Comparative Analysis of Nutritional Composition: Proximate and Mineral Content of Soybean Varieties

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This study aimed to evaluate the proximate composition and mineral content of soybean varieties from two research centers (Kelafo and Dolo-ado centers). Mature soybean seeds were collected from Kelafo, Dolo-ado, and local markets. Proximate composition (moisture, ash, fat, protein, fiber) and mineral content (calcium, iron, magnesium, zinc) were analyzed using standard methods, with triplicate measurements. Data analysis and modeling were conducted using GenStat version 18 and Excel 2019. Moisture content ranged from 4.78–7.34%, protein 19.65–30.35%, fat 5.37–21.61%, and fiber 3.75–6.29%. Calcium ranged from 48.9-157.2 mg/100g, iron 5.37–12.06 mg/100g, magnesium 658.5-2429.1 mg/100g, and zinc 3.79–6.45 mg/100g. Varieties K-Pawe-01, K-Pawe-03, D-Pawe-03, and D-Gezale exhibited high nutritional value, making them suitable for addressing protein-energy malnutrition and mineral deficiencies, particularly in vulnerable populations such as infants and lactating mothers. Soybean varieties Proximate composition Mineral content Nutritional analysis INTRODUCTION Soybean, scientifically known as Glycine max (L.), originated in East Asia, likely in the northern and central regions of China. Mature soybean seeds are composed of approximately 40% protein, 20% oil, and 10% water-soluble carbohydrates [ 1 ]. As a vital legume, Glycine max is increasingly consumed for its nutritional and economic benefits [ 2 ]. Its high-quality protein and oil are essential for human health, making soybeans a significant component of human diets [ 3 ]. Soybean quality is typically assessed based on protein, oil, fatty acid, and mineral content, as these factors are crucial for enhancing human and animal nutrition. Due to their affordability, soybeans provide an excellent source of protein, minerals, phosphorus, and vitamins [ 4 ]. Soybean products are widely recognized for their positive contributions to health and wellness. Regular consumption of soybeans has been associated with the prevention of several chronic conditions, including heart disease, obesity, hypercholesterolemia, cancer, diabetes, kidney disease, and osteoporosis [ 5 ]. Additionally, soybeans serve as a valuable protein source for individuals who are allergic to animal milk [ 6 ]. Among cereals and legumes, Glycine max stands out for its high protein content, which reaches 40%. In comparison, other legumes typically contain 20–30% protein, while cereals range from 8–15% [ 7 ]. Furthermore, a study of six soybean varieties in Bilo-19 reported a high protein content of 47.63 g/100 g, while the variety Ethio-Yugoslavia recorded the lowest protein content at 35.31 g/100 g, with this difference being statistically significant (P < 0.05). The average protein content across the six varieties was 37.10 g/100 g [ 8 ]. Soybeans are particularly valued as a plant-based protein due to their cholesterol-lowering effects in patients with type II hyperlipoproteinemia [ 9 ]. In addition to their high protein levels, soybeans contain approximately 20% oil, the second-highest oil content among all food legumes. Peanuts have the highest oil content at about 48% on a dry matter basis, followed by chickpeas with around 5% oil [ 10 ]. Soybeans are also rich in essential minerals and vitamins such as iron, zinc, copper, thiamine, riboflavin, niacin, pantothenic acid, and phospholipids [ 11 ]. These vitamins and minerals play crucial roles in red blood cell formation due to their hematinic properties [ 12 ]. Additionally, soybeans are known to contain flavonoids, particularly isoflavones, which contribute to their cancer-fighting and disease-preventing properties. As part of the study evaluation of the proximate composition and mineral content of five soybean varieties in two research centers, various research centers under the Somali Region Pastoral and Agro-pastoral Research Institute (SoRPARI) have focused on developing and releasing soybean varieties. A proximate analysis is essential to assess the quality of these varieties. This research provides a comprehensive analysis of five distinct soybean varieties Pawe-01, Pawe-02, Pawe-03, Gizo, and Gezale by evaluating their nutritional quality, agronomic performance, functional properties, and anti-nutritional factors under diverse environmental conditions at Kelafo and Dolo-Ado research centers. By examining key nutritional parameters such as protein, fiber, and carbohydrate content, the study aims to identify the most suitable varieties for enhancing plant-based nutrition programs and optimizing breeding and food product development. This research holds significant value in addressing food insecurity, malnutrition, and mineral deficiencies, particularly in low-income communities, while also promoting