Effects of agro-ecological zones on the chemical composition of feed resources in the Gera district, southwest Ethiopia

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The aim of this study was to determine and compare the chemical composition of major feed resources in three agro-ecologicalzones (AEZs) of the Gera District, southwest Ethiopia. Three representative samples of natural pasture ( Cynodon dactylon, Pavonia schimperiana Hochst and Rhynchosia ferruginea), three indigenous fodder trees and shrubs (IFTSs) (Erythrina abyssinica, Vernonia amygdalina and Maytenus undat), two cultivated forages ( Pennisetum purpureum and Pennisetum pedicellatum ) and five crop residues ( Hordeum vulgare (barley) , Zea mays (maize) , Sorghumbicolor (sorghum) , Triticum aestivum (wheat) and Eragrostis tef (Teff)) were collected from the Highland (HL), midland (ML) and lowland (LL) AEZs. The samples were analyzed for ash, dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), and acid detergent lignin (ADL) content. The results showed that different AEZs showed a significant ( P < 0.05) effect on the most of the chemical composition parameters of sampled feeds. Regardless of the AEZs, the mean DM, CP, ash, EE, NDF, ADF, ADL and CF varied from 89.17% in Pennisetum purpureum to 92.22±0.51 in Erythrina abyssinica , 2.90±0.22% in Triticum aestivum to 10.70±0.52 in Vernonia amygdalina , 7.24±0.19% in Sorghum bicolor to 13.25±0.51% in Pavonia Schimperiana Hochst , 1.33±0.04% in Triticum aestivum to 2.39±0.15% in Maytenus undata , 57.65±1.19% in Erythrina Abyssinica to 79.16±1.04%in Triticum aestivum , 34.57% in Pennisetum purpureum to 59.41±0.98% in Sorghum bicolor , 8.15±0.62%in Rhynchosia ferruginea to 12.65±0.57% in Triticum aestivum and 37.51% in Pennisetum pedicelatum to 69.93±0.65% DM in Triticum aestivum , respectively. In conclusion, IFTSs had the highest CP and the lowest NDF, implying their potential as a supplement to low-quality feeds, whereas crop residues had the lowest CP and the highest NDF compared to other feed types, indicating the need for their treatment with urea or supplementing animals with protein-rich feeds, especially during the dry season. chemical composition crop residues improved forage indigenous fodder trees and shrubs natural pasture livestock INTRODUCTION Ethiopia has the largest livestock population in Africa. According to the Central Statistical Agency (CSA, 2021 ), the country has approximately 70 million head of cattle, 42.9 million head of sheep, 52.5 million head of goats, 2.15 million head of horses, 10.80 million head of donkeys, 0.38 million head of mules, 8.1 million head of camels, and 56.87 million head of poultry at the country level. Despite having one of the largest livestock populations, its productivity has remained very low. This is mainly attributed to feed shortages both in quality and quantity (Tolera et al., 2012 ). Livestock production contributes approximately 17-25.3% of gross domestic product (GDP), 39–49% of agricultural GDP and more than 50% of household income in Ethiopia (Shapiro, 2017 ) . In addition, livestock supplies meat, milk and eggs as sources of protein and significantly contributes to the sustainability of crop production through the provision of draught power and manure for soil fertilization, transportation, income, employment, manure for soil fertility management, and security to reduce the risk of crop failure, live banks, wealth storage, and social prestige for rural farmers (Dereje et al., 2014 ). Despite the large population, animal productivity in Ethiopia is poor, even below the values recorded for the majority of the countries in eastern and sub-Saharan Africa (Gebreegziabher, 2010). The major constraints are low-productivity feed scarcity in terms of quality and quantity, low genetic potential of indigenous livestock, a high incidence of disease and parasites, traditional management practices, poor access to extension and credit services and a lack of knowledge to improve animal performance (Aynalem et al. 2011 ; Birhan and Adugna, 2014 ; Defar, 2018 ). Of these, poor-quality feed resources were identified as the greatest constraint limiting livestock productivity (Defar, 2018 ). Natural pasture, crop residues, hay, agro-industrial byproducts, improved feed and other products, such as animal byproducts and vegetable and fruit wastes, are livestock feed resources available in Ethiopia (CSA, 2020). Of these, natural pasture and crop residues are major feed resources but are characterized by low digestibility and crude protein content, which adversely affects livestock productivity (Shapiro et al., 2017 ). In southern Ethiopia, Deribe et al. ( 2013 ) reported that the CP contents of grass species and crop residues ranged from 1.42%-18.95% and 2.01–8.97% DM, respectively. In terms of quality, cereal crop residues are generally of low nutritive value because of their relatively low CP ranging from 2.39 ± 0.16% to 7.20 ± 0.09% and high NDF ranging from 72.59 ± 2.26 to 78.19 ± 0.77% in western Ethiopia (Tamene et al., 2022). Leng ( 1990 ) defined low-quality forage as those with a CP value < 8% and suggested the supplementation of such forages with appropriate nutrients to achieve high levels of animal production. Abeysekara ( 2003 ) reported that the quality of feeds reveals the nutrient (chemical) composition, palatability and intake, digestibility, antinutritional factors and animal production performance. Most of the forages from natural pastures and crop residues contain CP below 7% and NDF above 55% DM (Solomon et al., 2008), both of which indicate poor nutritive value incapable of meeting rumen microbial requirements, particularly with regard to CP content (Van Soest, 1994 ). Leng ( 1990 ) also indicated that low-quality forages, such as those with less than 8% DM CP content, adversely affect rumen microbial activity (Van Soest, 1982 ). It has been stated that a CP content of approximately 15% DM for high milk production (> 15 kg/cow/day) and 8 to 13% for moderate milk production (10–15 kg/cow/day) are required by dairy cows (ARC, 1984 ; Humphreys, 1991 ). The total NDF content of forage is a dominant factor in determining forage quality (Gezahagn et al., 2014 ). The NDF content of feeds above 60% and 50 to 60% DM are classified as poor and moderate quality feed, respectively (Van Soest, 1982 ). A greater amount of forage ADF results in reduced digestibility of dry matter as a consequence of increased lignification of cellulose in plants (Depeters, 1993 ). Kellems and Church ( 1998 ) categorized roughages with less than 40% ADF as high quality and those with more than 40% ADF as low quality. The lignin content of feeds and forages affects the digestibility of forage more than any other chemical component of feeds (Van Soest and Robertson, 1979 ; Van Soest, 1982 ). According to Van Soest ( 1982 ), a lignin content above 6% DM negatively affects the digestibility of forage. Deficiency of feed in terms of quantity and quality negatively affects the productive and reproductive performance of grazing livestock (Compbell et al., 2003. According to the National Research Council (NRC) (2007), optimum productive and reproductive performance of livestock can be achieved only when the animals are fed the required quantity of feedstuffs containing all the nutrients in the proper amount. Precise information on feed composition with respect to proximate composition and fiber fractions is essential for assessing the nutritional status of feeds and fodders and of the animals to which these feeds and fodders are fed (Ganai et al., 2004 ). In the present study area, natural pasture, crop residues, indigenous fodder trees and shrubs, and, to a lesser extent, improved forages are the most important feed resources for livestock. However, there is no information on their chemical composition. This lack of information could limit the formulation of balanced rations for better utilization of available feed resources to improve livestock productivity. Thus, the results of this study will help to fill this information gap and provide the basis for generating empirical evidence to improve feed quality to improve livestock productivity. With this insight, the objective of this study was to evaluate and compare the chemical composition of major feed resources obtained from three agro-ecological zones of the Gera district, southwest Ethiopia. MATERIALS AND METHODS Description of the study area This study was conducted in the Gera district of the Jimma zone, Oromia Regional State, southwest Ethiopia. A detailed description of the study area can be found in a previously published companion study (Abazinab et al., 2022 ). Feed sampling Representative samples of 13 different feedstuffs which farmers were feeding to their animals, including three natural pasture species ( Cynodon dactylon, Pavoniaschimperiana Hochst and Rhynchosia ferruginea) , three indigenous fodder trees and shrubs ( Erythrina Abyssinica, Vernonia amygdalina, and Maytenus undat ), two cultivated forages ( Pennisetum purpureum and Pennisetum pedicellatum ) and five crop residues ( Hordeum vulgare, Zea mays stover, Sorghum bicolor stover, Triticum aestivum straw and Eragrostis tef straw) were randomly collected from the HL, ML and LL AEZs of the Gera District following appropriate procedures. Samples of natural pasture were collected using a 0.5m x 0.5m quadrate from each selected grazing sites in each AEZ using sickle. The quadrate was thrown on the selected sites and harvested the whole plant at grazing height of about 5cm above the ground. For indigenous fodder trees and shrubs, edible green leaves and twigs were hand harvested from all four directions in the lower, middle, and top portions of the canopy in each agro-ecological zone. All samples of crop residues stems (including leaves, stems or stalks) were collected from fields after crops had been harvested and/or threshed under traditional practices. The crops were harvested when the plants were dry. After sampling, the same feed samples collected from highland midland and lowland agro-ecological zone were bulked together, mixed thoroughly and sub-sampled to make one composite sample. The fresh samples of native grasses, improved forages and IFTSs were weighed, sun-dried and stored in polythene bags. Chemical analyses of feed samples were performed at Animal Nutrition Laboratory of the Department of Animal Science, College of Agriculture and Veterinary Medicine, Jimma University for proximate analysis. Laboratory analysis In the laboratory, all samples were oven dried at 65°C for 24 hours, milled to pass through a 1 mm mesh sieve, and analyzed on a % DM basis, except for DM, which is expressed as % fresh matter. The samples were analyzed for DM, ash, CP, EE and CF by the procedures of the AOAC (2005). The DM content was determined by drying the samples at 105°C overnight to a constant weight. Ash content was determined by igniting the ground samples at 550°C for 6 hours in a muffle furnace. The nitrogen (N) content was determined by the Kjeldahl method, and CP was calculated as N × 6.25. The fiber fractions (NDF, ADF and ADL) were determined using the method of Van Soest et al. ( 1991 ). The samples were analyzed in duplicate. Statistical analysis Statistical analysis The data were subjected to analyses of variance (ANOVAs) using the Statistical Package for Social Sciences (SPSS) Program Version 20.0. The differences between means were separated by Duncan's multiple range test using the IBM SPSS Statistics Programme, Version 20.0. Differences were considered significant when P < 0.05. The results are presented as the means ± standard errors (SEs). The statistical model used for data analysis was as follows: Yij = µ + αi + Σij where Yij is the response of the parameter/variable investigation; DM, Ash, CP, CF, EE, NDF, ADF and ADL µ = overall mean αI = the effect of i th location/agro-ecology (I = HL, ML, LL) Σij = random error RESULTS AND DISCUSSION Chemical compositions of forage species in natural pastures Table 1 shows the chemical composition (% DM) of the natural pastures in the three agro-ecological zones of the study area. The results showed that the mean DM, ash, EE, CP, NDF, ADF, and CF of natural pastures ranged from 89.82 ± 0.29 in Rhynchosia ferruginea A. Rich at HL to 93.58 ± 0.26 in C. dactylon at LL, from 7.95 ± 0.39 in C. dactylon at LL to 14.83 ± 0.08 in Pavonia Schimperiana Hochst at HL, from 1.13 ± 0.09 in Pavonia Schimperiana Hochst at ML to 1.62 ± 0.12 in C. dactylon at HL, 7.12 ± 0.72 in Pavonia Schimperiana Hochst at ML to 11.16 ± 0.44 in C. dactylon at HL, 61.12 ± 0.64 in Pavonia Schimperiana Hochst at HL to 69.34 ± 0.44 in C. dactylon at LL, 37.41 ± 0.44 in Rhynchosia ferruginea A. Rich at HL to 47.68 ± 0.46 in C. dactylon at LL, and 6.59 ± 0. The DM, Ash, EE, CP, NDF, ADF, ADL and CF values of Cynadon dactylon ranged from 90.95 ± 0.46 to 93.58 ± 0.26, 9.27 ± 0.31 to 9.63 ± 0.68, 1.35 ± 0.15 to 1.62 ± 0.12, 7.77 ± 0.14 to 11.16 ± 0.44, 61.16 ± 0.86 to 69.34 ± 0.44, 38.24 ± 0.86 to 47.68 ± 0.46, 6.76 ± 0.73 to 11.56 ± 0.92, and 34.52 ± 0.38 to 43.59 ± 0.88, respectively. Variation in AEZ significantly ( p < 0.05 ) influenced the chemical composition parameters of Cynadon dactylon . The DM, NDF, AD, AD, and CF contents of C. dactylon were significantly (p < 0.05) greater at LL compared to other AEZS, whereas CP content was greater (p 0.05). These variations might be due to climatic conditions, soil fertility, and harvesting stage. Pavonia schimperiana from HL exhibited significantly (p < 0.05) greater ash values than those from ML and LL, whereas CP and EE were greater at LL, and NDF was greater at ML than at other AEZs. The DM, ADF and ADL contents of Rhynchosia ferruginea A. Rich in ML were significantly ( p < 0.05) greater than those in HL and LL. The other chemical composition parameters did not vary among the agro-ecological zones. The variations observed in the various chemical composition parameters among the different species in the AEZs might be due to differences in climatic conditions, soil fertility and stage of maturity. The DM values of the natural pasture species observed in this study are greater than the recommended range of 70–80% and may limit feed intake by livestock (Van Soest, 1994 ). The CP content of the natural pasture obtained in this study was greater than the minimum of 7–8% DM for optimum rumen microbial function and maintenance requirements of ruminants (NRC, 2001 ). However, our results are lower than the minimum recommended values of 12% for lactation and 11.3% DM for growth in ruminants (ARC, 1984 ), indicating the need for supplementation with high-protein feeds. The voluntary intake of ruminants decreases when the CP level is below 6–7% DM (ARC, 1984 ; Minson, 1990). The EE content of natural pasture species observed in the present study was lower than the minimum recommended value of 5% DM, indicating a lower energy level for the animal (Odedire and Babayemi, 2008 ). Fats, as livestock feed, function much like carbohydrates in that they serve as a source of heat and energy and for the formation of fat due to the larger proportion of carbon and hydrogen. The overall mean NDF content of the natural pasture recorded in this study was greater than the critical value of 60% (Reed and Goe, 1989 ), which may have resulted in decreased voluntary feed intake and feed conversion efficiency and increased rumination time. Roughage feeds with NDF contents less than 45, 45–65, and greater than 65% are considered high-, medium-, and low-quality, respectively (Singh Oosting, 1992). It has been reported that 36% NDF is ideal for forage for domestic animals, but greater than 36% NDF limits of intake due to rumen fill, and less than 36% NDF results in insufficient fiber for rumen scratch factor and proper rumen function (NRC, 2001 ). The higher NDF level of the natural pasture in this study might be due to its high maturity, which provided a chance for fiber accumulation in plant tissues. In this study, the ADF content in natural pastures ranged from 37.41 ± 0.44 in Rhynchosia ferruginea A. Rich at HL to 47.68 ± 0.46 in Cynodon dactylon at LL. These results are higher than the recommended level of 18–20% DM (Riaz et al. 2014 ) and the range of 17–21%, which is usually recommended for rumen stability (NRC, 2001 ). ADF contents greater than 40% are considered low quality, whereas those less than 40% are considered high quality (Kellems and Church, 1998 ). Based on this classification, the ADF contents of the natural pastures observed in this study were classified as both good and poor quality. The ADL content of the natural pasture in this study ranged from 6.59 ± 0.73 in Rhynchosia ferruginea A. Rich at HL to 11.56 ± 0.92 in Cynodon dactylon at LL. Of the components of the cell wall, lignin is considered the main factor limiting feed intake, fiber degradation in the rumen, the rate of organic matter fermentation, the number of microbial cells produced per unit of fermented organic matter, and the proportion of propionate to acetate in the products of fermentation (Van Soest, 1994 ; Van Soest and Robertson, 1985 ). The percentage of fiber that is digested may be less than 60% in feed that contains 10% DM of lignin (McDowell, 1985). Generally, the variations in the chemical composition of natural pastures between the present study and the literature might be due to environmental conditions, climatic conditions, plant type and species, soil fertility, weather conditions during growth, and stage of maturity variation. Table 1 Chemical composition (% DM) of natural pastures in three AEZs of Gera District, southwest Ethiopia Species Chemical composition (Mean ± SE) AEZ DM Ash EE CP NDF ADF ADL Cynadon dactylon HL 90.95 ± 0.46 b 9.63 ± 0.68 1.62 ± 0.12 11.16 ± 0.44 a 61.16 ± 0.86 b 38.24 ± 0.86 c 6.76 ± 0.73 b ML 91.50 ± 0.43 b 9.27 ± 0.31 1.49 ± 0.32 8.75 ± 0.70 b 67.25 ± 0.71 a 43.14 ± 1.38 b 7.13 ± 1.03 b LL 93.58 ± 0.26 a 7.95 ± 0.39 1.35 ± 0.15 7.77 ± 0.14 b 69.34 ± 0.44 a 47.68 ± 0.46 a 11.56 ± 0.92 a Overall 92.01 ± 0.44 8.95 ± 0.35 1.48 ± 0.08 9.23 ± 0.55 65.91 ± 1.27 43.02 ± 1.45 8.48 ± 0.89 P value 0.007 0.114 0.495 0.007 0.000 0.002 0.017 Pavonia Schimperiana Hochst (kalalaa) HL 90.88 ± 0.90 14.83 ± 0.08 a 1.48 ± 0.03 a 8.13 ± 0.68 ab 61.12 ± 0.64 b 40.85 ± 1.05 7.13 ± 0.43 ML 92.13 ± 0.96 13.23 ± 0.19 ab 1.13 ± 0.09 b 7.12 ± 0.72 b 65.86 ± 0.73 a 44.09 ± 1.02 9.66 ± 0.73 LL 92.85 ± 0.70 11.66 ± 0.71 b 1.55 ± 0.05 10.44 ± 0.24 a 60.95 ± 0.99 40.47 ± 0.85 7.73 ± 0.95 Overall 91.95 ± 0.51 13.25 ± 0.51 1.38 ± 0.07 8.56 ± 0.57 62.65 ± 0.89 41.81 ± 0.75 8.17 ± 0.53 P value 0.336 0.006 0.008 0.019 0.008 0.074 0.111 Rhynchosia ferruginea A. Rich ( Togoo) HL 89.82 ± 0.29 b 13.45 ± 0.40 1.48 ± 0.22 10.16 ± 0.25 62.35 ± 0.85 37.41 ± 0.44 6.59 ± 0.73 b ML 92.64 ± 0.34 a 12.40 ± 0.35 1.56 ± 0.21 8.77 ± 0.95 65.93 ± 1.09 40.55 ± 1.01 10.10 ± 0.36 a LL 90.19 ± 0.56 b 13.56 ± 0.36 1.49 ± 0.19 10.21 ± 0.21 63.86 ± 0.70 37.72 ± 0.65 7.75 ± 0.88 ab Overall 90.88 ± 0.48 13.14 ± 0.26 1.52 ± 0.11 9.71 ± 0.37 64.05 ± 0.68 38.56 ± 0.62 8.15 ± 0.62 P value 0.006 0.130 0. 958 0.216 0.079 0 .044 0.030 Means with different superscripts in the columns are significantly different at P < 0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber Chemical composition of indigenous fodder trees and shrubs Table 2 shows the chemical composition (on a % DM basis) of IFTSs in three agro-ecological zones of the study area. The mean DM, EE, NDF, ADF, ADL and CF contents of Vernonia amygdalina were significantly (P < 0.05) greater in LL AEZs than in ML and LL AEZs, while the ash content was significantly (P < 0.05) greater in ML AEZs than in HL and LL AEZs. All the chemical composition variables of Erythrina abyssinica were affected (P < 0.05) by the AEZ, except for DM and CF. The ash and CP contents were significantly (P < 0.05) greater in the HL AEZs than in the ML and LL AEZs, whereas NDF, ADF and ADL were significantly (P < 0.05) greater in the LL AEZ than in the HL and ML AEZ. The results revealed that AEZ had a significant effect (P < 0.05) on the chemical composition of Maytenus undata except for the EE. The NDF, ADF, ADL and CF contents of Maytenus undata were significantly (P < 0.05) greater in the ML than in the HL and LL AEZs. However, the DM and CP contents were significantly (P < 0.05) greater in LL than in ML and HL AEZ. The DM content of IFTSs differed significantly (p < 0.05) across the AEZs. The mean DM content in the ML AEZs ranged from 88.49 ± 0.26 in Vernonia amygdalina to 94.07 ± 0.37 in Erythrina Abyssinica . The DM content of IFTSs observed in this study is in agreement with previous studies (Belete et al., 2012 ; Deribe et al. 2013 ) in which the DM content ranged from 88–94.55%. Andualem et al. ( 2015 ) reported a DM value of 57.08% for browse species, which is much lower than the mean DM content obtained in this study. The difference may be due to variations in altitude, species, soil type and climate. The mean ash content of IFTSs ranged from 7.87 ± 0.72 in Maytenus undata at LL to 13.00 ± 0.38 in Maytenus undata at HL. The ash content in IFTSs recorded in this study is consistent with the findings of Deribe et al. ( 2013 ), who reported values ranging from 8.07 to 13.39%. Andualem et al. ( 2015 ) reported an ash content of 5% DM, which is lower than the ash value obtained in this study. These differences could be attributed to differences in growth environment, genotype and stage of maturity. The mean EE content of IFTSs in this study varied from 1.78 ± 0.12% in Vernonia amygdalina at ML to 2.69 ± 0.14% DM in Erythrina abyssinica at ML. Tamene et al. (2022) also reported that the EE content of IFTSs ranged from 1.64 ± 0.04 at LL to 4.10 ± 0.03 at the ML AEZ. In this study, the average CP content of IFTSs ranged from 8.30 ± 0.44 in Erythrina abyssinica at LL to 11.85 ± 0.85 in Vernonia amygdalina at HL. The CP content in IFTSs reported in this study is greater than the recommended minimum threshold of 7% CP necessary for ruminant feed intake and optimum rumen microbial functions (Van Soest, 1994 ). The CP contents of IFTSs obtained in this study are within the range of earlier studies (Belete et al., 2012 ; Andualem et al., 2015 ), which reported CP values ranging between 8.9% and 20.9% DM for indigenous browse species. Intake declines sharply when forage contains < 7% CP (McDonald et al., 2010). According to Mekonnen et al. ( 2009 ), browse species can be used as good protein supplements for low-quality basal diets, especially during the dry season when the quality and quantity of green herbages are limited. Based on the findings of the present study, the CP content of IFTSs was greater than the acceptable threshold (7% DM CP). Thus, they have the potential to supplement low-quality crop residues and natural pastures, especially during the dry season. The NDF content of IFTSs in this study ranged between 54.43 ± 1.28% in Erythrina abyssinica at HL and 66.67 ± 0.66% DM in Vernonia amygdalina at LL. The NDF content of all IFTS species was greater than 55% DM, the level above which voluntary feed intake is limited (Van Soest, 1965). A range of 60 to 65% DM NDF is suggested as the limit above which the intake of tropical feeds by ruminants is limited (Van Soest et al., 1991 ). Vernonia amygdalina was the most fibrous, with the highest overall NDF and ADF contents of 62.42 ± 1.72% and 47.81 ± 1.29% DM, respectively. An NDF range of 35–40% has been recommended by El Shaer and Gihad (1994) to be within the normal range for nutritious fodders. The mean ADF content of IFTSs varied from 34.65 ± 1 in Maytenus undata al LL to 47.81 ± 1.29 in Vernonia amygdalina at the LL AEZ. The ADF contents of IFTSs recorded in this study are 15.55% greater than the DM reported for browse species by Andualem et al. ( 2015 ). The ADF content of all IFTSs included in this study was greater than the reported range of 17–21%, which is usually recommended for rumen stability (NRC, 2001 ). The mean ADL content of the IFTSs varied from 6.52 ± 0.74 in Maytenus undata to 11.65 ± 0.89 in Erythrina abyssinica in the LL AEZ. Khanal and Subba ( 2001 ) reported that a high ADL content can limit the voluntary feed intake, digestibility, and nutrient utilization of ruminant animals. Generally, the variation in the chemical composition of IFTSs recorded in the present study and in the literature might be due to differences in the agro-ecological zone, climatic conditions, plant species, soil fertility conditions, weather conditions during growth, and stage of maturity. Table 2 Mean (± SE) chemical composition (% DM) of indigenous fodder trees and shrubs in different AEZs of the Gera district, Ethiopia IFTSs AEZ Chemical composition (% DM) DM Ash EE CP NDF ADF ADL Vernonia amygdalina HL 92.82 ± 0.22 a 10.44 ± 0.36 ab 2.38 ± 0.08 a 11.85 ± 0.85 56.13 ± 1.66 b 38.30 ± 0.73 b 7.16 ± 0.52 ML 88.49 ± 0.26 b 11.89 ± 0.3 a 1.78 ± 0.12 b 11.05 ± 0.38 64.46 ± 1.18 a 40.35 ± 0.14 b 7.53 ± 0.47 LL 93.27 ± 0.36 a 8.64 ± 0.67 b 2.49 ± 0.07 a 9.20 ± 0.73 66.67 ± 0.66 a 47.81 ± 1.29 a 10.05 ± 1.05 Overall 91.53 ± 0.77 10.32 ± 0.53 2.22 ± 0.12 10.70 ± 0.52 62.42 ± 1.72 42.15 ± 1.5 8.25 ± 0.58 P value 0.000 0.008 0.005 0.080 0.002 0.001 0.062 Erythrina abyssinica HL 90.75 ± 0.20 11.81 ± 0.78 a 1.87 ± 0.15 a 11.76 ± 0.91a 54.43 ± 1.28 b 35.83 ± 1.43 b 7.12 ± 0.74 b ML 94.07 ± 0.37 9.21 ± 0.38 b 2.69 ± 0.14 b 10.96 ± 0.73 ab 57.11 ± 1.00 ab 36.20 ± 0.42 b 9.31 ± 0.91 ab LL 91.83 ± 0.32 9.58 ± 0.29 ab 2.32 ± 0.12 b 8.30 ± 0.44 b 61.43 ± 1.4 a 41.52 ± 0.66 a 11.65 ± 0.89 a Overall 92.22 ± 0 .51 10.20 ± 0.48 2.29 ± 0.14 10.34 ± 0.63 57.65 ± 1.19 37.85 ± 1 9.36 ± 0.77 P value 0.001 0.027 0.017 0.033 0.021 0.009 0.026 Maytenus undata HL 89.95 ± 0.38 b 13.00 ± 0.38 a 2.06 ± 0.21 8.38 ± 0.29 b 60.58 ± 0.62 ab 36.16 ± 0.81 ab 8.44 ± 0.77 ab ML 89.68 ± 0.26 b 11.45 ± 0.34 a 2.53 ± 0.25 10.09 ± 0.38 ab 63.06 ± 0.88 a 38.65 ± 0.88 a 10.35 ± 0.64 a LL 93.62 ± 0.36 a 7.87 ± 0.72 b 2.58 ± 0.26 10.83 ± 0.75 a 57.75 ± 1.15 b 34.65 ± 1 b 6.52 ± 0. 