Dry matter yield and nutritive quality of alfalfa (Medicago sativa L.) cultivars grown in sub-humid areas in Ethiopia

Abstract

Alfalfa (Medicago sativa L.) is one of the most important perennial forage legumes with high nutritional quality. Four alfalfa cultivars were sown in randomized block design with four replications to evaluate their dry matter yield and nutritional quality under rain-fed conditions during 2016–2017 at Masha, southwest Ethiopia. Percentage of plot cover, plant height, leaf to stem ratio, dry matter yield, crude protein yield, and dry matter (DM), ash, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) were measured. The combined analysis revealed that days to 50% flowering were significantly (P < 0.01) influenced by cultivar and cropping year. Dry matter yield was significantly affected by cultivar and cultivar vs year interaction. Hairy Peruvian scored the highest plot cover percentage followed by Pioneer 00407, Hunter River, and Magna 788. The overall mean for days to 50% flowering indicated that Hunter River reached more lately than others. We observed that leaf-to-stem ratio and plant height were insignificant among the cultivars. Hairy Peruvian gave a higher dry matter yield (15.0 t ha⁻¹) followed by Pioneer 00407 (12.1 t ha⁻¹), Magna 788 (11.5 t ha⁻¹), and Hunter River (10.5 t ha⁻¹). The chemical compositions did not vary significantly (P > 0.05) due to cultivar differences. It could be concluded that, of the tested cultivars, Hairy Peruvian is an appropriate cultivar for biomass production potential under rain-fed conditions for sub-humid areas of southwest Ethiopia.

Keywords:

• biomass production
• chemical composition
• Hairy Peruvian
• Masha
• Ethiopia

PUBLIC INTEREST STATEMENT

In Ethiopian agriculture, the livestock sector plays a significant role in improving the livelihood of many people, and contributes to the provision of animal source food and nutritional security. However, inadequate and seasonal fluctuated feed resources both in amount and quality are the major bottleneck problems that hinders the animal production and productivity. To solve these feed constraints, the production of high-yielding and better use of improved forage species that are adapted to the local environmental conditions are fundamental options. Among different forage species, alfalfa is one of globally well-known perennial forage legume and nutritionally recognized as high-quality forage for all classes of livestock species. Thus, this study was focused on evaluation of alfalfa cultivars both in biomass yield and nutritional qualities. The result highlighted and identified alfalfa cultivar (Hairy Peruvian) that best suited and the promising cultivar for the sub-humid areas and similar environments of Ethiopia.

1. Introduction

The livestock sector in a developing country is an integral component of the farming system and plays a significant role in the provision of livelihood and nutrition security (Enahoro et al., 2018). For instance, in low-income countries, the demand in 2030 for beef, milk, poultry, and eggs is projected to be 124, 136, 301, and 208 percent increase over that in 2000, respectively (FAO, 2011). In Ethiopia, the livestock sub-sector plays a key role in economic and social contributions at household levels and to the national economy (Tolera et al., 2012). The sector contributed 20 percent of the total gross domestic product (GDP), 40 percent of agricultural GDP, and 20 percent of national foreign exchange earnings (Fitawek & Kalaba, 2017). However, livestock production in the country is constrained by seasonal fluctuations and unreliable feed supply both in quantity and quality (Alemayehu et al., 2020). Consequently, shortage of feed has been the greatest challenge in meeting the feeding needs of the beef and dairy cattle production system (Boote et al., 2022). To solve these feed constraints, the production of high-yielding and better use of improved forage species that are adapted to the local environmental conditions are fundamental options to reduce the production cost of feeding, minimize pressure on natural pasture and grazing lands, and also enhance natural assets substantially (Boote et al., 2022; Sanh et al., 2002). The introduction and production of highly promising improved forage crops like alfalfa are paramount to enhancing and improving the production and productivity of the livestock sector in the country (Alemayehu et al., 2020).

