssinica Hochst (AABB); the diploid lopsided or sand oat complex (A. strigosa Schreb. AsAs); and the recently domesticated A. magna Murphy et Terrel ssp. domestica Ladizinsky [1]. The oat genus’ center of origin is the Maghreb and southern Iberia, though the most likely tetraploid progenitor of the hexaploid species — A. insularis Ladizinsky (CCDD) — is currently found only in Tunisia and Sicily in the central Mediterranean [2,3]. The hexaploid cultivated forms appear to have been domesticated from weedy A. sterilis L. on at least two occasions in the ancient Near East [4,5], with a secondary center of diversification of the hulless or naked oat in Northwest China and Mongolia [6].

2. Materials and Methods

2.1. Plant Materials

Avena magna ssp. domestica lines in this study were developed from a single Ba13–13 × wild #169 recombinant inbred line (RIL) [7] expressing the wild-type growth habit and resistance to field races of crown rust (Puccinia coronata) in Baton Rouge, LA [9]. Seed from this line was subjected to six cycles of selfing and selection for improvements in agronomic and seed domestication, resulting in six foundational lines displaying various combinations of traits for domestication and cultivation including awn reduction, shattering resistance, semi-dwarfism, lodging resistance, erect growth habit, resistance to seed dormancy, phototropism, reduced groat length, and ease of dehulling [9]. A set of 114 RILs, including the 41 experimental lines in this study (Table 1), were produced by intercrossing the foundational lines as instructed by a virtual pedigree produced using a genotype/phenotype model with the JMP Genomics software package (SAS Institute Cary, Cary, NC, USA). The 41 lines were compared to the internal control ‘Avery’ (A40), a commercial A. magna ssp. domestica variety produced by General Mills in 2013 [9] and released commercially in Morocco late 2019.

2.2. Experimental Sites

Experimental site locations are mapped in Figure 1, shown photographically in Figure 2, and described in Table 2. Experimental trials of 2017–2018 were conducted at four locations: a commercial potato production farm 14 km southeast of Berrechid (central Atlantic coastal plain); a modern production farm 15 km south of Meknes; a subsistence farm in Lahri (low-altitude, Khenifra region); and a subsistence farm 4 km southwest of El Kebab (high-altitude, Khenifra region). Trials were sown at Berrechid on 6 December 2017; at Lahri and El Kebab on 8 December; and at Meknes on 27 December. Experimental trials of 2018–2019 were conducted in the fall–winter–spring growing season on an organic production farm 16 km west of Tiflet (northern Atlantic coastal plain); at the Royal Agricultural Domain Ain Hamra Farm in Seba Ayoun 20 km east of Meknes (north-central interior lowlands); at the El Kebab farm; and at a cooperative subsistence farm 18 km east of Youssoufia in Bouchane (semiarid Phosphate Plateau) with sowing dates of November 27, 28, 29, and 30, respectively. Locations were purposely selected to test the adaptational range of A. magna as a grain crop and, consequently, included a range of technological sophistication from commercial to subsistence; climate zones ranging from warm to cool and dry to humid; and traditional cultural contexts including both Amazigh (Lahri, El Kebab) and Arab (i.e., Bouchane).

2.3. Experimental Design

The experimental set-up at the 2017–2018 locations was in randomized complete blocks (RCB) with two repetitions. Planting was done in paired three-meter rows, spaced 20 cm apart, with a seeding rate of 5 g per paired lines. The spacing between lines was 60 cm. Each site was characterized by peculiarities or variations in the planting plan in accordance with terrain constraints. The experiments in 2018–2019 were set up in randomized complete blocks (RCB) with 1.83 m rows in three blocks at Meknes and Tiflet; 1 m rows with three blocks at El Kebab; and 2 m rows with three blocks at Bouchane.

2.4. Measurements and Observations

Agronomic and morpho-physiological characteristics were measured to estimate yield potential through grain and straw productivity; yield stability across environments; tolerance to the three main oat diseases (crown rust (CR), barley yellow dwarf virus (BYDV), powdery mildew); and to determine the most optimally and stably productive lines in terms of yield. Measurements were taken at three different growth stages in order to carry out the disease and agro-morphological measurements.

