The University of Queensland, Australia; 2. ILRI, Addis Ababa, Ethiopia; 3. Central Queensland University, Australia.

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1 Effect of Variety and Location on Seed and Straw Yields and Nutritive Value of Common Bean (Phaseolus vulgaris L.) Straw in Crop-Livestock Systems of Ethiopia Mesfin Dejene 1, Rob Dixon 1, Alan Duncan 2, David McNeill 1, Kerry Walsh 3 and Endalkachew Wolde-meskel 2 1 The University of Queensland, Australia; 2 ILRI, Addis Ababa, Ethiopia; 3 Central Queensland University, Australia. Pan-African Grain Legume & World Cowpea Conference, Livingstone, Zambia, March 02, 2016.

2 Introduction Phaseolus vulgaris L. (bean, common bean, haricot bean or kidney bean) In Ethiopia common bean is increasingly important for food security and income and have considerable national economic significance as an export commodity. Production is expanding, where small holder farmers use beans as economical source of protein, a cash crop and fodder for livestock.

3 Introduction Crop residue left after grain/pod harvest contributes substantially to the feed supply for ruminants livestock. Cereal residues Crop aftermath free grazing

4 Introduction Cont d Cereal crop residues comprise a large proportion, but the N concentration & digestible energy contents are often much lower. The residues of grain legumes often better quality forage sources than cereal residues

5 Introduction Cont d Little emphasis has been given to improving the yield & nutritive value of crop residues for ruminants through plant breeding & selection. Common bean residue

6 Introduction Cont d This is especially the situation for grain legumes. The data analyzed for this experiment was part of a larger N2Africa project (Farrow, 2014).

7 Objectives (1) to assess the extent of variation in seed and straw yields, and straw quality traits, (2) to establish the interrelationships among the traits examined, (3) to determine the main and interaction effects of genotype and location in common bean, and (4) to examine the prospects for improving total biomass yield and feed value of bean straw.

8 Materials and Methods Table 1. Trial locations agro-ecologies and GPS Coordinates Location Agroecological Longitude Latitude Altitude (m.a.s.l) zones* Boricha SM1,M Mandura M1, SH SM1:sub-moist hot to warm lowlands ; M2:moist tepid to cool mid highlands ; M1:moist hot to warm lowlands; SH1:sub-humid hot to warm lowlands (*Farrow, 2014).

9 Laboratory evaluation of feed samples Air dry ground samples scanned in a spinning cup at nm, Foss 6500 NIR spectrometer CQ University. Fig.1. Foss 6500 NIR spectrometer Chemometric analyses of the spectral data was conducted with ISI software version software.

10 Laboratory evaluation of feed samples Cont d Spectral data was used to predict quality parameters: Total N, Dry matter digestibility (DMD), Neutral Detergent Fibre (NDF) and Acid Detergent Fibre (ADF), with the existing north Australian forage calibrations developed from tropical forages (Dixon and Coates, unpublished) (Table 2).

11 Laboratory evaluation of feed samples Cont d Table 2. Attributes of North Australian forage NIRS calibrations Attributes n Expected fit of MPLS model R 2 SECV Total nitrogen (Total N), % Dry matter digestibility (DMD), % Neutral detergent fibre (NDF), % Acid detergent fibre (ADF), % Source: R.M. Dixon and D.B. Coates, unpublished

12 Statistical analyses ANOVA was done using GLM procedure in SAS 9.2 (2009). The model Y ij = µ + α i + β j + (αβ) ij + ε ij was used for the analysis of the data, where where Y ij is the mean yield of genotype i in location j; µ is the overall mean; α i and β j are the main genotype and location effects; (αβ) ij is the genotype x location interaction effect; & ε ij is the residual associated with genotype i in location j.

13 Statistical analyses Cont d Simple linear relationships between yield, chemical and residue digestibility was analyzed by SAS Proc Corr. The comparison of means: Duncan s multiple range tests at 5 % level of significance.