74 b Overall 91.08 ± 0.65 10.77 ± 0.79 2.39 ± 0.15 9.77 ± 0.44 60.46 ± 0.89 36.49 ± 0.74 8.44 ± 0.65 P value 0.000 0.001 0.313 0.038 0.018 0.053 0.026 Means with different superscripts in the columns are significantly different at P < 0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error; IFTSs, indigenous fodder trees and shrubs Chemical composition of improved forages Table 3 shows the chemical compositions (%DM basis) of the cultivated forage species in the three agro-ecological zones of the study area. The DM, Ash, EE, CP, NDF, ADF, ADL and CF values of Pennisetum purpureum were 89.17%, 10.86%, 1.6%, 6.9%, 66.69%, 34.57%, 12.22% and 45.92%, respectively. According to McDonald et al. (2011), the DM content of fodder and formulated feeds influences the availability of nutrients and microbial activity. The DM content of Pennisetum purpureum (89.17%) recorded in the present study is in line with the results of Gashu et al. (2017), who reported 89.5% DM. However, this value is lower than the value (91%) reported by Solomon et al. ( 2019 ). The ash content of Pennisetum purpureum (10.86%) obtained in this study is consistent with the observation of Solomon et al. ( 2019 ), who reported a value of 10.98%. The EE content of Pennisetum purpureum was very low (1.6% DM). It has been reported that EE contents of feeds above 7% DM limit the amount of feed that livestock consume (Eastridge, 2014). The CP content of Pennisetum purpureum (6.9%) observed in the present study is higher than the reported value of 5.58% (Guerra et al., 2016 ) but lower than the recommended value of 7 to 8% DM CP, which is the lowest amount of CP required for microbial growth in the rumen (Asaolu et al., 2011; Van Soest, 1994 ). The NDF in Pennisetum purpureum (66.69%) obtained in the current study is in agreement with the value of 67.11% reported by Gashu et al. (2017). The percentage of ADF in Pennisetum purpureum (34.57%) recorded in the present study is lower than the 47.45% reported by Guerra et al. ( 2016 ). The ADF value of Pennisetum purpureum is greater than the reported range of 17–21% recommended for rumen stability (NRC, 2001 ). The DM, Ash, EE, CP, NDF, ADF, ADL and CF contents of Pennisetum pedicellatum were 91.20%, 9.45%, 1.52%, 8.58%, 63.97%, 36.88%, 10.81% and 37.52% DM, respectively. The ash content of Pennisetum pedicellatum (9.45% DM) recorded in the present study is in line with the observation of Fiseha ( 2018 ), who reported a value of 9.0%. The EE content of Pennisetum pedicellatum (1.52%) recorded in this study indicated that it was a low source of energy. It has been reported that the consumption of feeds and forages with low EE contents can increase methane production, which is detrimental to the environment and further increases energy inefficiency in ruminants (Enjalbert et al. 2017). In contrast, excessive consumption of EE in ruminant livestock may impair microbial activities, limiting fiber digestibility (Eastridge, 2014). The CP values for Pennisetum pedicellatum (8.58% DM) observed in this study are not in agreement with the findings of Bezabih et al. ( 2016 ), who reported 11% CP. Generally, the CP contents of the two cultivated forages in the present study are greater than the minimum level of 7–8% DM required for optimum rumen function and feed intake in ruminants (Van Soest, 1994 ). However, it was lower than the recommended minimum requirements for lactation (12%) and growth (11.3% DM in ruminants) (ARC, 1984 ). The NDF content of Pennisetum pedicellatum (63.97%) recorded in the present study is lower than the range of 72.78 to 77.68% reported by Asmare et al. ( 2017 ). However, it is within the range of 58.82 to 63% (Bimrew et al., 2018 ). The ADF values for Pennisetum pedicellatum (36.88%) recorded in this study are consistent with the results of Genet et al. ( 2017 ), who reported values ranging from 16.63–36.14% DM. However, this value is greater than the reported range of 17–21% recommended for rumen stability (NRC, 2001 ). The ADL content of cultivated forages ranged from 10.8% in Pennisetum pedicellatum at ML to 12.22% DM in Pennisetum purpureum at HL. The high contents of ADL in cultivated forages reported in this study could have a negative influence on digestibility, which causes a decrease in the availability of nutrients. Generally, the variation in chemical composition of cultivated forages recorded in the present study and in the literature might be due to differences in agro-ecological zone, plant species, soil on which they were grown, weather conditions during growth, and the stage of maturity. Table 3 Chemical composition (% DM) of improved forages in three AEZs in the Gera district, southwest Ethiopia Improved forage Mean (± SE) chemical composition AEZ DM Ash EE CP NDF ADF ADL Pennisetum purpureum HL 89.17 10.86 1.67 8.90 66.69 34.57 12.22 Pennisetum pedicellatum ML 91.20 9.45 1.52 8.58 63.97 36.8 10.8 DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error Chemical composition of crop residues Table 4 presents the mean (± SE) chemical composition of the crop residues in the three agro-ecological zones of the study area. The results revealed that, except for NDF, all chemical composition variables of maize stover were influenced by the AEZ (P < 0.05). The mean DM, Ash, EE, ADF, ADL and CF contents of maize stover were significantly (P < 0.05) greater in the HL than in the LL and ML AEZs. The mean DM, Ash, EE, CP and CF contents of teff straw differed significantly (P < 0.05) across the AEZs, with the highest values recorded in the HL AEZs compared to those in the ML and LL AEZs. The mean EE, CP and ADF contents of wheat straw were significantly (P < 0.05) greater in the HL than in the ML and LL AEZs. The mean DM and EE contents of barley straw were significantly (P < 0.05) greater in the HL AEZs than in the ML and LL AEZs. However, the NDF and ADF contents were significantly (P 0.05) of AEZs on the DM, Ash, CP, ADF, ADL and CF contents of sorghum stover except for EE and NDF (P < 0.05), which were greater in the HL AEZs than in the ML and LL AEZs. The DM contents of maize stover, teff straw and barley straw ( Hordeum vulgare L.) differed significantly (P < 0.05) across the AEZs. The DM content of the crop residues in the present study ranged from 89.47 ± 0.53 in teff ( Eragrostis tef (Zucc) Trotter.) straw at LL to 94.28 ± 0.20 in maize ( Zea mays L .) stover at the HL AEZ. The results of the present study are in agreement with the findings of previous studies (Girma et al., 2014 ; Ararsa and Amanuel, 2021 ) reporting that the DM content of various crop residues ranged from 89.86 to 94.77% elsewhere in Ethiopia. In this study, the ash content of maize stover and teff straw varied significantly (P < 0.05) in response to the AEZ. The average ash content of crop residues ranged from 6.94 ± 0.24% in sorghum stover at LL to 11.61 ± 0.57% DM in wheat straw at the HL AEZ. The mean ash content in sorghum stover, maize stover and teff straw recorded in the current study was higher than the ash values reported by Tikabo and Shumuye (2021). There was a significant difference (P < 0.05) in the EE content of crop residues (P < 0.05) across the studied AEZs. The average EE content of crop residues ranged from 1.29 ± 0.08 in wheat straw at ML to 2.41 ± 0.09% in barley straw at HL AEZ. The EE contents of maize stover and wheat straw were greater in the HL treatment than in the ML treatment. However, the EE content of wheat ( Triticum aestivum L .) straw was lower at the ML, and that of sorghum stover was lower at the LL AEZ. The CP contents of maize stover, teff straw and wheat straw varied significantly (P < 0.05) across the AEZs. The CP content of crop residues ranged from 2.43 ± 0.13 for wheat straw at the ML to 4.81 ± 0.35 for barley straw at the HL AEZ. These low CP contents of crop residues might be attributed to the age of the crops that were harvested after the seeds had dried well before they were harvested. The CP content of crop residues recorded in the present study was much lower than the minimum level of 7% required for rumen microbial function (Van Soest, 1982 ). The CP content of crop residues in this study was in agreement with the CP values of < 7% for maize stover, teff straw, wheat straw, barley straw and sorghum stover reported by Deribe et al. (2019). Nasrullah et al. ( 2003 ) stated that voluntary feed intake decreases rapidly if the CP content of roughages is below 6.2% DM. Cereal straws generally have a low nitrogen content and are composed of cell wall components with little soluble cell content (Preston and Leng, 1986 ). The NDF content of the crop residues did not vary significantly (P > 0.05) across the AEZs except for those of barley straw and sorghum stover. The NDF content in crop residues ranged between 70.61 ± 1.17 in sorghum stover at LL and 79.95 ± 3.02 in maize stover at HL. All crop residues reported in this study had NDF contents greater than 65% DM and were classified as low-quality roughages (Singh and Oosting, 1992 ). Similar to the findings of the present study, Sisay ( 2006 ) also reported NDF contents of crop residues higher than 70% DM. It has been reported that as plants mature, the NDF, ADF and lignin contents increase, while the CP content decreases (Mahala et al., 2009 ), emphasizing that an increase in these parameters is influenced by the maturity stage of the crop residues. Feds with NDF contents less than 45%, 45–65% and greater than 65% are considered to be of high, medium and low quality, respectively (Bogale et al., 2008 ; Mpairwe et al., 2002 ). A high NDF above 72% will cause a low intake of forage (Lima et al., 2002 ), and as NDF values increase, DM intake generally decreases (Schroeder, 2012 ). The ADF contents of maize stover, wheat straw and barley straw varied significantly (P < 0.05) across the studied AEZs. The ADF content of crop residues ranged from 48.26 ± 0.38 in wheat straw at HL to 60.31 ± 1.61 in sorghum stover at the LL AEZ. A high ADF content in crop residues could result in lower digestibility since the digestibility of feed and its ADF content are negatively correlated (McDonald et al., 2002 ). Feeds with ADF contents less than 30% and greater than 40% are considered to be of high quality and poor quality, respectively (Mpairwe et al., 2002 ). The ADF content of crop residues in this study was greater than 48% DM, indicating their low digestibility. Agro-ecology influenced the ADL content of maize stover only (P < 0.05). The ADL content of crop residues varied from 7.52 ± 0.49 in teff straw at HL to 13.34 ± 0.55 in wheat straw at ML. The findings of the present study are consistent with the results of Gashaw and Defar ( 2017 ), who reported ADL contents of 8.07, 9.22 and 10.30% DM for barley straw, teff straw and wheat straw, respectively. ADL represents an indigestible portion of rough materials and forms complexes with cellulose and hemicellulose constituents through lignification, thereby impairing microbial digestion. According to Van Soest ( 1982 ), an ADL content above 6% has a negative impact on the digestibility of forage. Therefore, all crop residues included in this study had ADL contents above this recommended level, resulting in low digestibility by ruminants. Generally, the variation in the chemical composition of crop residues between the present study and the literature might be due to differences in the agro-ecological zone, climatic conditions, soil fertility on which the crop was grown, weather conditions during growth, and maturity stage. Table 4 Chemical composition (% DM) of crop residue from three AEZs in the Gera district, southwest Ethiopia Crop residue AEZ Chemical composition (Mean ± SE) DM ASH EE CP NDF ADF ADL HL 94.28 ± 0.20 b 9.82 ± 0.94 b 2.17 ± 0.12 b 3.24 ± 0.13 a 79.95 ± 3.02 56.88 ± 1.45 b 9.49 ± 0.35 b Maize stover ML 93.90 ± 0.08 b 9.23 ± 0.33 b 2.01 ± 0.03 b 3.75 ± 0.11 ab 74.73 ± 1.43 52.17 ± 1.35 ab 8.75 ± 0.29 ab LL 90.94 ± 0.24 a 6.11 ± 0.45 a 1.47 ± 0.16 a 4.09 ± 0.19 a 70.51 ± 1.06 49.62 ± 0.46 a 7.80 ± 0.16 a Overall 93.04 ± 0.54 8.39 ± 0.65 1.88 ± 0.12 3.69 ± 0.14 74.06 ± 1.38 52.89 ± 1.21 8.68 ± 0.28 p- value 0.000 0.013 0.013 0.020 0.154 0.013 0.015 Teff straw HL 93.31 ± 0.09 c 8.98 ± 0.38 b 1.74 ± 0.04 b 4.38 ± 0.33 b 79.30 ± 2.07 51.87 ± 1.15 7.52 ± 0.49 ML 91.42 ± 0.14 b 8.14 ± 0.12 ab 1.43 ± 0.09 ab 3.94 ± 0.06 ab 77.82 ± 0.98 54.71 ± 0.54 7.80 ± 0.22 LL 89.47 ± 0.53 a 7.67 ± 0.25 a 1.39 ± 0.06 a 3.36 ± 0.10 a 78.31 ± 1.43 56.42 ± 1.34 9.61 ± 0.67 Overall 91.40 ± 0.57 8.26 ± 0.24 1.52 ± 0.06 3.89 ± 0.17 78.47 ± 0.81 54.33 ± 0.85 8.31 ± 0.41 p- value 0.000 0.040 0.031 0.036 0.80 0.061 0.056 Wheat straw HL 93.89 ± 0.28 11.61 ± 0.57 1.38 ± 0.05 3.37 ± 0.14 80.36 ± 1.32 48.26 ± 0.38 11.97 ± 0.93 ML 92.37 ± 0.57 10.76 ± 0.32 1.29 ± 0.08 2.43 ± 0.13 77.95 ± 1.48 53.79 ± 1.60 13.34 ± 0.55 Overall 93.13 ± 0.44 11.18 ± 0.35 1.33 ± 0.04 2.90 ± 0.22 79.16 ± 1.04 51.03 ± 1.44 12.65 ± 0.57 p- value 0.079 0.271 0.047 0.008 0.292 0.028 0.274 Barley straw HL 93.56 ± 0.35 10.74 ± 0.45 2.41 ± 0.09 4.81 ± 0.35 71.93 ± 0.34 50.71 ± 1.24 9.51 ± 0.92 ML 89.73 ± 0.51 10.13 ± 0.05 1.49 ± 0.03 4.47 ± 0.15 75.50 ± 0.56 56.67 ± 1.16 10.71 ± 0.96 Overall 91.65 ± 0.90 10.43 ± 0.25 1.95 ± 0.21 4.64 ± 0.18 73.72 ± 0.85 53.69 ± 1.53 10.11 ± 0.65 p- value 0.004 0.262 0.001 0.436 0.006 0.025 0.420 Sorghum stover ML 94.26 ± 0.14 7.54 ± 0.21 1.66 ± 0.06 3.93 ± 0.36 79.09 ± 1.8 58.51 ± 1.18 9.44 ± 0.81 LL 93.45 ± 0.79 6.94 ± 0.24 1.18 ± 0.02 3.16 ± 0.72 70.61 ± 1.17 60.31 ± 1.61 11.21 ± 0.58 Overall 93.85 ± 0.401 