  • GYH: grain yield (q/ha)
  • DYH: dry matter yield (q/ha).
  • Pgrains: grain weight per plant
  • TSW: thousand-seed weight

2.5. Statistical Analyses

The collected data were used to carry out statistical analyses. We assessed intra-locality variability by comparing the lines with each other at each agro-climatic site. On the one hand, the measured parameters were the subject of a descriptive analysis and an analysis of variance (ANOVA) with two sources of variation (lines and blocks). Before any analysis, the normality of the variables was tested for each indicator through a Kolmogorov–Smirnov (KS) test at a significance level of 5%. If the null hypothesis was rejected, a test to compare the Student-Newman-Keuls means (SNK) was used to distinguish the different homogeneous groups. For experimental sites where the variables associated with productivity (grain yield, dry matter yield, harvest index) presented significant differences due to the effect of the genotype, we carried out a principal component analysis (PCA).

  • SSA2: sum of squares of the interaction component of the second axis of the PCA
  • IPCA1: ACP score of the interaction first axis component
  • IPCA2: score of the interaction second axis component.

3. Results and Discussion

3.1. Intra-Locality Analyses

3.1.1. Assessments of Disease Tolerances

The observation of diseases was carried out in the middle of the cycle for all crops, specifically on the 92nd, 111th, 118th, and 156th days after sowing at the Meknes, Berrechid, Lahri, and El Kebab sites in 2017–2018, respectively. The three most important diseases attacking oats in Morocco are crown rust (Puccinia coronata f. sp. avenae), BYDV, and powdery mildew (Blumeria graminis f. sp. avenae). Crown rust developed by the middle of the cycle at the Berrechid site but was not observed at the other locations until very late in the growth cycle. We therefore assessed crown rust severity only at Berrechid via visual scoring using the modified Cobb scale [17]. Following this we performed a two-factor ANOVA, with the summary table showing only significant differences presented in Table 3. Powdery mildew was only observed at Berrechid and was therefore not scored. As for BYDV, it was observed at all sites, though infestations within a given site did not appear to be uniform.

3.1.2. Analyses of Agro-Morphological Traits

Significant agro-morphological effects at the eight environments are highlighted via descriptive statistics provided in Table 4 and two-way ANOVA Table 5. Variables studied included the measured parameters, the calculated parameters, the thousand-seed weight (TSW) and the harvest index (HI).

3.1.3. Analyses of Productivity Traits

To assess the productivity of the A. magna oat lines, we analyzed the GYH, DYH, and HI of the eight experimental trials. Descriptive statistics for these productivity traits appear in Table 6 and the rankings of the 41 lines in Table 7.

3.2. Interlocality Analyses

3.2.1. Three-Factor ANOVA’s and CV’s

Descriptive statistics for the agro-morphological and productivity traits showed different degrees of variation between the parameters (data not presented). BYDV susceptibility rate varied between 0 and 100% with an average of 20% and had the highest variability coefficient (129.56%). The RW presented a high coefficient of variation (119%). The GYH, DYH, DYP, GYP, NGP, and NFT all showed variability ranging from 60–119%. The GYH varied between 0.34 and 164.80 q/ha with a mean of 24.38 q/ha. The thousand-seed weight (TSW) had the lowest CV (27.46%), ranging from 12.50 to 58.49 g with a mean of 35.19 g.

3.2.2. Correlation Matrix

The Pearson correlation matrix values among variables are displayed in Table 10. Significant values are highlighted in bold type. The highest positive correlations of paired variables were observed between DYP and GYP (R = 0.97) and between NGP and GYP (R = 0.93). Other significant positive correlations were observed between GYH and DYH (R = 0.65) and between DYP and RW (R = 0.60). There were also significant correlations with R-values of 0.54 between DYP and GYP; 0.52 between DYP and SW; and 0.51 between DYH and VGV, SW, and DYP (Table 10). The low positive correlations ranged from 0.49 to 0.40 and were observed between NGP and GYP (R = 0.47); NGP and GYH (R = 0.45); TSW and PH (R = 0.41); and HI and GYP (R = 0.40). The lowest correlations were measured between NFT and RL (R = 0.36); NFT and TSW (R = 0.36); NFT and GYP (R = 0.35); NGP and DYP (R = 0.33); and GYH and DYP (R = 0.31). In addition, there were two negative correlations between parameters: the first was between HI and DYH (R = −0.43) and the second between GYP and BYDV sensitivity (R = −0.34).