agricultural sustainability. The findings will provide essential data to guide future breeding programs, improve the nutritional profile of soy-based foods, and contribute to public health outcomes in regions with limited access to diverse and nutrient-rich foods. MATERIAL AND METHODS 2.1. Adapting Soybean Cultivation to Arid and Semi-Arid Conditions The cultivation of mature soybean seeds at the Kelafo and Dolo-Ado Research Centers, located in the Somali Regional State of Ethiopia, is designed to suit the region's arid and semi-arid agro-ecological conditions. The experiment was conducted during the 2021/2022 cropping seasons, using five released soybean varieties evaluated under a Randomized Complete Block Design with three replications. Each experimental unit consisted of four rows, every 4 meters in length, with a row-to-row spacing of 40 cm and a plant-to-plant spacing of 10 cm. The gross plot size was 4 m x 1.6 m, with data collected from the two middle rows. These research areas experience high temperatures, often exceeding 30°C, and low annual rainfall, ranging from 300 to 600 mm. Such climatic conditions require the selection of drought-tolerant soybean varieties capable of thriving under heat stress and limited moisture availability. Research and development efforts in these centers aim to optimize agricultural practices, ensuring crops like soybeans can flourish despite the challenges posed by the lowland elevation and the harsh climatic factors. 2.2. Sample collection and preparation Mature soybean seeds were sourced from the Kelafo and Dolo-Ado Research Centers, and two local varieties were purchased from the markets in Gode and Jigjiga cities, located in the Somali Regional State, Ethiopia. The seeds were thoroughly cleaned to remove foreign materials, and any damaged or insect-infested seeds were discarded. After washing with tap water, the seeds were sun-dried for 8 hours to eliminate any moisture absorbed during the washing process. They were then ground into flour using a laboratory hammer mill (Model NL-BL-4361, China), packed in airtight polyethylene bags, and stored at 4°C for further analysis. 2.3. Determination of Proximate Composition Using standard analytical methods (AOAC, 2023), the soybean varieties were analyzed for proximate composition, including ash, moisture, crude fat, crude fiber, crude protein, carbohydrate, and energy content [ 13 ]. All measurements were performed in triplicate, with results expressed as percentages, except for energy value, which was reported in kcal/100 g. Carbohydrate content was calculated by difference (Eq. 1), and energy value (E.V.) was determined using the Atwater factor method (Eq. 2): % Carbohydrate content = 100% (% moisture + % protein + %Fat + %Ash) …… (1). E.V = (9 x Crude Fat %) + (4 x Crude Protein %) + (4 x Carbohydrate %) ………(2). 2.4. Determination of Mineral Content The concentrations of selected mineral elements (Ca, Fe, Mg, and Zn) were determined from a solution prepared by wet digestion of the sample ash with a 1:1 (v/v) HCl and nitric acid mixture. The analysis was conducted using an atomic absorption spectrophotometer [ 13 ]. 2.5. Data analysis All analyses were performed in triplicate, and results were presented as mean ± standard error. Data analysis and modeling were carried out using GenStat version 18 and Excel 2019, with a significance level of p < 0.05 to determine statistical significance. Results 3.1. Agronomic Performance of Soybean Varieties at Kelafo and Dolo-Ado Research Centers 3.1.1. Dolo-Ado Center The analysis of variance indicated that the varieties had no significant effect on the number of seeds per pod (Table 1 ). Mean separation analysis revealed that Pawe-03 had the highest number of seeds per pod (2.633), which was statistically similar to Gizo. The lowest number of seeds per pod (2.433) was recorded for Pawe-01, with an overall mean of 2.500 (Table 1 ). The highest hundred-seed weight was observed in Pawe-01 (9.083 g), which was statistically comparable to Pawe-02 (9.033 g), followed by Pawe-03. Pawe-02 had the lowest hundred-seed weight (10.04 g), while the overall average was 12.31 g (Table 1 ). The variation in hundred-seed weight among the varieties may be attributed to differences in seed size influenced by the growth environment. These variations are consistent with findings from the Sudanian Zone of Burkina Faso and Southwestern Ethiopia [ 14 – 15 ]. Additionally, a meta-analysis reported that differences in hundred-seed weight among soybean varieties could be attributed to crop yield potential, growth rate, enhanced nutrient translocation, and genetic superiority [ 16 ]. The analysis of variance showed no significant differences among the varieties in terms of days to maturity (Table 1 ). Pawe-02 had the longest duration to maturity (99.33 days), followed by Pawe-01 (97.83 days), which was statistically