7.24 ± 0.19 1.42 ± 0.11 3.55 ± 0.24 74.85 ± 2.13 59.41 ± 0.98 10.32 ± 0.59 p- value 0.374 0.140 0.002 0.107 0.018 0.421 0.150 Means with different superscripts in the columns are significantly different at P < 0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error CONCLUSIONS Overall, the agro-ecological zone had a significant effect on most of the chemical composition variables of the feedstuffs evaluated in this study. This might be due to variations in soil type, organic matter content, temperature and rainfall. The indigenous fodder tree and shrub species had greater CP and lower NDF, implying their potential to supplement poor quality feeds such as crop residues, stubble and dry natural pasture grasses, especially during the dry season. On the other hand, crop residues had the lowest CP below the minimum threshold required for the activity of rumen microorganisms and maintenance requirements of ruminants and the highest NDF, implying the need to either improve their nutritive value through urea treatment or supplement animals with protein-rich feeds. Generally, agro-ecology was found to be a key variable influencing the chemical composition of the feedstuffs included in this study. Further evaluation of the nutritive values and mineral contents of these feed resources is essential. Moreover, further animal-based trials involving these feeds are needed to substantiate the findings of the present study on animal performance. Declarations Acknowledgments The authors wish to thank Jimma University for financial support and laboratory technicians at the Animal Nutrition Laboratory of the department of Animal Science, College of Agriculture and Veterinary Medicine, Jimma University. Data availability All data that support the findings of this study are available on request from the corresponding author. Funding The authors acknowledge: Jimma University, College of Agriculture and Veterinary Medicine Research Affairs for supporting the Master’s programme of Hassen Abazinab in sample analysis. Author information Authors and affiliations Jimma Zone Livestock and Fisheries Development Agency, Jimma, Oromia, Ethiopia Department of Animal Science, College of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Oromia, Ethiopia Contributions This work was generated from a Master of Science research work done by HA under the supervision of BD and EM as Postgraduate supervisors. Corresponding author Correspondence to Belay Duguma Ethics declarations Ethics approval and consent to participate Ethical approval for this study was obtained from Jimma University, College of Agriculture and veterinary medicine Ethics Committee. Informed consents were also obtained from all farmers before data collection in conformity for anonymity of the study participants. Competing interests The authors declare no competing interests. References Abazinab, H., Duguma, B., Muleta, E., 2022. 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Nutritive evaluation of natural pasture at early and late rainfall season in Kordofan and Butana, Sudan. Australian Journal of Basic and Applied Science 3: 4327-4332. McDonald, P., Edward, R.A., Greenhalgh, J.F. D., Morgan, G.A., 2002. Animal Nutrition (6th ed.), Pearson Educational Limited, Edinburgh, Great Britain, pp. 544. Meissner H.H., Viljoen M.O., van Niekerk W.A. (1991): Intake and digestibility by sheep of Antherphora, Panicum, Rhodes and Smooth finger grass. In: Proc. 4th International Rangeland Congress, September 17th–21st, Montpellier, France. Mekonnen, K.., Glatze, L.G., Sieghard, T.M. 2009. Assessments of fodder values of 3 indigenous and 1 exotic woody plant species in the HLs of Central Ethiopia. Mount. Reg. Develop., 29 (2009), pp. 135-142. Mpairwe, D. R., Sabiiti, E. N., Ummuna, N. N., Tegegne, A., & Osuji, P. (2002). Effect of intercropping cereal crops with forage legumes and source of nutrients on cereal grain yield and fodder dry matter yields. African Crop Science Journal, 10 (1), 1–14. Nasrullah M.N., Akhasi R., Kawamure O. (2003): Nutritive value of forage plants grown in South Sulawesi, Indonesia. Asian-Australian Journal of Animal Science, 16, 693–701. NRC, 2001. Nutrient requirements of dairy cattle: 2001 , (7th ed.). National Research Council, National Academies Press. NRC, 2007. Nutrient requirements of cattle, 6th edition, Washington DC, National Academy Press. Odedire J.A., Babayemi O.J. (2008): Comparative studies on the yield and chemical composition of Panicum maximum and Andropogon gayanus as influenced by Tephrosia candida and Leucaena leucocephala . Livestock Research for Rural Development, 20, 2. Preston, T.R. and R.A. Leng. 1986. Matching Livestock Production Systems to Available Resources. IlCA, Addis Ababa, Ethiopia. Reed, J.A. and M.R. Goe, 1989. Estimating the nutritive value of cereal crop residues: implications for developing feeding standards for draught animals. ILCA. Bulletin No. 4 ILCA, Addis. Riaz MQ, Südekum K-H, Clauss M, Jayanegara A (2014) Voluntary feed intake and digestibility of four domestic ruminant species as influenced by dietary constituents: a meta-analysis. Livestock Science 162, 76–85. doi:10.1016/j.livsci.2014.01.009 Schroeder J., 2012. Interpreting Forage Analysis. North Schroeder J., 2012. Interpreting Forage Analysis. North Dakota: NDSU Extension Service. Shapiro BI, Gebru G, Desta S, Negassa A, Nigussie K, Aboset G, and Mechale H. 2017. Ethiopia livestock sector analysis . ILRI (International Livestock Research Institute) Project Report. Nairobi, Kenya. Singh G. and S. Oosting, “A model for describing the energy value of straws,” Indian dairyman , 75, 1992. Singh, B. B., Musa, A., Ajeigbe, H. A. and Tarawali, S. A.(2011) Effect of feeding crop residues of different cereals and legumes on weight gain of Yankassa rams. International Journal of Livestock Production, 2: 017–023. Sisay, A., 2006. Qualitative and Quantitative Aspects of Animal Feed in Different Agro ecological Areas of North Gonder. MSc. Thesis. Alemaya University, Dire Dawa. Skerman, P.J., and Riveros, F. 1990. Tropical grasses. Rome: Food Agriculture Organization of the United Nations. Solomon, T., Bimrew, A., Firew, T., 2019. Farmers’ utilization practice, yield and chemical composition of selected improved forages grown in natural resource management areas of Farta District, South Gondar Zone, Ethiopia. Cogent Food & Agriculture, 5, 1. Tamene Bayissa, Belay Duguma, and Kassahun Desalegn, 2022.Chemical composition of major livestock feed resources in the medium and low agro-ecological zones in the mixed farming system of Haru District, Ethiopia. Heliyon 8 (2022) e09012. Tikabo G., and Shumuye B.,2021.Chemical Composition and Digestibility of Major Feed Resources in Tanqua-Abergelle District of Central Tigray, Northern Ethiopia. African Journal of Agricultural Research, 7(4), 19-13. Tolera, A., Yami, A., Alemu, D., 2012. Livestock feed resources in Ethiopia: Challenges, Opportunities and the need for transformation. Ethiopia Animal Feed Industry Association, Addis Ababa, Ethiopia. Topps, JH. 1993. Assessment of forage legumes as protein rich supplements in ruminant production systems in Zimbabewe. Proceedings of the 2nd African feed Resource Network (AFRNET) Workshop, Dec. 6-10, Nairobi, Kenya, pp:69-70. Van Soest, P. and J. Robertson, Analysis of Forages and FibrousFood , Cornell University, Ithaca, NY, USA, 1985. Van Soest, P.J. 1982. Analytical systems for evaluation of feeds. Nutritional ecology of the ruminant . Van Soest, P.J. 1994. Nutritional ecology of the ruminant. Cornell University, Ithaca. P. 476 Van Soest, P.J., 1994. Nutritional ecology of the ruminant. 2nd Edition, Cornell University Press, Ithaca, 476. Van Soest, P.J., Robertson, J.B. 1979. Systems of analysis for evaluating fibers feed. In: Pigden, W.J., C.C. Balch and Michael Graham (Eds.), Standardization of Analytical Methodology for Feeds. Workshop proceeding, 12-14 March, Ottawa, Canada, pp. 49-60. Van Soest, P.J., Robertson, J.B., Lewis, B.A., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci. 7 4, 3583–3597. Zewdie, W., 2010. Livestock production systems in relation with feed availability in the HLs and Central Rift valley of Ethiopia. M.Sc. thesis submitted to the School of Animal and Range Sciences, School of Graduate studies Haramaya University, Ethiopia. Additional Declarations No competing interests reported. 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According to the Central Statistical Agency (CSA, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the country has approximately 70\u0026nbsp;million head of cattle, 42.9\u0026nbsp;million head of sheep, 52.5\u0026nbsp;million head of goats, 2.15\u0026nbsp;million head of horses, 10.80\u0026nbsp;million head of donkeys, 0.38\u0026nbsp;million head of mules, 8.1\u0026nbsp;million head of camels, and 56.87\u0026nbsp;million head of poultry at the country level. Despite having one of the largest livestock populations, its productivity has remained very low. This is mainly attributed to feed shortages both in quality and quantity (Tolera et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLivestock production contributes approximately 17-25.3% of gross domestic product (GDP), 39\u0026ndash;49% of agricultural GDP and more than 50% of household income in Ethiopia (Shapiro, 2017\u003cb\u003e)\u003c/b\u003e. In addition, livestock supplies meat, milk and eggs as sources of protein and significantly contributes to the sustainability of crop production through the provision of draught power and manure for soil fertilization, transportation, income, employment, manure for soil fertility management, and security to reduce the risk of crop failure, live banks, wealth storage, and social prestige for rural farmers (Dereje et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the large population, animal productivity in Ethiopia is poor, even below the values recorded for the majority of the countries in eastern and sub-Saharan Africa (Gebreegziabher, 2010). The major constraints are low-productivity feed scarcity in terms of quality and quantity, low genetic potential of indigenous livestock, a high incidence of disease and parasites, traditional management practices, poor access to extension and credit services and a lack of knowledge to improve animal performance (Aynalem et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Birhan and Adugna, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Defar, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Of these, poor-quality feed resources were identified as the greatest constraint limiting livestock productivity (Defar, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNatural pasture, crop residues, hay, agro-industrial byproducts, improved feed and other products, such as animal byproducts and vegetable and fruit wastes, are livestock feed resources available in Ethiopia (CSA, 2020). Of these, natural pasture and crop residues are major feed resources but are characterized by low digestibility and crude protein content, which adversely affects livestock productivity (Shapiro et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In southern Ethiopia, Deribe et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reported that the CP contents of grass species and crop residues ranged from 1.42%-18.95% and 2.01\u0026ndash;8.97% DM, respectively. In terms of quality, cereal crop residues are generally of low nutritive value because of their relatively low CP ranging from 2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16% to 7.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09% and high NDF ranging from 72.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26 to 78.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77% in western Ethiopia (Tamene et al., 2022). Leng (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) defined low-quality forage as those with a CP value\u0026thinsp;\u0026lt;\u0026thinsp;8% and suggested the supplementation of such forages with appropriate nutrients to achieve high levels of animal production.