3.2.3. Principal Component Analysis

The principal component analyses (PCA) were conducted at three sites (Table 2): Berrechid on the relatively humid central Atlantic Coastal Plain; Bouchane at a semiarid location on the Central Plateau; and El Kebab representing a relatively high-altitude environment in the Middle Atlas Mountains. In addition, we carried out a combined-site PCA.

3.2.4. AMMI Analysis

The objective of the AMMI analysis was to accurately characterize the genotype and environmental effects on the productivity and stability of the A. magna germplasm across environments. The combined analysis of variance for grain yield of the 41 Avena magna lines across the eight environments is in Table 12. The effects of the genotypes, the environments, and their interaction were highly significant (p ≤ 0.0001) on the total variance. The environment’s main effect accounted for 82.89%, whereas genotype and G × E interaction effects accounted for 1.81% and 15.30% of the total variation, respectively.

Author Contributions

Conceptualization, O.B., E.N.J., and E.W.J.; methodology, O.B., E.W.J., S.S., T.E., A.E.M., I.A.H., I.E.F., L.S.K.; formal analysis, O.B., E.W.J., T.E., A.E.M., I.A.H., I.E.F., L.S.K., R.L., S.S.; execution of research, O.B., E.N.J., E.W.J., T.E., A.E.M., I.A.H., I.E.F., L.S.K., T.A., R.L., K.K., M.N., W.R., G.G., J.T., L.K.Y., D.E.J., S.S.; writing — original draft preparation, E.N.J., O.B., A.E.M., I.E.F., L.S.K., G.G., J.T., L.K.Y.; writing — review and editing, E.N.J., O.B., T.E., L.K.Y.; visualization, E.N.J., O.B., T.E., A.E.M., I.E.F., L.S.K.; supervision, O.B., E.N.J., E.W.J., M.N., T.A., W.R., D.E.J., S.S.; project administration, O.B., E.W.J., M.N., W.R., P.J.M., E.N.J.; funding acquisition, O.B., E.W.J., E.N.J., M.N., W.R., P.J.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by General Mills, Inc., with travel and other logistical support in Morocco provided by The Context Network, LLC; Brigham Young University; 25:2 Solutions, LLC; and the Institut Agronomique et Vétérinaire-Hassan II.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Acknowledgments

We are grateful for Paul Richter’s help with crossing of A. magna lines. We are also indebted to the vision of Gideon Ladizinsky of the Hebrew University of Jerusalem, who inspired us to initially pursue the work that led to these first published field trials of domesticated A. magna and to whose legacy this work should be attributed.

Conflicts of Interest

Although the research was supported with a grant from General Mills, Inc., they were not involved in the design or interpretation of the field data. They did review the manuscript prior to submission to ensure that the description of A. magna line domestication and breeding was represented accurately, as described in the patent application of Jackson [9]. All other interested parties were involved in all aspects of experimental design, execution, analyses of data, and manuscript preparation.