Alfalfa (Medicago sativa L.) is a perennial herbaceous forage legume grown around the world with the largest cultivation area and is recognized as high-quality forage for all classes of livestock species (Lenné & Wood, 2004; Mielmann, 2013; Shi et al., 2017). It is the most important forage legume and is mostly known as the “queen of the forages”, and could be used as an animal feed directly for grazing or conserved as silage or hay. Alfalfa can produce 25% more dry matter yield than pastures (Richard, 2011). Nutritionally, it has high protein profile 15 to 22 % crude protein on a dry matter basis, minerals, and vitamins, and is highly degradable by rumen microbes (Chen et al., 2009; Hao et al., 2008). It has traits of wider adaptability, on wide range soils including acidic soil, salty soil, resistance to frequent cutting, and useful contribution to soil fertility by providing high levels of nitrogen to the soil (Kebede et al., 2017; Shi et al., 2017). Moreover, forage production is the most important trait for the determination and identification of cultivars that adapt and have good persistence to particular environmental conditions (Casler & Undersander, 2000). The biomass productivity of alfalfa is affected by varietal differences, agronomic and management practices. Evaluations of the nutritive value are also an important aspect of quality forage production and increase animal performance (Becvarova et al., 2009).

In Ethiopia, researches have indicated that alfalfa has great potential for forage production in the central areas of the country (Geleti et al., 2014; Kebede et al., 2017); however, information regarding the adaptability and forage production of alfalfa cultivars in the study area is very limited. In southwestern Ethiopia, livestock production mainly relies on natural pasture and crop residues with shortage of feed supplements either produced or purchased by the farmers. Therefore, it was very prominent to identify the adaptability of different cultivars and choose varieties that can adapt and give high herbage yield to the particular environmental conditions. Thus, the present study was planned to evaluate four alfalfa cultivars for dry matter production potential and nutritive value for livestock producers in sub-humid areas of southwest Ethiopia.

2. Materials and methods

2.1. Site description

The experiment was performed at Masha sub-trial site under rain-fed conditions from 2016 to 2017 years. The experimental site is located at 7° 44ʹ00”-7° 82ʹ00” N latitude and 35° 29ʹ00”- 35° 66ʹ00” E longitude at an elevation of 2223 meters above sea level, southwest Ethiopia (Kebede, 2002). The long term (1981–2015 years) of the average annual rainfall of the area is 1615 mm, and the area has received a bimodal rainfall pattern in which 70 percent falls between June to October and the rest 30 percent falls between February to May. The area received a total of 2071 and 1897 mm of rainfall in the 2016 and 2017 years, respectively. The mean maximum and minimum temperatures are 23.0 and 12.3°C, respectively (Benti & Abara, 2019; Zewide et al., 2018). The soil texture is clay 45%, silt 31%, and sand 14%, has a pH of 4.5–5.2, cation exchange capacity (CEC) of 20, total nitrogen 0.1%; and available phosphorus level of 5.5 ppm (Embaye et al., 2005; Zewide et al., 2018).

2.2. Tested cultivars, experimental design, and management

Four alfalfa cultivars were brought from Debrezeit Agriculture Research Center (Ethiopia) and used for this study. The research center initially introduced the cultivar from USA and maintained in the center forage gene bank. The cultivars, Magna 788 from University of California (Putnam et al., 2007), Hunter River, Pioneer 00407 (Yu et al., 2004), and Hairy Peruvian originated from Peru and introduced from USA (Parfitt, 1956) were sown in mid-June 2016 when adequate moisture is present, on a well-prepared plot measured 2.4 by 3 m and laid out in a randomized complete block design with four replications. Sowing was done at a 16 kg ha⁻¹ seeding rate by drilling in 0.3 m row spacing with approximately ½ inch soil depth. To ensure good seed to soil contact, the soil onto the seedbed was pressed by hand. The spacing between plots and blocks was 1 m and 1.5 m, respectively. Uniform trial management such as hand weeding and hoeing between rows were carried out during establishment year and after every harvest to facilitate the regrowth of healthy and productive stand (Kay, 2004). No fertilizer was applied to the experiment in line with general farmers’ practices. Due to the perennial nature and the persistence characteristics of the crop, the second year data (2017) was collected from the regrowth following the second harvest during the first year.