similar to Gizo. The shortest duration (95.33 days) was observed in Gazale, which was also comparable to Pawe-01 (Table 2 ). The effect of varieties on plant height was non-significant (Table 1 ). The tallest plants were recorded in Gizo (63.37 cm), while the shortest were recorded for Pawe-01 (54.73 cm), with an overall mean of 59.8 cm (Table 1 ). Variety had no significant effect on the number of pods per plant (Table 1 ). The highest number of pods per plant (62.53) was recorded in Gazale, while the lowest (54.57) was observed in Pawe-02, with an overall mean of 59.1 (Table 1 ). The highest grain yield was recorded for Pawe-03 (1978 kg/ha), which was statistically similar to Pawe-02 (1972 kg/ha). Pawe-01 had the lowest grain yield (1205 kg/ha). The higher yields of Pawe-03 and Pawe-02 may be attributed to differences in growth habits and genetic potential, which contributed to variations in yield performance. These findings align with similar results reported in Northwestern Ethiopia [ 17 ]. 3.1.2. Kelafo Center The Gizo variety exhibited the longest time to maturity (91.67 days), while Pawe-01 matured the earliest (89.33 days). This result is consistent with the findings of a study conducted in Ethiopia [ 18 ]. The highest number of pods per plant was observed in Pawe-01 (58.67), while Pawe-02 had the lowest (47.37). This finding aligns with previous studies conducted in Northwestern Ethiopia [ 17 ]. Similarly, variations in the days to 90% maturity across different genotypes have been reported by [ 15 ], who also observed significant differences in the number of pods per plant, ranging from 70 to 35. Pawe-01 recorded the highest number of seeds per pod (3.158), which was statistically similar to Pawe-03, Gizo, and Gazale. [ 2 ] also reported variations in the number of seeds per pod, ranging from 129.1 to 72.6. The highest hundred-seed weight was recorded for Pawe-01 (9.173 g), while Gizo had the lowest (7.107 g). Table 1 Mean of agronomic traits of soybean varieties tested at Kelafo and Dolo-ado centers Varieties Location DM(%) PH(cm)(%) NPPP(%) NSPP(%) TSW(g)(%) Yield (Y) (kg/ha)(%) Gazale Dolo-ado Center 95.83a 63.33a 62.53a 2.333a 7.617b 1508b Gizo 97.83a 63.37a 56.97a 2.633a 7.767b 1449b Pawe-01 97.17a 54.73a 60.47a 2.433a 9.083a 1205c Pawe-02 96.83a 55.10a 54.57a 2.467a 9.033a 1972a Pawe-03 97.83a 62.37a 60.77a 2.633a 8.250ab 1978a Grand Mean 97.10 59.8 59.1 2.500 8.35 1622 CV% 1.9 12.4 13.8 14.9 9.7 9.3 LSD 2.231 9.02 9.92 0.4524 0.982 182.7 Gazale Kelafo Center 90.83abc 61.85a 53.65abc 3.158a 8.150b 887d Gizo 91.67a 66.35a 54.88ab 3.158a 7.107c 946d Pawe-01 89.33c 67.30a 58.67a 3.108a 7.137c 1188c Pawe-02 89.83bc 67.63a 47.37c 2.608b 9.173a 1372b Pawe-03 91.42ab 65.28a 50.83bc 3.158a 8.033b 1539a Grand Mean 90.62 65.7 53.08 3.038 8.35 1186 CV% 2.2 12.3 14.4 16.2 9.0 13.5 LSD 1.680 6.66 6.329 0.4068 0.991 132.7 CV = Coefficient of Variation, LSD = Least Significant Difference. Means followed by different letters within columns are significantly different by Duncan’s new multiple range test (P = 0.05). DM = Days to 90% maturity, PH (cm) = plant height(centi metter ), NPPP = number of pods per pl ant, NSPP = number of seed per pod, TSW (gram) = thousand seed weight, BM (kg/ha) = biomass 3.2. Proximate composition of soybean varieties The results are presented in Table 2 . K-Pawe-01 had the highest moisture content among all the varieties, though it was not significantly different from K-Pawe-02. The lowest moisture content was recorded in L-Jigjiga, which showed a significant difference compared to L-Gode. D-Pawe-01 showed the highest ash content, although this difference was not statistically significant except when compared to K-Gezale and the local varieties. Table 2 also indicates that D-Gezale had the highest crude fat content, while K-Pawe-03 showed no significant difference from G-Gezale. However, the regional varieties had the lowest crude fat content. The variations in crude fat content, particularly the lowest values observed in the Gizo variety at Dolo-Ado and the Gezale variety at Kelafo, may be attributed to environmental factors such as soil composition, temperature fluctuations, and water availability. These factors play a critical role in lipid metabolism, ultimately influencing fat accumulation and the overall nutritional profile of the soybean varieties. Additionally, the data revealed that the local varieties contained higher fiber content than the others. D-Pawe-03 had the highest protein content, while the local varieties had the lowest. Carbohydrate content was more pronounced in the regional varieties, with significant differences observed among them. K-Pawe-01 had the lowest carbohydrate content. In terms of energy content, D-Gezale recorded the highest value, with no significant differences from D-Pawe-01, D-Pawe-02, K-Gizo, K-Pawe-01, K-Pawe-02, and K-Pawe-03. The control