\u003c/p\u003e \u003cp\u003eAbeysekara (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) reported that the quality of feeds reveals the nutrient (chemical) composition, palatability and intake, digestibility, antinutritional factors and animal production performance. Most of the forages from natural pastures and crop residues contain CP below 7% and NDF above 55% DM (Solomon et al., 2008), both of which indicate poor nutritive value incapable of meeting rumen microbial requirements, particularly with regard to CP content (Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Leng (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) also indicated that low-quality forages, such as those with less than 8% DM CP content, adversely affect rumen microbial activity (Van Soest, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). It has been stated that a CP content of approximately 15% DM for high milk production (\u0026gt;\u0026thinsp;15 kg/cow/day) and 8 to 13% for moderate milk production (10\u0026ndash;15 kg/cow/day) are required by dairy cows (ARC, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Humphreys, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1991\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe total NDF content of forage is a dominant factor in determining forage quality (Gezahagn et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The NDF content of feeds above 60% and 50 to 60% DM are classified as poor and moderate quality feed, respectively (Van Soest, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). A greater amount of forage ADF results in reduced digestibility of dry matter as a consequence of increased lignification of cellulose in plants (Depeters, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Kellems and Church (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) categorized roughages with less than 40% ADF as high quality and those with more than 40% ADF as low quality. The lignin content of feeds and forages affects the digestibility of forage more than any other chemical component of feeds (Van Soest and Robertson, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Van Soest, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). According to Van Soest (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e), a lignin content above 6% DM negatively affects the digestibility of forage.\u003c/p\u003e \u003cp\u003eDeficiency of feed in terms of quantity and quality negatively affects the productive and reproductive performance of grazing livestock (Compbell et al., 2003. According to the National Research Council (NRC) (2007), optimum productive and reproductive performance of livestock can be achieved only when the animals are fed the required quantity of feedstuffs containing all the nutrients in the proper amount. Precise information on feed composition with respect to proximate composition and fiber fractions is essential for assessing the nutritional status of feeds and fodders and of the animals to which these feeds and fodders are fed (Ganai et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study area, natural pasture, crop residues, indigenous fodder trees and shrubs, and, to a lesser extent, improved forages are the most important feed resources for livestock. However, there is no information on their chemical composition. This lack of information could limit the formulation of balanced rations for better utilization of available feed resources to improve livestock productivity. Thus, the results of this study will help to fill this information gap and provide the basis for generating empirical evidence to improve feed quality to improve livestock productivity. With this insight, the objective of this study was to evaluate and compare the chemical composition of major feed resources obtained from three agro-ecological zones of the Gera district, southwest Ethiopia.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the study area\u003c/h2\u003e \u003cp\u003eThis study was conducted in the Gera district of the Jimma zone, Oromia Regional State, southwest Ethiopia. A detailed description of the study area can be found in a previously published companion study (Abazinab et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFeed sampling\u003c/h2\u003e \u003cp\u003eRepresentative samples of 13 different feedstuffs which farmers were feeding to their animals, including three natural pasture species (\u003cem\u003eCynodon dactylon, Pavoniaschimperiana Hochst and Rhynchosia ferruginea)\u003c/em\u003e, three indigenous fodder trees and shrubs (\u003cem\u003eErythrina Abyssinica, Vernonia amygdalina, and Maytenus undat\u003c/em\u003e), two cultivated forages (\u003cem\u003ePennisetum purpureum and Pennisetum pedicellatum\u003c/em\u003e) and five crop residues (\u003cem\u003eHordeum vulgare, Zea mays stover, Sorghum bicolor stover, Triticum aestivum straw\u003c/em\u003e and \u003cem\u003eEragrostis tef\u003c/em\u003e straw) were randomly collected from the HL, ML and LL AEZs of the Gera District following appropriate procedures. Samples of natural pasture were collected using a 0.5m x 0.5m quadrate from each selected grazing sites in each AEZ using sickle. The quadrate was thrown on the selected sites and harvested the whole plant at grazing height of about 5cm above the ground. For indigenous fodder trees and shrubs, edible green leaves and twigs were hand harvested from all four directions in the lower, middle, and top portions of the canopy in each agro-ecological zone. All samples of crop residues stems (including leaves, stems or stalks) were collected from fields after crops had been harvested and/or threshed under traditional practices. The crops were harvested when the plants were dry. After sampling, the same feed samples collected from highland midland and lowland agro-ecological zone were bulked together, mixed thoroughly and sub-sampled to make one composite sample. The fresh samples of native grasses, improved forages and IFTSs were weighed, sun-dried and stored in polythene bags. Chemical analyses of feed samples were performed at Animal Nutrition Laboratory of the Department of Animal Science, College of Agriculture and Veterinary Medicine, Jimma University for proximate analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory analysis\u003c/h2\u003e \u003cp\u003eIn the laboratory, all samples were oven dried at 65\u0026deg;C for 24 hours, milled to pass through a 1 mm mesh sieve, and analyzed on a % DM basis, except for DM, which is expressed as % fresh matter. The samples were analyzed for DM, ash, CP, EE and CF by the procedures of the AOAC (2005). The DM content was determined by drying the samples at 105\u0026deg;C overnight to a constant weight. Ash content was determined by igniting the ground samples at 550\u0026deg;C for 6 hours in a muffle furnace. The nitrogen (N) content was determined by the Kjeldahl method, and CP was calculated as N \u0026times; 6.25. The fiber fractions (NDF, ADF and ADL) were determined using the method of Van Soest et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The samples were analyzed in duplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were subjected to analyses of variance (ANOVAs) using the Statistical Package for Social Sciences (SPSS) Program Version 20.0. The differences between means were separated by Duncan's multiple range test using the IBM SPSS Statistics Programme, Version 20.0. Differences were considered significant when P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The results are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors (SEs).\u003c/p\u003e \u003cp\u003eThe statistical model used for data analysis was as follows:\u003c/p\u003e \u003cp\u003eYij\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;αi\u0026thinsp;+\u0026thinsp;Σij\u003c/p\u003e \u003cp\u003ewhere Yij is the response of the parameter/variable investigation; DM, Ash, CP, CF, EE, NDF, ADF and ADL\u003c/p\u003e \u003cp\u003e\u0026micro;\u0026thinsp;=\u0026thinsp;overall mean\u003c/p\u003e \u003cp\u003eαI\u0026thinsp;=\u0026thinsp;the effect of i\u003csup\u003eth\u003c/sup\u003e location/agro-ecology (I\u0026thinsp;=\u0026thinsp;HL, ML, LL)\u003c/p\u003e \u003cp\u003eΣij\u0026thinsp;=\u0026thinsp;random error\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eChemical compositions of forage species in natural pastures\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the chemical composition (% DM) of the natural pastures in the three agro-ecological zones of the study area. The results showed that the mean DM, ash, EE, CP, NDF, ADF, and CF of natural pastures ranged from 89.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29 \u003cem\u003ein Rhynchosia ferruginea A. Rich\u003c/em\u003e at HL to 93.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 \u003cem\u003ein C. dactylon\u003c/em\u003e at LL, from 7.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39 in \u003cem\u003eC. dactylon\u003c/em\u003e at LL to 14.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 in \u003cem\u003ePavonia Schimperiana Hochst\u003c/em\u003e at HL, from 1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 in \u003cem\u003ePavonia Schimperiana Hochst\u003c/em\u003e at ML to 1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 \u003cem\u003ein C. dactylon\u003c/em\u003e at HL, 7.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72 \u003cem\u003ein Pavonia Schimperiana Hochst\u003c/em\u003e at ML to 11.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 \u003cem\u003ein C. dactylon\u003c/em\u003e at HL, 61.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 \u003cem\u003ein Pavonia Schimperiana Hochst\u003c/em\u003e at HL to 69.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 \u003cem\u003ein C. dactylon\u003c/em\u003e at LL, 37.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 \u003cem\u003ein Rhynchosia ferruginea A. Rich\u003c/em\u003e at HL to 47.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 \u003cem\u003ein C. dactylon\u003c/em\u003e at LL, and 6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.\u003c/p\u003e \u003cp\u003eThe DM, Ash, EE, CP, NDF, ADF, ADL and CF values of \u003cem\u003eCynadon dactylon\u003c/em\u003e ranged from 90.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 to 93.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26, 9.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31 to 9.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68, 1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 to 1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12, 7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14 to 11.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44, 61.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 to 69.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44, 38.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 to 47.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46, 6.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73 to 11.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92, and 34.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38 to 43.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88, respectively. Variation in AEZ significantly (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e) influenced the chemical composition parameters of \u003cem\u003eCynadon dactylon\u003c/em\u003e. The DM, NDF, AD, AD, and CF contents of \u003cem\u003eC. dactylon\u003c/em\u003e were significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater at LL compared to other AEZS, whereas CP content was greater (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) at HL than ML and LL. AEZ had no effect on the ash or EE content of \u003cem\u003eC. dactylon\u003c/em\u003e (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These variations might be due to climatic conditions, soil fertility, and harvesting stage.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePavonia schimperiana\u003c/em\u003e from HL exhibited significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater ash values than those from ML and LL, whereas CP and EE were greater at LL, and NDF was greater at ML than at other AEZs. The DM, ADF and ADL contents of \u003cem\u003eRhynchosia ferruginea A. Rich\u003c/em\u003e in ML were significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater than those in HL and LL. The other chemical composition parameters did not vary among the agro-ecological zones. The variations observed in the various chemical composition parameters among the different species in the AEZs might be due to differences in climatic conditions, soil fertility and stage of maturity.\u003c/p\u003e \u003cp\u003eThe DM values of the natural pasture species observed in this study are greater than the recommended range of 70\u0026ndash;80% and may limit feed intake by livestock (Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe CP content of the natural pasture obtained in this study was greater than the minimum of 7\u0026ndash;8% DM for optimum rumen microbial function and maintenance requirements of ruminants (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). However, our results are lower than the minimum recommended values of 12% for lactation and 11.3% DM for growth in ruminants (ARC, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1984\u003c/span\u003e), indicating the need for supplementation with high-protein feeds. The voluntary intake of ruminants decreases when the CP level is below 6\u0026ndash;7% DM (ARC, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Minson, 1990).\u003c/p\u003e \u003cp\u003eThe EE content of natural pasture species observed in the present study was lower than the minimum recommended value of 5% DM, indicating a lower energy level for the animal (Odedire and Babayemi, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Fats, as livestock feed, function much like carbohydrates in that they serve as a source of heat and energy and for the formation of fat due to the larger proportion of carbon and hydrogen.