2.3. Data collection and laboratory analysis

Agronomic data such as four weeks and eight-weeks plot soil cover percentage after planting and taken on plot-based to determine the plant vigor, days to 50% flowering, plant height, leaf to stem ratio, dry matter yield, and nutritive value were considered. We measured the plant height at full blooming stage from 10 randomly selected sample plants and their mean was recorded for statistical analysis. Leaf-to-stem ratio (LSR) was taken from 10 sample plants and partitioned into leaf and stem fractions to determine the ratio of the dry weight of leaves to the weight of stem. A total of six central rows from each plot of the cultivars were harvested for dry matter yield (DMY) determination. Data for dry matter production and in each harvests were considered. Harvesting was undertaken manually using sickle at 50% flowering stage at about 5 cm above ground from each plot and weighted using spring balance to determine total fresh weight. The yield from each cut for each year was computed and the combined data was also used to calculate total dry matter. For each harvest in 2016 and 2017 years, samples weighing 500 g were randomly taken during the harvest periods, and dried in a forced-air oven at 65 °C for 72 hours. The dried samples were weighed and ground in a mill with a 1 mm sieve size and submitted to Holetta Agricultural Research Center, Animal nutrition laboratory for chemical analysis. The dry matter yield was computed from the samples in each plot. The sum of all harvests in each year is considered as yearly yield and we also considered the total harvests of both years. Crude protein yield was computed using the formula: CPY = CP%* DMY (t/ha).

For nutritional quality analysis, samples from each harvest cycle of the two years cropping seasons were taken and bulked for chemical analysis. The dried grass samples from each treatment were ground in a mill to pass a 1 mm sieve size used for laboratory analysis. The ground samples were dried over night at 65 °C for 72 hours in an oven dry to constant moisture. The DM, ash and organic matter contents of the feed samples were determined following the procedure of AOAC (1990). Total ash content was determined by combusting the samples in a muffle furnace at 550 °C for 6 hours. The N (nitrogen) contents of the sample were determined by the micro-Kjeldhal method (AOAC, 1990) and the amount of N multiplied by 6.25 to estimate the crude protein (CP). Neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) were determined according to the procedure of (Van Soest et al., 1991).

2.4. Statistical analysis

The data were analyzed using the analysis of variance (ANOVA) of the general linear models (SAS, 2011). Mean differences for cultivars were separated with the least significant difference (LSD) at P ≤ 0.05 significant level.

3. Results and discussion

3.1. Cultivar, year, and their interactions

The analysis of variance (ANOVA) for Cultivar, year, and their interactions of alfalfa are shown in Table 1. The mean square of the cultivar had a significant (P < 0.01) effect on days to 50% flowering, dry matter yield (DMY), and crude protein yield (CPY). Conversely leaf-to-stem ratio (LSR) and plant height (PH) were not affected. This is in agreement with Gashaw et al. (2015) who demonstrated that the cultivars effect was not significant for leaf stem ratio. Year also significantly (P < 0.01) influenced for days to 50% flowering; in contrast, plant height, leaf-to-stem ratio, and dry matter yield are unlikely affected by year. Except for DMY, and CPY the interaction of cultivar and year did not significantly (P > 0.05) affect the measured traits. The dry matter production variation was induced by either cultivar or cropping year.

Table 1. Analysis of variance for cultivar, year, and their interaction for days to 50% flowering, leaf to stem ratio, plant height, dry matter yield, and crude protein yield

Source of variation	DF	Parameters
		D50%Fl	LSR	PH	DMY	CPY
Cultivar	3	218.8**	0.03ns	20.8ns	5.8**	0.13**
Year	1	155**	0.01ns	7.2ns	0.7ns	0.02ns
Interaction	3	16.1ns	0.5ns	1.2ns	6.3**	0.15**

DF = Degrees of freedom; D50% Fl = days to 50% of flowering; LSR = leaf to stem ratio; PH = plant height in cm; DMY = dry matter yield in ton/hectare; CPY = crude protein yield ton/hectare; ** = significant difference at P < 0.01; ns = non-significant at P > 0.05.