samples from Gode and Jigjiga had significantly lower crude fat content, indicating non-standard quality. They were included to represent local soybeans and serve as a baseline for comparison. Their lower nutritional values highlight the need for improved varieties to ensure better nutritional outcomes. Table 2 Proximate Composition of Different Soybean Varieties Varieties Location Parameters Moisture (%) Ash (%) Crude Fat (%) Crude Protein (%) Crude Fiber (%) Carbohydrate Content (%) Energy (%) Gezale Dolo-ado Center 5.09 ± 0.04 c 5.62 ± 0.07 ab 21.61 ± 0.03 a 28.92 ± 0.03 c 3.75 ± 0.13 d 35.01 ± 0.18 ef 450.21 ± 0.32 a Gizo 5.51 ± 0.02 abc 5.76 ± 0.03 ab 13.04 ± 0.02 h 28.68 ± 0.03 d 5.04 ± 0.03 b 41.97 ± 0.04 c 399.96 ± 0.23 e Pawe-01 5.53 ± 0.03 abc 6.30 ± 0.48 a 21.47 ± 0.01 b 28.73 ± 0.02 d 4.45 ± 0.09 bc 45.35 ± 0.05 efg 489.5 ± 0.39 b Pawe-02 5.17 ± 0.01 bc 5.75 ± 0.19 ab 20.83 ± 0.01 e 27.96 ± 0.02 f 4.14 ± 0.05 cd 47.07 ± 0.00 d 487.6 ± 0.26 b Pawe-03 5.81 ± 0.11 abc 5.77 ± 0.08 ab 20.02 ± 0.00 f 30.35 ± 0.02 a 4.57 ± 0.05 bc 45.06 ± 0.52 fg 481.8 ± 2.00 c Gezale Kelafo Center 6.25 ± 0.02 abc 5.22 ± 0.07 b 16.56 ± 0.01 g 26.35 ± 03 g 4.32 ± 0.24 bcd 52.77 ± 0.22 c 465.6 ± 0.88 d Gizo 6.52 ± 1.68 abc 5.34 ± 0.09 ab 21.27 ± 0.00 c 26.35 ± 0.03 g 4.92 ± 0.30 b 35.60 ± 0.32 d 439.23 ± 1.26 b Pawe-01 7.34 ± 0.61 a 5.64 ± 0.55 ab 21.13 ± 0.05 d 29.52 ± 0.02 b 4.62 ± 0.02 bc 44.73 ± 0.06 g 487.2 ± 0.17 b Pawe-02 7.17 ± 0.42 a 5.84 ± 0.50 ab 21.12 ± 0.00 d 28.49 ± 0.01 e 4.36 ± 0.20 bcd 46.03 ± 0.01 e 488.2 ± 0.09 b Pawe-03 7.12 ± 0.02 ab 5.61 ± 0.27 ab 21.60 ± 0.00 a 27.94 ± 0.02 f 4.63 ± 0.03 bc 31.1 ± 0.00 e 430.56 ± 0.08 b Control Gode 4.79 ± 0.70 c 4.27 ± 0.38 c 5.37 ± 0.02 j 19.86 ± 0.02 h 5.94 ± 0.30 a 59.77 ± 0.29 a 366.85 ± 1.32 f Control Jigjiga 4.78 ± 0.08 c 3.82 ± 0.12 c 6.34 ± 0.02 i 19.65 ± 0.04 i 6.29 ± 0.08 a 59.12 ± 0.02 b 372.14 ± 0.43 g Grand Mean 6.59 5.43 17.53 26.9 4.75 50.82 468.64 CV % 11.6 7.8 0.2 0.1 6.2 0.6 0.3 LSD % 1.66 0.658 0.071 0.076 0.644 0.664 2.63 All values are the means expressed on a dry matter basis ± standard error. Means with the same superscripts do not differ significantly (P < 0.05), D = Dolo-Ado, K = Kelafo, CV = Coefficient of Variation, LSD = Least Significance Difference. 1.1. Mineral contents and anti-nutritional factors of different soybean varieties The results of the mineral element analysis, including calcium, iron, magnesium, and zinc, are shown in Table 3 , with concentrations expressed as mg/100 g in the dry matter of soybean flour. Variety K-Pawe-03 had the highest calcium content, followed by D-Pawe-03 and D-Gizo, though there was no significant difference between D-Pawe-03 and D-Gizo. K-Pawe-03 also had the highest iron content among all the varieties, while the local varieties showed the lowest mineral content overall. Regarding magnesium, K-Pawe-02 exhibited the highest content, with K-Pawe-03 ranking next. The results indicate that K-Pawe-03 had significantly higher levels of all the analyzed minerals than the other varieties. The lowest zinc content was found in L-Jigjiga. Table 3 Total mineral contents of different soybean varieties Varieties Location Parameters (mg/100 g) Calcium % Iron % Magnesium % Zinc % Gezale Dolo-ado Center 130.8 ± 0.19 d 9.570 ± 36.07 bcd 930.9 ± 36.07 e 6.040 ± 0.01 abc Gizo 143.0 ± 2.10 b 9.765 ± 111.75 bcd 1144.1 ± 111.75 cd 6.030 ± 0.09 abc Pawe-01 137.9 ± 1.47 c 8.105 ± 67.80 de 1073.5 ± 67.80 cde 6.000 ± 0.10 abc Pawe-02 135.4 ± 1.57 c 9.990 ± 2.87 bc 1231.8 ± 2.86 bc 6.075 ± 0.19 abc Pawe-03 143.7 ± 1.32 b 10.815 ± 16.23 ab 1140.0±`6.23 cd 5.680 ± 0.19 cd Gezale Kelafo Center 137.9 ± 1.34 c 9.165 ± 11.90 bcde 978.1 ± 11.90d e 6.450 ± 0.00 a Gizo 138.1 ± 1.21 c 9.355 ± 0.13 bcde 1117.3 ± 0.13cd e 6.275 ± 0.30a b Pawe-01 130.2 ± 0.81 d 8.715 ± 61.65 cde 1095.1 ± 61.64 cde 6.385 ± 0.03 ab Pawe-02 127.1 ± 1.74 d 8.110 ± 1.07 de 2429.1 ± 1.07 a 6.120 ± 0.07 abc Pawe-03 157.2 ± 0.74 a 12.060 ± 9.51 a 1378.2 ± 9.51 b 5.960 ± 0.08 bc Control Gode 55.4 ± 1.10 e 7.705 ± 1.20 e 658.5 ± 1.12 f 5.275 ± 0.03 d Control Jigjiga 48.9 ± 1.38 f 5.375 ± 123.48 f 945.3 ± 123.48 e 3.790 ± 0.16 e Grand Mean 123.79 9.06 1177.0 5.840 CV % 7.6 6.8 3.3 8.1 LSD % 1.49 173.3 0.41 0.19 All values are the means expressed on a dry matter basis ± standard error. Means with the same superscripts do not differ significantly (P < 0.05), D = Dolo-Ado, K = Kelafo, CV = Coefficient of Variation, LSD = Least Significance Difference. DISCUSSION 2.1. Proximate composition of Soybean The study revealed that soybeans have a low moisture content, ranging from 4.78–7.34%, which implies that soybeans can be stored for extended periods since low moisture levels inhibit the growth of microorganisms. This finding is consistent with a study conducted in Nigeria, which reported a moisture content of 6.12%, highlighting the potential for long-term storage without