\u003c/p\u003e \u003cp\u003eThe overall mean NDF content of the natural pasture recorded in this study was greater than the critical value of 60% (Reed and Goe, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), which may have resulted in decreased voluntary feed intake and feed conversion efficiency and increased rumination time. Roughage feeds with NDF contents less than 45, 45\u0026ndash;65, and greater than 65% are considered high-, medium-, and low-quality, respectively (Singh Oosting, 1992). It has been reported that 36% NDF is ideal for forage for domestic animals, but greater than 36% NDF limits of intake due to rumen fill, and less than 36% NDF results in insufficient fiber for rumen scratch factor and proper rumen function (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The higher NDF level of the natural pasture in this study might be due to its high maturity, which provided a chance for fiber accumulation in plant tissues.\u003c/p\u003e \u003cp\u003eIn this study, the ADF content in natural pastures ranged from 37.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 in \u003cem\u003eRhynchosia ferruginea A. Rich\u003c/em\u003e at HL to 47.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 in \u003cem\u003eCynodon dactylon\u003c/em\u003e at LL. These results are higher than the recommended level of 18\u0026ndash;20% DM (Riaz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and the range of 17\u0026ndash;21%, which is usually recommended for rumen stability (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). ADF contents greater than 40% are considered low quality, whereas those less than 40% are considered high quality (Kellems and Church, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Based on this classification, the ADF contents of the natural pastures observed in this study were classified as both good and poor quality.\u003c/p\u003e \u003cp\u003eThe ADL content of the natural pasture in this study ranged from 6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73 in \u003cem\u003eRhynchosia ferruginea A. Rich at\u003c/em\u003e HL to 11.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92 in \u003cem\u003eCynodon dactylon\u003c/em\u003e at LL. Of the components of the cell wall, lignin is considered the main factor limiting feed intake, fiber degradation in the rumen, the rate of organic matter fermentation, the number of microbial cells produced per unit of fermented organic matter, and the proportion of propionate to acetate in the products of fermentation (Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Van Soest and Robertson, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). The percentage of fiber that is digested may be less than 60% in feed that contains 10% DM of lignin (McDowell, 1985). Generally, the variations in the chemical composition of natural pastures between the present study and the literature might be due to environmental conditions, climatic conditions, plant type and species, soil fertility, weather conditions during growth, and stage of maturity variation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical composition (% DM) of natural pastures in three AEZs of Gera District, southwest Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eChemical composition (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAEZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eDM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eAsh\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eEE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eCP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eNDF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eADF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eADL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eCynadon dactylon\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003ePavonia\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eSchimperiana Hochst\u003c/em\u003e (kalalaa)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eRhynchosia ferruginea A. Rich (\u003c/em\u003eTogoo)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0. 958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 .044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMeans with different superscripts in the columns are significantly different at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eChemical composition of indigenous fodder trees and shrubs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the chemical composition (on a % DM basis) of IFTSs in three agro-ecological zones of the study area. The mean DM, EE, NDF, ADF, ADL and CF contents of \u003cem\u003eVernonia amygdalina\u003c/em\u003e were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in LL AEZs than in ML and LL AEZs, while the ash content was significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in ML AEZs than in HL and LL AEZs.\u003c/p\u003e \u003cp\u003eAll the chemical composition variables of \u003cem\u003eErythrina abyssinica\u003c/em\u003e were affected (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) by the AEZ, except for DM and CF. The ash and CP contents were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the HL AEZs than in the ML and LL AEZs, whereas NDF, ADF and ADL were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the LL AEZ than in the HL and ML AEZ. The results revealed that AEZ had a significant effect (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on the chemical composition of \u003cem\u003eMaytenus undata\u003c/em\u003e except for the EE. The NDF, ADF, ADL and CF contents of \u003cem\u003eMaytenus undata\u003c/em\u003e were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the ML than in the HL and LL AEZs. However, the DM and CP contents were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in LL than in ML and HL AEZ.\u003c/p\u003e \u003cp\u003eThe DM content of IFTSs differed significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the AEZs. The mean DM content in the ML AEZs ranged from 88.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 in \u003cem\u003eVernonia amygdalina\u003c/em\u003e to 94.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37 in \u003cem\u003eErythrina Abyssinica\u003c/em\u003e. The DM content of IFTSs observed in this study is in agreement with previous studies (Belete et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Deribe et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) in which the DM content ranged from 88\u0026ndash;94.55%. Andualem et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported a DM value of 57.08% for browse species, which is much lower than the mean DM content obtained in this study. The difference may be due to variations in altitude, species, soil type and climate.\u003c/p\u003e \u003cp\u003eThe mean ash content of IFTSs ranged from 7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72 in \u003cem\u003eMaytenus undata\u003c/em\u003e at LL to 13.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38 in \u003cem\u003eMaytenus undata\u003c/em\u003e at HL. The ash content in IFTSs recorded in this study is consistent with the findings of Deribe et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who reported values ranging from 8.07 to 13.39%. Andualem et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported an ash content of 5% DM, which is lower than the ash value obtained in this study. These differences could be attributed to differences in growth environment, genotype and stage of maturity. The mean EE content of IFTSs in this study varied from 1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12% in \u003cem\u003eVernonia amygdalina\u003c/em\u003e at ML to 2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14% DM in \u003cem\u003eErythrina abyssinica\u003c/em\u003e at ML. Tamene et al. (2022) also reported that the EE content of IFTSs ranged from 1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 at LL to 4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 at the ML AEZ.\u003c/p\u003e \u003cp\u003eIn this study, the average CP content of IFTSs ranged from 8.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 in \u003cem\u003eErythrina abyssinica\u003c/em\u003e at LL to 11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85 in \u003cem\u003eVernonia amygdalina\u003c/em\u003e at HL. The CP content in IFTSs reported in this study is greater than the recommended minimum threshold of 7% CP necessary for ruminant feed intake and optimum rumen microbial functions (Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The CP contents of IFTSs obtained in this study are within the range of earlier studies (Belete et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Andualem et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which reported CP values ranging between 8.9% and 20.9% DM for indigenous browse species. Intake declines sharply when forage contains\u0026thinsp;\u0026lt;\u0026thinsp;7% CP (McDonald et al., 2010). According to Mekonnen et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), browse species can be used as good protein supplements for low-quality basal diets, especially during the dry season when the quality and quantity of green herbages are limited. Based on the findings of the present study, the CP content of IFTSs was greater than the acceptable threshold (7% DM CP). Thus, they have the potential to supplement low-quality crop residues and natural pastures, especially during the dry season.\u003c/p\u003e \u003cp\u003eThe NDF content of IFTSs in this study ranged between 54.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28% in \u003cem\u003eErythrina abyssinica\u003c/em\u003e at HL and 66.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66% DM in \u003cem\u003eVernonia amygdalina\u003c/em\u003e at LL. The NDF content of all IFTS species was greater than 55% DM, the level above which voluntary feed intake is limited (Van Soest, 1965). A range of 60 to 65% DM NDF is suggested as the limit above which the intake of tropical feeds by ruminants is limited (Van Soest et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). \u003cem\u003eVernonia amygdalina\u003c/em\u003e was the most fibrous, with the highest overall NDF and ADF contents of 62.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72% and 47.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29% DM, respectively. An NDF range of 35\u0026ndash;40% has been recommended by El Shaer and Gihad (1994) to be within the normal range for nutritious fodders.\u003c/p\u003e \u003cp\u003eThe mean ADF content of IFTSs varied from 34.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1 in \u003cem\u003eMaytenus undata\u003c/em\u003e al LL to 47.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29 in \u003cem\u003eVernonia amygdalina\u003c/em\u003e at the LL AEZ. The ADF contents of IFTSs recorded in this study are 15.55% greater than the DM reported for browse species by Andualem et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The ADF content of all IFTSs included in this study was greater than the reported range of 17\u0026ndash;21%, which is usually recommended for rumen stability (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mean ADL content of the IFTSs varied from 6.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74 in \u003cem\u003eMaytenus undata\u003c/em\u003e to 11.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89 in \u003cem\u003eErythrina abyssinica\u003c/em\u003e in the LL AEZ. Khanal and Subba (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) reported that a high ADL content can limit the voluntary feed intake, digestibility, and nutrient utilization of ruminant animals. Generally, the variation in the chemical composition of IFTSs recorded in the present study and in the literature might be due to differences in the agro-ecological zone, climatic conditions, plant species, soil fertility conditions, weather conditions during growth, and stage of maturity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SE) chemical composition (% DM) of indigenous fodder trees and shrubs in different AEZs of the Gera district, Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIFTSs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAEZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eChemical composition (% DM)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eADF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eVernonia amygdalina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.82\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eErythrina abyssinica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0 .51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eMaytenus undata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0. 74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMeans with different superscripts in the columns are significantly different at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error; IFTSs, indigenous fodder trees and shrubs\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChemical composition of improved forages\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the chemical compositions (%DM basis) of the cultivated forage species in the three agro-ecological zones of the study area. The DM, Ash, EE, CP, NDF, ADF, ADL and CF values of \u003cem\u003ePennisetum purpureum\u003c/em\u003e were 89.17%, 10.86%, 1.6%, 6.9%, 66.69%, 34.57%, 12.22% and 45.92%, respectively.