3.2. Plot cover in four and eight weeks at establishment year

Percentage of plot soil cover at four weeks (PCFW) and plot cover at eight weeks (PCEW) after establishment for the evaluated alfalfa cultivars are indicated in Figure 1. At PCFW, Hairy Peruvian scored the highest plot cover percentage followed by Pioneer 00407, Hunter River, and Magna 788 in descending order. Likewise, Hairy Peruvian and Pioneer 00407 were recorded higher PCEW percentage than Hunter River, and Magna 788. The two later cultivars scored statistically similar plot cover percentages. We observed that as the growth period advanced the plot soil cover increased and this might be attributed to an increase in plant vigor, the number of tillers, and the development of roots to make better nutrient uptake. In agreement with the present findings, Kay (2004) reported that primary stems continue to develop, producing secondary stems. Although alfalfa required good soil pH ranging from 6.5 to 7 for better establishment and growth, the soil conditions of the experimental site could not limit alfalfa production. In contrast, Redfearn and Zhang (2011) found that the growth of alfalfa commonly depends on the chemical properties of the soils.

Figure 1. The percent plot cover at four weeks (PCFW), and the plot cover at eight weeks (PCEW) of four alfalfa cultivars.

3.3. Days to 50% flowering and leaf to stem ratio

The cultivars showed a significant difference (P < 0.05) for days to 50% flowering in both years and the overall mean (Table 2). Days to 50% flowering showed significance (P < 0.01). Accordingly, Hunter River, Magna 788, and Pioneer 00407 cultivars reached significantly earlier to 50% flowering stage than Hairy Peruvian. In contrast, Geleti et al. (2014) found that five alfalfa cultivars attained eight cuts at average intervals of 54.6 ± 12.4 days. The variation in days to forage harvest compared with other findings (Geleti et al., 2014; Kennington et al., 2005) might be due to altitude, climatic conditions (rainfall and temperature), soil types and varietal differences. The overall mean for the days to 50% flowering across the year also showed significance (P < 0.01). The evaluated alfalfa cultivars reached earlier days to forage harvest (50% flowering) in the establishment year (2016) than the following year (2017). Two cuts were taken at an average interval of 110.8 days and three harvest cycles were taken at an average interval of 115.8 days between harvests in 2016 and 2017 years, respectively. The variation to attain 50 % flowering of alfalfa across the year might be due to differences in the weather conditions probably the amount of rainfall. Nevertheless, no significant variation was found among the alfalfa cultivars in leaf to stem ratio in both production years and the overall mean across the years.

Table 2. Mean values of days to 50% flowering and leaf to stem ratio of four alfalfa cultivars evaluated during 2016 and 2017 years

Cultivars	Days to 50% flowering			Leaf to stem ratio
	2016	2017	Mean	2016	2017	Mean
Magna 788	108.0^bc	116.3^ab	112.2^b	0.7	0.8	0.7
Hunter River	106.0^c	107.0^b	106.5^b	0.8	0.7	0.7
Pioneer 00407	111.3^b	115.3^ab	113.3^b	0.7	0.7	0.7
Hairy Peruvian	117.7^a	124.7^a	121.2^a	0.8	0.9	0.9
Mean	110.8^b	115.8^a	113.3	0.74	0.8	0.8
CV (%)	24.5	4.2	4.2	24.5	23	22.1
Sig. level	*	**	**	Ns	Ns	Ns

Means within a column followed by different supper-script letters are significantly different (P < 0.05) CV = coefficient of variation; * = significant difference at P < 0.05** = significant difference at P < 0.01; Ns = non-significant

3.4. Plant height at harvest

As shown in Table 3, the measured plant height in each subsequent harvest did not significantly (P > 0.05) affect due to cultivars both in the establishment year and in the following year. The overall mean plant height (PH) of the cultivars in the subsequent harvests ranged from 66.3 to 75.2 cm. In contrast to the present finding, Atumo et al. (2021) found that the plant height of six alfalfa genotypes evaluated at four locations were in the range of 56.1 to 60.1 cm. The variation could be due to the genetic factor, soil characteristics and climatic conditions (temperature and rainfall) influencing the growth of the crop (Barnabás et al., 2008).