significant microbial growth [ 19 ]. The ash content in the soybean samples was notably high, ranging from 3.82–6.30%, indicating that these soybeans are rich in minerals. This aligns with another Nigerian study reporting an ash content of 4.29% [ 20 ]. The protein content ranged from 19.65–30.35%, reflecting a high concentration of protein compounds, making soybeans a promising solution for addressing malnutrition, particularly protein-energy malnutrition conditions such as marasmus and kwashiorkor. The crude fat content in this study ranged from 5.37–21.61%, with varieties like D-Gezale and K-Pawe-01 showing the highest values at 21.61% and 21.60%, respectively. Although the overall fat content was lower than that of some other sources, these results are consistent with the findings reported in the study [ 20 ]. The fiber content ranged from 3.75% (D-Gezale) to 6.29% (L-Jigjiga), which provides health benefits such as aiding digestion and reducing colon cancer risk [ 2 ]. Carbohydrate content ranged from 44.75–68.82%, offering a high carbohydrate level essential for managing protein-energy malnutrition. These findings correspond to carbohydrate content values of 34.97–39.86% reported in other studies [ 21 ]. The energy content of the soybeans ranged from 403.1 kcal/100 g to 450.21 kcal/100 g, comparable to values reported in Ghana [ 21 ]. 2.2. Mineral Concentrations of Soybean The calcium content in soybean varieties ranged from 48.9–157.21%, indicating their potential to develop complementary foods for infants. This is crucial, as calcium plays a significant role in bone and tooth development, which aligns with the findings reported in the study [ 21 ]. The iron content was high, ranging from 5.37–12.06%, with K-Pawe-03 showing the highest value. This finding supports efforts to address iron deficiencies in vulnerable populations, aligning with the study [ 22 ], which highlights the critical role of iron in oxygen transport within the bloodstream. By addressing these deficiencies, it is possible to improve overall health outcomes, particularly for those at greater risk. Magnesium content is also significant and supports protein formation, calcium retention, and energy release. Zinc content ranged from 3.79–6.45%, which is critical for immune health. These findings align with earlier studies on magnesium and zinc's roles in human health [ 21 ]. CONCLUSION This study highlights the superior nutritional value of soybean varieties from Kelafo and Dolo-Ado, particularly the Pawe and Gezale types. These varieties, such as K-Pawe-01, K-Pawe-03, D-Pawe-03, and D-Gezale, are rich in protein (28.73%-30.35%), fat (up to 21.61%), and carbohydrates (52.77%), making them ideal for food product development to combat protein-energy malnutrition. While the fiber content (3.75%-5.94%) is relatively low, it still supports digestive health. The high ash content indicates significant levels of essential minerals like calcium, magnesium, zinc, and iron, which are vital for bone health, immunity, and metabolic function. The findings suggest that these soybeans could be beneficial for food fortification and improving nutritional intake in regions facing malnutrition. Declarations Ethics and Consent to Participate Declarations Not applicable Consent for Publication All authors have agreed to submit and publish this manuscript. We confirm that the manuscript, including any identifiable information, does not violate any confidentiality agreements and that consent for publication has been obtained from all relevant parties Availability of Data and Materials The data generated and analyzed during this study are available from the corresponding author upon reasonable request. Statements We confirm that all experimental and field research involving plants, whether cultivated or wild, including the collection of plant samples, complied with applicable institutional, national, and international guidelines and laws. No specific approvals were necessary for this study, as it adhered to all relevant regulations Competing Interests The authors declare that they have no competing interests. Funding Somali Region Pastoral and Agropastoral Research Institute (SoRPARI). Authors' Contributions Mahamed Dol Ateye conceived the study, contributed to the study design, performed the analysis, and wrote the manuscript. Abdulkarim Mohammed Ali, Shamsedin Mahdi Hassan, and Hodo Mohamed Jama contributed to data duration and visualization. Mahamed Dol Ateye reviewed and edited the manuscript. All authors read and approved the final manuscript. Abdikadir Sheik has comprehensively analyzed various agronomic traits in soybeans, including yield, number of days to maturity, plant height, number of pods per plant, first pod height, and the weight of 1,000 seeds. Acknowledgment The authors acknowledge the Somali Region Pastoral and Agropastoral Research Institute (SoRPARI) for their support and resources. References Byth, D. (1968). Comparative photoperiodic responses for several soya bean varieties of tropical and temperate origin. 