14 Results Seed and residue yields and residue quality traits

15 Table 3. Seed and residue yields, and nutritive value of the residues of 9 common bean varieties (averaged across locations). Traits Mean (n=54) Range (n=6) Effects Variety Location V X L (V) (L) Seed yield (t/ha) P<0.003 P<0.002 P<0.03 Residue yield (t/ha) P<0.002 P< P<0.001 Harvest index NS NS NS Digestible yield, (t/ha) P< P< P< Total N (%) P< P< P< DMD (%) P< P< P< NDF (%) P< P< P< ADF (%) P< P< P< N: Nitrogen; DMD: Dry matter digestibility; NDF: Neutral detergent fibre; ADF: Acid detergent fibre; NS: Non-significant

16 3.0 Fig.2. Seed and residue yields and harvest index (HI) of nine bean varieties (averaged across location, 2013/14 (n=6) Seed Residue HI 2.5 AB A ABC ABC Yield, t/ha d E c DE c BCD bc DE ab a c CDE abc abc Argene Awash-1 A-Melka Dimtu Dinknesh H-Dume Ibado Nasir SARI Varieties

17 Total N (%) and DM digestibility coefficient Fig.3. Total Nitrogen (N, %) and DM digestibility coefficient of whole residue of nine common bean varieties (averaged across a locations) 2013/14 (n=6) b c d de f def ef g A FG BC G EF DE B A CD A-Melka Argene Awash-1 Dimtu Dinkinesh H-Dume Ibado Nassir SARI Varieties Total N DMD

18 Total N (%) and DM digestibility coefficient Fig. 4. Total Nitrogen (N, %) and DM digestibility coefficient of common bean residue botanical fractions (averaged across locations and varieties) (n=54). b A a Husk Straw Whole residue Residue morphological fractions C a B Total N% DMD

19 Results Cont d. Relationship between seed and residue traits

20 Seed yield (t/ha) Fig.4. Relationship between seed yield and residue yield in common been genotypes across both location y = 0.593x (r 2 =0.79; P<0.001; n=54) Residue yield (t/ha)

21 Residue total N verses seed yield. Total N (%) (a) Boricha, 2013/14 y = x R 2 = ; p=0.93; n= Seed yield (t/ha) Total N (%) (b) Mandura, 2013/14 y = x R² = 0.412; p<0.001; n= Seed yield (t/ha) Fig.5. Relationship between residue total N, % and seed yield, t/ha at (a) Boricha, and (b) Mandura, 2013/4 cropping season

22 Residue dry matter digestibility (DMD), % verses seed yield. DMD (%) (a) Boricha, 2013/14 y = 1.009x R² = 0.053; n= Seed yield (t/ha) DMD (%) (b) Mandura, 2013/14 y = x R² = 0.220; p=0.013; n= Seed yield (t/ha) Fig.6. Relationship between residue dry matter digestibility (DMD), % and seed yield, t/ha at (a) Boricha, and (b) Mandura, 2013/4 cropping season

23 Conclusion These results indicate that prospects for improving total biomass yield and feed value of bean straw. the absence of straw quality penalty for high seed and straw yields can depend on location/environment. It should therefore be possible to identify varieties of common bean that combine high harvest index and residue yield with desirable straw quality characteristics However, more number of varieties/genotypes shall be tested in a number of locations and season/years.

24 HOW GRAIN LEGUME DEVELOPMENT COULD IMPROVE LIVESTOCK PRODUCTIVITY? Breed/select legume varieties/genotypes that tolerate leaf shattering towards maturity stage suitable for integrating with cereals. Improve feed supply through proper/timely harvesting, threshing and conservation of grain legume residues Improve nutritive value of the whole basal diet for ruminants through optimizing of mixtures of legume and cereal residues Improve whole farm productivity and sustainability through better feeding and management of livestock and manure management.

25 Thank you