Table 3. Mean of plant height (PH) at harvest of four alfalfa cultivars evaluated during 2016 and 2017 years at Masha highland

Cultivars	2016			2017				Overall
	PH1	PH2	Mean	PH1	PH2	PH3	Mean
Magna 788	69.2	75.3	72.2	71.2	79.4	66.7	72.4	72.3
Hunter River	67.5	70.2	68.8	70.3	73	65	69.4	69.2
Pioneer 00407	64.2	69.4	66.8	68.5	74	64.7	69.1	67.9
Hairy Peruvian	66.4	72.4	69.4	68.8	74.5	69	70.8	70.1
Mean	66.8	71.8	69.3	69.7	75.2	66.3	70.4	69.9
CV (%)	12.7	11.5	11.4	11.1	7.5	3.2	5.8	8.6
Sig. level	Ns	Ns	Ns	Ns	Ns	Ns	Ns	Ns

PH1, PH2 & PH3 (cm) = plant height in cm at harvest 1, 2 & 3; CV = coefficient of variation; Ns = non-significant

3.5. Dry matter production

Table 4 illustrates the dry matter yield of two harvests taken in the month of September and December in 2016 whereas three harvests were taken in 2017 on the months of June, September and December with a total of five harvests. We observed a significant difference (P < 0.05) among the cultivars for dry matter yield in the 2016 production year, and this was also consistently observed in total dry matter yield of both years. Conversely, no statistical yield differences were exhibited among cultivars in the second year. Hairy Peruvian attained higher total dry matter yield followed by Pioneer 00407, Magna 788, and Hunter River with mean values of 15.0, 12.1, 11.5, and 10.5 t ha⁻¹, respectively.

Table 4. Dry matter yield of four alfalfa cultivars during 2016 and 2017 years at Masha highland

	2016			2017				Total
	DMY1	DMY2	Sub-total	DMY1	DMY2	DMY3	Sub-total
Magna 788	2.4^b	3.0^b	5.4^b	2.0	2.7	1.4	6.1	11.5^b
Hunter River	2.0^b	2.5^b	4.5^b	1.8	2.4	1.7	5.9	10.5^b
Pioneer 00407	2.9^b	3.2^b	6.1^b	2.3	2.0	1.5	5.8	12.1^b
Hairy Peruvian	4.5^a	4.7^a	9.2^a	2.2	2.0	1.7	5.9	15.0^a
Mean	2.9	3.4	6.3	2.1	2.3	1.2	5.9	12.3
CV (%)	15.8	18.4	16.2	15.5	16.9	14.8	13.2	10.0
Sig. level	**	*	**	Ns	Ns	Ns	Ns	**

Means within a column followed by different supper-script letters are significantly different (P < 0.05) DMY1, DMY2 &DMY3 (cm) = dry matter yield at harvest 1, 2 & 3, respectively; CV = coefficient of variation; * = significant difference at P < 0.05** = significant difference at P < 0.01; Ns = non-significant

The dry matter yield of the subsequent harvests of alfalfa cultivars achieved in 2017 showed a constant persistence among the cultivars. In our study, we observed that the as the frequency of harvest increase the dry matter yield decrease and this was prominently indicated in in the third harvest of the second year. Similarly, studies confirmed that cutting too frequently may cause low herbage yield due to plant death in a reduction in the crown and root reserves (Humphries et al., 2006; Suriyagoda et al., 2010). However, better cumulative yields are attainable as the harvesting cycle increases within a specific period.

3.6. Crude protein production

The crude protein yield of the tested alfalfa cultivars is presented in Table 5. Significant variations (P < 0.01) were observed among the alfalfa cultivars in 2016 and the total mean. Whereas in 2017, the cultivars were not significantly varied. Hairy Peruvian attained the highest crude protein yield with mean value of 1.41 and 1.16 t/ha in 2016 and total mean, respectively than the rest of tested cultivars. The CPY of the tested alfalfa cultivars showed a consistent trend with that of the DMY. The CPY obtained in the present study lay between 2.4 to 2.9 t/ha reported by Atumo et al. (2021).