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W., Coulibaly, S., Sombié, P. A. E. D., Boro, O., Hassane, A.-K., Ouédraogo, A.-A., Bama, H. B., Sawadogo, M., & Sérémé, P. (2022). Evaluation of Early Maturity Group of Soybean (Glycine max L. Merr.) for Agronomic Performance and Estimates of Genetic Parameters in Sudanian Zone of Burkina Faso. Advances in Agriculture, 1–9. https://doi.org/10.1155/2022/3370943 Yechalew, S., Masresha, Y., Mesfin, H., & Bahailu, A. (2020).Performance of Released Soybean Varieties at Jimma, South Western Ethiopia. Journal of Biology, Agriculture and Healthcare. https://doi.org/10.7176/jbah/10-4-02 Xu, C., Wu, T., Yuan, S., Sun, S., Han, T., Song, W., & Wu, C. (2022). Can Soybean Cultivars with Larger Seed Size Produce More Protein, Lipids, and Seed Yield? A Meta-Analysis. Foods, 11(24), 4059. https://doi.org/10.3390/foods11244059 Agegn, A., Bitew, Y., & Ayalew, D. (2022). Response of yield and quality of soybean [Glycine max (L.) Merrill] varieties to blended NPSZnB fertilizer rates in Northwestern Ethiopia. Heliyon, 8(5), e09499. https://doi.org/10.1016/j.heliyon.2022.e09499 Sileshi, Y., Yirga, M., Atero, B., Tesfaye, A., Bosa, D., & Hailemaria, M. (2022). Performance of Newly Released Early Maturing Soybean (Glycine max (L.) Merr.) Variety,‘Guda’in the Major Growing Agro-ecologies of Ethiopia. Ethiopian Journal of Crop Science, 10(1). https://www.ajol.info/index.php/ejcs/article/view/243237 Nwosu, D. J., Olubiyi, M. R., Aladele, S. E., Apuyor, B., Okere, A. U., Lawal, A. I., Afolayan, G., Ojo, A. O., Nwadike, C., Lee, M.-C., & Nwosu, E. C. (2019). Proximate and mineral composition of selected soybean genotypes in Nigeria. Journal of Plant Development, 26, 67–76. https://doi.org/10.33628/jpd.2019.26.1.67 Etiosa, O. R., Chika, N. B., & Benedicta, A. (2017). Mineral and proximate composition of soya bean. Asian Journal of Physical and Chemical Sciences, 4(3), 1-6. https://doi.org/10.9734/ajopacs/2017/38530 Eshun, G. (2012). Nutrient composition and functional properties of bean flours of three soya bean varieties from Ghana. African Journal of Food Science and Technology, 3(8), 176-181. http://www.interesjournals.org/AJFST Mehas, K. Y. (2001). Food science: The biochemistry of food and nutrition. McGraw-Hill Education. https://doi.org/10.1108/nfs.2001.01731baf.006 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 29 May, 2025 Reviewers agreed at journal 07 May, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 21 Apr, 2025 Reviewers agreed at journal 14 Apr, 2025 Editor assigned by journal 01 Apr, 2025 Reviewers invited by journal 24 Mar, 2025 Submission checks completed at journal 22 Mar, 2025 First submitted to journal 05 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5416187","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447524322,"identity":"86c0e407-10cb-4126-b011-2015747b44bd","order_by":0,"name":"Mahamed Dol Ateye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYNACAxs5fhCdUECMajYQUZFmLNkA0mJAtJYzhxI3HABbR4QO/vnNxyQ+th1I3Hx+deKHBwYM8vxiB/BrkTjGliY5s+2O8bYbbzdLAB1mOHN2AgFrjvGYSfO2PZPdduPsBpCWBIPbBLTIH+P/Jv237TDj5hlnN/8gSovBMR42aYYzhxU38PduI84Ww2NpxpY9wECWuMG7zSLBQIKwX+QOH3544wcoKvvPbr75o8JGnl+agBYgYJEAUxJglRIElYMA8wcwxX+AKNWjYBSMglEwAgEAPwpI5O13y7QAAAAASUVORK5CYII=","orcid":"","institution":"Somali Region Pastoral and Agropastoral Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Mahamed","middleName":"Dol","lastName":"Ateye","suffix":""},{"id":447524323,"identity":"07f4dd57-334e-42a6-9ce7-eb7d6463c571","order_by":1,"name":"Abdulkarim Mohammed Ali","email":"","orcid":"","institution":"Somali Region Pastoral and Agropastoral Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Abdulkarim","middleName":"Mohammed","lastName":"Ali","suffix":""},{"id":447524325,"identity":"1c8569b0-988d-49ef-81d1-181f6f0fbbd4","order_by":2,"name":"Shamsedin Mahdi Hassan","email":"","orcid":"","institution":"Jigjiga University","correspondingAuthor":false,"prefix":"","firstName":"Shamsedin","middleName":"Mahdi","lastName":"Hassan","suffix":""},{"id":447524326,"identity":"23e517d9-2886-4c44-9114-a16085ae0a5f","order_by":3,"name":"Hodo Mohamed Jama","email":"","orcid":"","institution":"Somali Region Pastoral and Agropastoral Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Hodo","middleName":"Mohamed","lastName":"Jama","suffix":""},{"id":447524327,"identity":"d6ce51a4-8fe1-4a45-b830-b7608cc2e3d6","order_by":4,"name":"Abdikadir Sheikh Abdurahman","email":"","orcid":"","institution":"Somali Region Pastoral and Agropastoral Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Abdikadir","middleName":"Sheikh","lastName":"Abdurahman","suffix":""}],"badges":[],"createdAt":"2024-11-08 11:38:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5416187/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5416187/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81524539,"identity":"47a234ab-4463-4912-be0b-4ba46844ed91","added_by":"auto","created_at":"2025-04-28 08:30:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1211315,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5416187/v1/ecd83c58-ce69-48e9-92a6-72114587e992.