\u003c/p\u003e \u003cp\u003eAccording to McDonald et al. (2011), the DM content of fodder and formulated feeds influences the availability of nutrients and microbial activity. The DM content of \u003cem\u003ePennisetum purpureum\u003c/em\u003e (89.17%) recorded in the present study is in line with the results of Gashu et al. (2017), who reported 89.5% DM. However, this value is lower than the value (91%) reported by Solomon et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The ash content of \u003cem\u003ePennisetum purpureum\u003c/em\u003e (10.86%) obtained in this study is consistent with the observation of Solomon et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who reported a value of 10.98%. The EE content of \u003cem\u003ePennisetum purpureum\u003c/em\u003e was very low (1.6% DM). It has been reported that EE contents of feeds above 7% DM limit the amount of feed that livestock consume (Eastridge, 2014).\u003c/p\u003e \u003cp\u003eThe CP content of \u003cem\u003ePennisetum purpureum\u003c/em\u003e (6.9%) observed in the present study is higher than the reported value of 5.58% (Guerra et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) but lower than the recommended value of 7 to 8% DM CP, which is the lowest amount of CP required for microbial growth in the rumen (Asaolu et al., 2011; Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The NDF in \u003cem\u003ePennisetum purpureum\u003c/em\u003e (66.69%) obtained in the current study is in agreement with the value of 67.11% reported by Gashu et al. (2017). The percentage of ADF in \u003cem\u003ePennisetum purpureum\u003c/em\u003e (34.57%) recorded in the present study is lower than the 47.45% reported by Guerra et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The ADF value of \u003cem\u003ePennisetum purpureum\u003c/em\u003e is greater than the reported range of 17\u0026ndash;21% recommended for rumen stability (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe DM, Ash, EE, CP, NDF, ADF, ADL and CF contents of \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e were 91.20%, 9.45%, 1.52%, 8.58%, 63.97%, 36.88%, 10.81% and 37.52% DM, respectively. The ash content of \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e (9.45% DM) recorded in the present study is in line with the observation of Fiseha (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who reported a value of 9.0%. The EE content of \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e (1.52%) recorded in this study indicated that it was a low source of energy. It has been reported that the consumption of feeds and forages with low EE contents can increase methane production, which is detrimental to the environment and further increases energy inefficiency in ruminants (Enjalbert et al. 2017). In contrast, excessive consumption of EE in ruminant livestock may impair microbial activities, limiting fiber digestibility (Eastridge, 2014). The CP values for \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e (8.58% DM) observed in this study are not in agreement with the findings of Bezabih et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who reported 11% CP. Generally, the CP contents of the two cultivated forages in the present study are greater than the minimum level of 7\u0026ndash;8% DM required for optimum rumen function and feed intake in ruminants (Van Soest, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). However, it was lower than the recommended minimum requirements for lactation (12%) and growth (11.3% DM in ruminants) (ARC, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1984\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe NDF content of \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e (63.97%) recorded in the present study is lower than the range of 72.78 to 77.68% reported by Asmare et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, it is within the range of 58.82 to 63% (Bimrew et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The ADF values for \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e (36.88%) recorded in this study are consistent with the results of Genet et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who reported values ranging from 16.63\u0026ndash;36.14% DM. However, this value is greater than the reported range of 17\u0026ndash;21% recommended for rumen stability (NRC, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The ADL content of cultivated forages ranged from 10.8% in \u003cem\u003ePennisetum pedicellatum\u003c/em\u003e at ML to 12.22% DM in \u003cem\u003ePennisetum purpureum\u003c/em\u003e at HL. The high contents of ADL in cultivated forages reported in this study could have a negative influence on digestibility, which causes a decrease in the availability of nutrients. Generally, the variation in chemical composition of cultivated forages recorded in the present study and in the literature might be due to differences in agro-ecological zone, plant species, soil on which they were grown, weather conditions during growth, and the stage of maturity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical composition (% DM) of improved forages in three AEZs in the Gera district, southwest Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eImproved forage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SE) chemical composition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAEZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eADF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePennisetum purpureum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e34.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePennisetum pedicellatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e63.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eChemical composition of crop residues\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the mean (\u0026plusmn;\u0026thinsp;SE) chemical composition of the crop residues in the three agro-ecological zones of the study area. The results revealed that, except for NDF, all chemical composition variables of maize stover were influenced by the AEZ (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean DM, Ash, EE, ADF, ADL and CF contents of maize stover were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the HL than in the LL and ML AEZs. The mean DM, Ash, EE, CP and CF contents of teff straw differed significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the AEZs, with the highest values recorded in the HL AEZs compared to those in the ML and LL AEZs. The mean EE, CP and ADF contents of wheat straw were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the HL than in the ML and LL AEZs. The mean DM and EE contents of barley straw were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the HL AEZs than in the ML and LL AEZs. However, the NDF and ADF contents were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) greater in the ML AEZs than in the LL and ML AEZs. There was no significant effect (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) of AEZs on the DM, Ash, CP, ADF, ADL and CF contents of sorghum stover except for EE and NDF (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which were greater in the HL AEZs than in the ML and LL AEZs.\u003c/p\u003e \u003cp\u003eThe DM contents of maize stover, teff straw and barley straw (\u003cem\u003eHordeum vulgare\u003c/em\u003e L.) differed significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the AEZs. The DM content of the crop residues in the present study ranged from 89.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53 in teff (\u003cem\u003eEragrostis tef\u003c/em\u003e (Zucc) Trotter.) straw at LL to 94.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20 in maize (\u003cem\u003eZea mays L\u003c/em\u003e.) stover at the HL AEZ. The results of the present study are in agreement with the findings of previous studies (Girma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ararsa and Amanuel, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reporting that the DM content of various crop residues ranged from 89.86 to 94.77% elsewhere in Ethiopia.\u003c/p\u003e \u003cp\u003eIn this study, the ash content of maize stover and teff straw varied significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in response to the AEZ. The average ash content of crop residues ranged from 6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24% in sorghum stover at LL to 11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57% DM in wheat straw at the HL AEZ. The mean ash content in sorghum stover, maize stover and teff straw recorded in the current study was higher than the ash values reported by Tikabo and Shumuye (2021).\u003c/p\u003e \u003cp\u003eThere was a significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the EE content of crop residues (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the studied AEZs. The average EE content of crop residues ranged from 1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 in wheat straw at ML to 2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09% in barley straw at HL AEZ. The EE contents of maize stover and wheat straw were greater in the HL treatment than in the ML treatment. However, the EE content of wheat (\u003cem\u003eTriticum aestivum L\u003c/em\u003e.) straw was lower at the ML, and that of sorghum stover was lower at the LL AEZ.\u003c/p\u003e \u003cp\u003eThe CP contents of maize stover, teff straw and wheat straw varied significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the AEZs. The CP content of crop residues ranged from 2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13 for wheat straw at the ML to 4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 for barley straw at the HL AEZ. These low CP contents of crop residues might be attributed to the age of the crops that were harvested after the seeds had dried well before they were harvested. The CP content of crop residues recorded in the present study was much lower than the minimum level of 7% required for rumen microbial function (Van Soest, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). The CP content of crop residues in this study was in agreement with the CP values of \u0026lt;\u0026thinsp;7% for maize stover, teff straw, wheat straw, barley straw and sorghum stover reported by Deribe et al. (2019). Nasrullah et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) stated that voluntary feed intake decreases rapidly if the CP content of roughages is below 6.2% DM. Cereal straws generally have a low nitrogen content and are composed of cell wall components with little soluble cell content (Preston and Leng, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe NDF content of the crop residues did not vary significantly (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) across the AEZs except for those of barley straw and sorghum stover. The NDF content in crop residues ranged between 70.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17 in sorghum stover at LL and 79.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02 in maize stover at HL. All crop residues reported in this study had NDF contents greater than 65% DM and were classified as low-quality roughages (Singh and Oosting, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). Similar to the findings of the present study, Sisay (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) also reported NDF contents of crop residues higher than 70% DM. It has been reported that as plants mature, the NDF, ADF and lignin contents increase, while the CP content decreases (Mahala et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), emphasizing that an increase in these parameters is influenced by the maturity stage of the crop residues. Feds with NDF contents less than 45%, 45\u0026ndash;65% and greater than 65% are considered to be of high, medium and low quality, respectively (Bogale et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Mpairwe et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A high NDF above 72% will cause a low intake of forage (Lima et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), and as NDF values increase, DM intake generally decreases (Schroeder, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ADF contents of maize stover, wheat straw and barley straw varied significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) across the studied AEZs. The ADF content of crop residues ranged from 48.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38 in wheat straw at HL to 60.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61 in sorghum stover at the LL AEZ. A high ADF content in crop residues could result in lower digestibility since the digestibility of feed and its ADF content are negatively correlated (McDonald et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Feeds with ADF contents less than 30% and greater than 40% are considered to be of high quality and poor quality, respectively (Mpairwe et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The ADF content of crop residues in this study was greater than 48% DM, indicating their low digestibility.