References

  1. Ladizinsky, G. Domestication via hybridization of the wild tetraploid oats Avena magna and A. murphyi. Theor. Appl. Genet. 1995, 91, 639–646. [Google Scholar] [CrossRef] [PubMed]
  2. Ladizinsky, G. A new species of Avena from Sicily, possibly the tetraploid progenitor of hexaploid oats. Genet. Resour. Crop Evol. 1998, 45, 263–269. [Google Scholar] [CrossRef]
  3. Jellen, E.N.; Ladizinsky, G. Giemsa C-banding in Avena insularis Ladizinsky. Genet. Resour. Crop Evol. 2000, 47, 227–230. [Google Scholar] [CrossRef]
  4. Zhou, X.; Jellen, E.N.; Murphy, J.P. Progenitor germplasm of domesticated hexaploid oat. Crop Sci. 1999, 39, 1208–1214. [Google Scholar] [CrossRef]
  5. Jellen, E.N.; Beard, J. Geographical distribution of a chromosome 7C and 17 intergenomic translocation in cultivated oat. Crop Sci. 2000, 40, 256–263. [Google Scholar] [CrossRef]
  6. Loskutov, I.G. On evolutionary pathways of Avena species. Genet. Resour. Crop Evol. 2008, 55, 211–220. [Google Scholar] [CrossRef]
  7. Oliver, R.E.; Jellen, E.N.; Ladizinsky, G.; Korol, A.B.; Kilian, A.; Beard, J.L.; Dumlupinar, Z.; Wisniewski-Morehead, N.H.; Svedin, E.; Coon, M.; et al. New Diversity Arrays Technology (DArT) markers for tetraploid oat (Avena magna Murphy et Terrell) provide the first complete oat linkage map with markers linked to domestication genes from hexaploid A. sativa L. Theor. Appl. Genet. 2011, 123, 1159–1171. [Google Scholar] [CrossRef] [PubMed]
  8. Ladizinsky, G. Development of protein rich tetraploid oat–current state and prospects. In Proceedings of the American Oat Workers Conference Abstracts, Ottawa, ON, Canada, 13–16 July 2014; Available online: http://aowc.ca/AOWC2014_presentations.html (accessed on 20 February 2020).
  9. Jackson, E.W. High Protein Oat Species. W.I.P.O. Patent Application WO 2017/070104 A1, 27 April 2017. [Google Scholar]
  10. Schilling, J.; Freier, K.P.; Hertig, E.; Scheffran, J. Climate change, vulnerability and adaptation in North Africa with focus on Morocco. Agric. Ecosyst. Environ. 2012, 156, 12–26. [Google Scholar] [CrossRef]
  11. Barouaca, H. Situation of malnutrition in Morocco: Results after 40 years of struggle. Nutr. Clin. Diet. Hosp. 2012, 32 (Suppl. 2), 76–81. [Google Scholar]
  12. Zobel, R.W.; Wright, M.J.; Gauch, H.G. Statistical analysis of a yield trial. Agron. J. 1998, 80, 388–393. [Google Scholar] [CrossRef]
  13. Purchase, J.L. Parametric Analysis to Describe Genotype x Environment Interaction and Yield Stability in Winter Wheat. Ph.D. Thesis, University of the Orange Free State, Bloemfontein, South Africa, 1997. [Google Scholar]
  14. Wardofa, G.A.; Mohammed, H.; Asnake, D.; Alemu, T. Genotype X Environment Interaction and Yield Stability of Bread Wheat Genotypes in central Ethiopia. J. Plant Breed. Genet. 2019, 7, 87–94. [Google Scholar] [CrossRef]
  15. Gauch, H.G.; Piepho, H.-P.; Annicchiarico, P. Statistical Analysis of Yield Trials by AMMI and GGE: Further Considerations. Crop. Sci. 2008, 48, 866–889. [Google Scholar] [CrossRef]
  16. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2013; Available online: http://www.R-project.org/ (accessed on 25 February 2021).
  17. Peterson, R.F.; Campbell, A.B.; Hannah, A.E. A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Can. J. Res. 2011, 26, 496–500. [Google Scholar] [CrossRef]
  18. Al Faïz, C.; Saïdi, S.; Jaritz, G. Avoine fourragère (Avena sativa L.). In Production et Utilisation des Cultures Fourragères au Maroc; Jaritz, G., Bounejmate, M., Eds.; INRA: Rabat, Morocco, 1997; pp. 209–224. [Google Scholar]
  19. El Yamani, M.; Hill, J.H. Aphid vectors of barley yellow dwarf virus in west-central Morocco. J. Phytopath. 1991, 133, 105–111. [Google Scholar] [CrossRef]
  20. Adugna, W.; Labuschagne, M.T. Genotype-environment interactions and phenotypic stability analyses of linseed in Ethiopia. Plant Breed. 2002, 121, 66–71. [Google Scholar] [CrossRef]
  21. Anderson, C.H.; Read, D.W.L. Water-use efficiency of some varieties of wheat, oats, barley, and flax grown in the greenhouse. Can. J. Plant Sci. 1966, 46, 375–378. [Google Scholar] [CrossRef]

--

--

Context Global Development® (CGD) is a non-profit organization that leads agricultural and social impact programs worldwide.

Love podcasts or audiobooks? Learn on the go with our new app.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Context Global Development

Context Global Development

Context Global Development® (CGD) is a non-profit organization that leads agricultural and social impact programs worldwide.