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of Nutritional Composition: Proximate and Mineral Content of Soybean Varieties ","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSoybean, scientifically known as \u003cem\u003eGlycine max\u003c/em\u003e (L.), originated in East Asia, likely in the northern and central regions of China. Mature soybean seeds are composed of approximately 40% protein, 20% oil, and 10% water-soluble carbohydrates [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As a vital legume, \u003cem\u003eGlycine max\u003c/em\u003e is increasingly consumed for its nutritional and economic benefits [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Its high-quality protein and oil are essential for human health, making soybeans a significant component of human diets [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Soybean quality is typically assessed based on protein, oil, fatty acid, and mineral content, as these factors are crucial for enhancing human and animal nutrition. Due to their affordability, soybeans provide an excellent source of protein, minerals, phosphorus, and vitamins [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSoybean products are widely recognized for their positive contributions to health and wellness. Regular consumption of soybeans has been associated with the prevention of several chronic conditions, including heart disease, obesity, hypercholesterolemia, cancer, diabetes, kidney disease, and osteoporosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, soybeans serve as a valuable protein source for individuals who are allergic to animal milk [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among cereals and legumes, \u003cem\u003eGlycine max\u003c/em\u003e stands out for its high protein content, which reaches 40%. In comparison, other legumes typically contain 20\u0026ndash;30% protein, while cereals range from 8\u0026ndash;15% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, a study of six soybean varieties in Bilo-19 reported a high protein content of 47.63 g/100 g, while the variety Ethio-Yugoslavia recorded the lowest protein content at 35.31 g/100 g, with this difference being statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The average protein content across the six varieties was 37.10 g/100 g [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSoybeans are particularly valued as a plant-based protein due to their cholesterol-lowering effects in patients with type II hyperlipoproteinemia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to their high protein levels, soybeans contain approximately 20% oil, the second-highest oil content among all food legumes. Peanuts have the highest oil content at about 48% on a dry matter basis, followed by chickpeas with around 5% oil [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSoybeans are also rich in essential minerals and vitamins such as iron, zinc, copper, thiamine, riboflavin, niacin, pantothenic acid, and phospholipids [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These vitamins and minerals play crucial roles in red blood cell formation due to their hematinic properties [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, soybeans are known to contain flavonoids, particularly isoflavones, which contribute to their cancer-fighting and disease-preventing properties.\u003c/p\u003e \u003cp\u003eAs part of the study evaluation of the proximate composition and mineral content of five soybean varieties in two research centers, various research centers under the Somali Region Pastoral and Agro-pastoral Research Institute (SoRPARI) have focused on developing and releasing soybean varieties. A proximate analysis is essential to assess the quality of these varieties.\u003c/p\u003e \u003cp\u003eThis research provides a comprehensive analysis of five distinct soybean varieties Pawe-01, Pawe-02, Pawe-03, Gizo, and Gezale by evaluating their nutritional quality, agronomic performance, functional properties, and anti-nutritional factors under diverse environmental conditions at Kelafo and Dolo-Ado research centers. By examining key nutritional parameters such as protein, fiber, and carbohydrate content, the study aims to identify the most suitable varieties for enhancing plant-based nutrition programs and optimizing breeding and food product development. This research holds significant value in addressing food insecurity, malnutrition, and mineral deficiencies, particularly in low-income communities, while also promoting agricultural sustainability. The findings will provide essential data to guide future breeding programs, improve the nutritional profile of soy-based foods, and contribute to public health outcomes in regions with limited access to diverse and nutrient-rich foods.