\u003c/p\u003e \u003cp\u003eAgro-ecology influenced the ADL content of maize stover only (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The ADL content of crop residues varied from 7.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49 in teff straw at HL to 13.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55 in wheat straw at ML. The findings of the present study are consistent with the results of Gashaw and Defar (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who reported ADL contents of 8.07, 9.22 and 10.30% DM for barley straw, teff straw and wheat straw, respectively. ADL represents an indigestible portion of rough materials and forms complexes with cellulose and hemicellulose constituents through lignification, thereby impairing microbial digestion. According to Van Soest (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1982\u003c/span\u003e), an ADL content above 6% has a negative impact on the digestibility of forage. Therefore, all crop residues included in this study had ADL contents above this recommended level, resulting in low digestibility by ruminants. Generally, the variation in the chemical composition of crop residues between the present study and the literature might be due to differences in the agro-ecological zone, climatic conditions, soil fertility on which the crop was grown, weather conditions during growth, and maturity stage.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical composition (% DM) of crop residue from three AEZs in the Gera district, southwest Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCrop residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAEZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eChemical composition (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eASH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eADF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaize stover\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep- value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBarley straw\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep- value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSorghum stover\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep- value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMeans with different superscripts in the columns are significantly different at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. DM, dry matter; EE, ether extract; CP, crude protein; CF, crude fiber; ADL, acid detergent lignin; NDF, neutral detergent fiber; ADF, acid detergent fiber; SE, standard error\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eOverall, the agro-ecological zone had a significant effect on most of the chemical composition variables of the feedstuffs evaluated in this study. This might be due to variations in soil type, organic matter content, temperature and rainfall. The indigenous fodder tree and shrub species had greater CP and lower NDF, implying their potential to supplement poor quality feeds such as crop residues, stubble and dry natural pasture grasses, especially during the dry season. On the other hand, crop residues had the lowest CP below the minimum threshold required for the activity of rumen microorganisms and maintenance requirements of ruminants and the highest NDF, implying the need to either improve their nutritive value through urea treatment or supplement animals with protein-rich feeds. Generally, agro-ecology was found to be a key variable influencing the chemical composition of the feedstuffs included in this study. Further evaluation of the nutritive values and mineral contents of these feed resources is essential. Moreover, further animal-based trials involving these feeds are needed to substantiate the findings of the present study on animal performance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank Jimma University for financial support and laboratory technicians at\u0026nbsp;the\u0026nbsp;Animal Nutrition\u0026nbsp;Laboratory\u0026nbsp;of the department of Animal Science, College of Agriculture and\u0026nbsp;Veterinary Medicine, Jimma University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data that support the findings of this study are available on request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge: Jimma University, College of Agriculture and Veterinary Medicine Research Affairs for supporting the Master\u0026rsquo;s programme of Hassen Abazinab in sample analysis.\u003c/p\u003e\n\u003ch2\u003eAuthor information\u003c/h2\u003e\n\u003ch3\u003eAuthors and affiliations\u003c/h3\u003e\n\u003col\u003e\n \u003cli\u003eJimma Zone Livestock and Fisheries Development Agency, Jimma, Oromia, Ethiopia\u003c/li\u003e\n \u003cli\u003eDepartment of Animal Science, College of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Oromia, Ethiopia\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3\u003eContributions\u003c/h3\u003e\n\u003cp\u003eThis work was generated from a Master of Science research work done by HA under the supervision of BD and EM as Postgraduate supervisors.\u003c/p\u003e\n\u003ch3\u003eCorresponding author\u003c/h3\u003e\n\u003cp\u003eCorrespondence to\u0026nbsp;Belay Duguma\u003c/p\u003e\n\u003ch2\u003eEthics declarations\u003c/h2\u003e\n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eEthical approval for this study was obtained from Jimma University, College of Agriculture and veterinary medicine Ethics Committee. Informed consents were also obtained from all farmers before data collection in conformity for anonymity of the study participants.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbazinab, H., Duguma, B., Muleta, E., 2022. Livestock farmers\u0026apos; perception of climate change and adaptation strategies in the Gera district, Jimma zone, Oromia Regional state, southwest Ethiopia. Helyon, 8 (12), 1-13.\u003c/li\u003e\n\u003cli\u003eAbeysekara A W A Saman, 2003. The Nutritional Value of Oat Forages for Dairy Cows. MSc Thesis University of Saskatchewan, Saskatoon, Canada, S7N 5A8.\u003c/li\u003e\n\u003cli\u003eAndualem, T., Berhan, T., and Gebeyehu, G., 2015 Assessment of cattle feed resources; chemical composition and digestibility of Major Feeds in Essera District Southern Ethiopia. Sci. Technol. Arts Res. 4(2),89-98.\u003c/li\u003e\n\u003cli\u003eAOAC (Association of Official Analytical Chemists). Official methods of analysis of AOAC International, 2005.\u003c/li\u003e\n\u003cli\u003eArarsa, D., Amanuel B., 2021. Evaluation of Livestock Feed Nutritional Composition in WelisoDistrict, South West Shoa Zone, Central Ethiopia. \u003cem\u003eInternational Journal of Advanced Research in Biological Sciences. \u003c/em\u003eInt. J. Adv. Res. Biol. Sci. 8(3), 51-60.\u003c/li\u003e\n\u003cli\u003eARC 1984. The nutrient requirements of ruminant livestock (Suppl. No. 1). Agricultural Research Council. Commonwealth Agricultural Bureaux, Farnham Royal, UK.\u003c/li\u003e\n\u003cli\u003eARC, 1984. The Nutrient requirements of Ruminant Livestock, Supplement No. 1. Report of the Protein Group of the Agricultural Research Council Working Party on Nutrient Requirements of Ruminants. 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Workshop proceeding, 12-14 March, Ottawa, Canada, pp. 49-60.\u003c/li\u003e\n\u003cli\u003eVan Soest, P.J., Robertson, J.B., Lewis, B.A., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci. \u003cstrong\u003e7\u003c/strong\u003e4, 3583\u0026ndash;3597.\u003c/li\u003e\n\u003cli\u003eZewdie, W., 2010. Livestock production systems in relation with feed availability in the HLs and Central Rift valley of Ethiopia. M.Sc. thesis submitted to the School of Animal and Range Sciences, School of Graduate studies Haramaya University, Ethiopia.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Agriculture](https://www.springer.com/journal/44279)","snPcode":"44279","submissionUrl":"https://submission.nature.com/new-submission/44279/3","title":"Discover Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chemical composition, crop residues, improved forage, indigenous fodder trees and shrubs, natural pasture, livestock","lastPublishedDoi":"10.21203/rs.3.rs-4217865/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4217865/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe poor quality of available feed resources is the major limiting factor forlivestock productivity in Ethiopia. The aim of this study was to determine and compare the chemical composition of major feed resources in three agro-ecologicalzones (AEZs) of the Gera District, southwest Ethiopia. Three representative samples of natural pasture (\u003cem\u003eCynodon dactylon, Pavonia schimperiana Hochst and Rhynchosia ferruginea), \u003c/em\u003ethree indigenous fodder trees and shrubs (IFTSs)\u003cem\u003e(Erythrina abyssinica, Vernonia amygdalina and Maytenus undat), \u003c/em\u003etwo cultivated forages (\u003cem\u003ePennisetum purpureum and Pennisetum pedicellatum\u003c/em\u003e) and five crop residues (\u003cem\u003eHordeum vulgare \u003c/em\u003e(barley)\u003cem\u003e, Zea mays\u003c/em\u003e (maize)\u003cem\u003e, Sorghumbicolor\u003c/em\u003e (sorghum)\u003cem\u003e, Triticum aestivum \u003c/em\u003e(wheat) and\u003cem\u003e Eragrostis tef \u003c/em\u003e(Teff)) were collected from the Highland (HL),\u003cstrong\u003e \u003c/strong\u003emidland (ML) and lowland (LL) AEZs. The samples were analyzed for ash, dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), and acid detergent lignin (ADL) content. The results showed that different AEZs showed a significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) effect on the most of the chemical composition parameters of sampled feeds. Regardless of the AEZs, the mean DM, CP, ash, EE, NDF, ADF, ADL and CF varied from 89.17% in \u003cem\u003ePennisetum purpureum\u003c/em\u003e to 92.22±0.51 in \u003cem\u003eErythrina abyssinica\u003c/em\u003e, 2.90±0.22% in \u003cem\u003eTriticum aestivum \u003c/em\u003eto 10.70±0.52 in \u003cem\u003eVernonia amygdalina\u003c/em\u003e, 7.24±0.19% in \u003cem\u003eSorghum bicolor\u003c/em\u003e to 13.25±0.51% in \u003cem\u003ePavonia Schimperiana Hochst\u003c/em\u003e, 1.33±0.04% in \u003cem\u003eTriticum aestivum\u003c/em\u003e to 2.39±0.15% in \u003cem\u003eMaytenus undata\u003c/em\u003e, 57.65±1.19% in \u003cem\u003eErythrina Abyssinica\u003c/em\u003e to 79.16±1.04%in \u003cem\u003eTriticum aestivum\u003c/em\u003e, 34.57% in \u003cem\u003ePennisetum purpureum\u003c/em\u003e to 59.41±0.98% in \u003cem\u003eSorghum bicolor\u003c/em\u003e, 8.15±0.62%in \u003cem\u003eRhynchosia ferruginea\u003c/em\u003e to 12.65±0.57% in \u003cem\u003eTriticum aestivum\u003c/em\u003e and 37.51% in \u003cem\u003ePennisetum pedicelatum\u003c/em\u003e to 69.93±0.65% DM in \u003cem\u003eTriticum aestivum\u003c/em\u003e, respectively. In conclusion, IFTSs had the highest CP and the lowest NDF, implying their potential as a supplement to low-quality feeds, whereas crop residues had the lowest CP and the highest NDF compared to other feed types, indicating the need for their treatment with urea or supplementing animals with protein-rich feeds, especially during the dry season.\u003c/p\u003e","manuscriptTitle":"Effects of agro-ecological zones on the chemical composition of feed resources in the Gera district, southwest Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-03 19:05:57","doi":"10.21203/rs.3.rs-4217865/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-08T06:45:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-24T21:53:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247626172523138343205841451339920745215","date":"2024-07-17T14:08:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20508613146883299325344698699747695409","date":"2024-07-12T12:01:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-09T13:13:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"207733891941795297164200898338623152764","date":"2024-05-02T15:11:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118670154186556379674528931902688912728","date":"2024-05-02T13:07:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202710342136771688941721281737436470621","date":"2024-05-02T11:56:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-02T11:47:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-29T08:44:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-29T08:28:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Agriculture","date":"2024-04-04T12:25:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Agriculture](https://www.springer.com/journal/44279)","snPcode":"44279","submissionUrl":"https://submission.nature.com/new-submission/44279/3","title":"Discover Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0dbcc24-a7b9-4504-8c4b-85be56ec186d","owner":[],"postedDate":"May 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-10-01T04:38:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-03 19:05:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4217865","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4217865","identity":"rs-4217865","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}