Table 5. Crude protein yield of four alfalfa cultivars during 2016 and 2017 years at Masha highland

Cultivars	Crude protein yield (CPY t/ha)
	2016	2017	Total
Magna 788	0.85^b	0.96	0.91^b
Hunter River	0.71^b	0.92	0.81^b
Pioneer 00407	0.97^b	0.93	0.95^b
Hairy Peruvian	1.41^a	0.91	1.16^a
Mean	0.99	0.93	0.96
CV (%)	15.2	12.3	15.2
Sig. level	**	Ns	**

Means within a column followed by different supper-script letters are significantly different (P < 0.05) CV = coefficient of variation; ** = significant difference at P < 0.01; Ns = non-significant

3.7. Chemical composition

The nutritive composition of alfalfa cultivars evaluated at Masha is indicated in Table 6. We observed that the chemical composition for dry matter (DM), ash, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) not varied significantly due to cultivar differences. Good quality alfalfa is low in fiber and high in digestible protein (Redfearn & Zhang, 2011; Sanz-Sáez et al., 2012). Although several factors such as geographical location, soil fertilization, variety, environmental conditions, stage of plant maturity at harvesting, season, and postharvest storage method influencing the composition of the feed, feed quality should be taken into account to recommend cultivars for forage production in a particular environment (Fekede et al., 2015; Gashaw et al., 2015; Kennington et al., 2005). Study done by Radović et al. (2009) and (Putnam et al., 2007) confirmed that differences between alfalfa cultivars are not significant effect on nutritive value rather agronomic practices such as cutting schedule and weed control influence quality at a greater degree. The insignificant difference in chemical composition of the tested cultivar in the present study would lead us to select better herbage yielder cultivar.

Table 6. The chemical composition of alfalfa cultivars grown at Masha highland

Variety	Chemical composition (%)
	DM	Ash	CP	NDF	ADF	ADL
Magna 788	91.8	7.4	15.9	44.8	30.9	6.7
Hunter River	92.7	7.5	15.5	44.5	30.3	6.4
Pioneer 00407	92.3	7.3	15.8	44.3	30.6	6.4
Hairy Peruvian	92.7	7.5	15.4	44.5	30.2	6.3
Mean	92.3	7.4	15.7	44.5	30.5	6.5
CV (%)	0.5	2.9	3.8	1.7	1.7	7.2
Sig. level	Ns	Ns	Ns	Ns	Ns	Ns

DM = dry matter, CP = crude protein, NDF = Neutral detergent fiber, ADF = acid detergent fiber, ADL = Acid detergent fiber, CV = coefficient of variation; Ns = non-significant

4. Conclusion

The results of this study indicate that the alfalfa cultivars differed markedly in dry matter yield. However, the tested cultivars found to be non-significant difference in leaf to stem ratio, plant height and in terms of chemical compositions. In conclusion, among the tested alfalfa cultivars, Hairy Peruvian was identified as high dry matter yielder, adaptable and best suited cultivar for sub-humid areas of southwest Ethiopia and in environments with similar agro-ecology of the country. Therefore, the selected cultivar should be demonstrated to the farmers’ condition for wider use.

Author’s contributions

Gezahegn Mengistu, Melkam Aleme, Ararsa Bogale, and Dereje Tulu proposed the concept, performed the experiment, field data execution, and analysis, writing and editing. Mulisa Faji, Geberemariyam Terefe, and Kedir Muhammed did laboratory analysis and editing the paper.

Acknowledgements

The authors are highly acknowledged by the Ethiopian Institute of Agricultural Research, a forage research program in financial support for this work. The authors also would like to greatly acknowledge Holetta animal nutrition laboratory staff for their assistance in laboratory analysis and Teppi Agricultural Research Center staff for implementation and finalization of this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data set used /analyzed during the current study is available from the corresponding author on reasonable request. www.linkedin.com/in/gezahegn-mengistu-ab9492155

Additional information

Funding

This work is financially supported by the Ethiopian Institute of Agricultural Research (EIAR), livestock research directorate. None of the funder was involved in data collection, analysis and interpretation or writing the paper.

Notes on contributors

Gezahegn Mengistu

Gezahegn Mengistu from Ethiopia received Bsc in Animal Science from Ambo University, followed by his MSc in Animal Production from Jimma University, College of Agriculture and Veterinary Medicine. Since May 2014, he has been working in Ethiopian Institute of Agricultural Research (EIAR), at Teppi and Holetta Agricultural Research Centers on animal feed and nutrition, improved forage crops research activities. His research interest focuses on animal production specifically in animal feed and nutrition, conducting animal feed experimentation, forage and pasture research. His goal centered conducting research on improved forage crops to improve animal productivity through nutrition and management that will enhance livestock farm sustainability and profitability.