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Adapting Soybean Cultivation to Arid and Semi-Arid Conditions\u003c/h2\u003e \u003cp\u003eThe cultivation of mature soybean seeds at the Kelafo and Dolo-Ado Research Centers, located in the Somali Regional State of Ethiopia, is designed to suit the region's arid and semi-arid agro-ecological conditions. The experiment was conducted during the 2021/2022 cropping seasons, using five released soybean varieties evaluated under a Randomized Complete Block Design with three replications. Each experimental unit consisted of four rows, every 4 meters in length, with a row-to-row spacing of 40 cm and a plant-to-plant spacing of 10 cm. The gross plot size was 4 m x 1.6 m, with data collected from the two middle rows. These research areas experience high temperatures, often exceeding 30\u0026deg;C, and low annual rainfall, ranging from 300 to 600 mm. Such climatic conditions require the selection of drought-tolerant soybean varieties capable of thriving under heat stress and limited moisture availability. Research and development efforts in these centers aim to optimize agricultural practices, ensuring crops like soybeans can flourish despite the challenges posed by the lowland elevation and the harsh climatic factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sample collection and preparation\u003c/h2\u003e \u003cp\u003eMature soybean seeds were sourced from the Kelafo and Dolo-Ado Research Centers, and two local varieties were purchased from the markets in Gode and Jigjiga cities, located in the Somali Regional State, Ethiopia. The seeds were thoroughly cleaned to remove foreign materials, and any damaged or insect-infested seeds were discarded. After washing with tap water, the seeds were sun-dried for 8 hours to eliminate any moisture absorbed during the washing process. They were then ground into flour using a laboratory hammer mill (Model NL-BL-4361, China), packed in airtight polyethylene bags, and stored at 4\u0026deg;C for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Determination of Proximate Composition\u003c/h2\u003e \u003cp\u003eUsing standard analytical methods (AOAC, 2023), the soybean varieties were analyzed for proximate composition, including ash, moisture, crude fat, crude fiber, crude protein, carbohydrate, and energy content [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. All measurements were performed in triplicate, with results expressed as percentages, except for energy value, which was reported in kcal/100 g. Carbohydrate content was calculated by difference (Eq.\u0026nbsp;1), and energy value (E.V.) was determined using the Atwater factor method (Eq.\u0026nbsp;2):\u003c/p\u003e \u003cp\u003e% Carbohydrate content\u0026thinsp;=\u0026thinsp;100% (% moisture + % protein + %Fat + %Ash) \u0026hellip;\u0026hellip; (1).\u003c/p\u003e \u003cp\u003eE.V = (9 x Crude Fat %) + (4 x Crude Protein %) + (4 x Carbohydrate %) \u0026hellip;\u0026hellip;\u0026hellip;(2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Determination of Mineral Content\u003c/h2\u003e \u003cp\u003eThe concentrations of selected mineral elements (Ca, Fe, Mg, and Zn) were determined from a solution prepared by wet digestion of the sample ash with a 1:1 (v/v) HCl and nitric acid mixture. The analysis was conducted using an atomic absorption spectrophotometer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data analysis\u003c/h2\u003e \u003cp\u003eAll analyses were performed in triplicate, and results were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error. Data analysis and modeling were carried out using GenStat version 18 and Excel 2019, with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 to determine statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Agronomic Performance of Soybean Varieties at Kelafo and Dolo-Ado Research Centers\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Dolo-Ado Center\u003c/h2\u003e \u003cp\u003eThe analysis of variance indicated that the varieties had no significant effect on the number of seeds per pod (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mean separation analysis revealed that Pawe-03 had the highest number of seeds per pod (2.633), which was statistically similar to Gizo. The lowest number of seeds per pod (2.433) was recorded for Pawe-01, with an overall mean of 2.500 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The highest hundred-seed weight was observed in Pawe-01 (9.083 g), which was statistically comparable to Pawe-02 (9.033 g), followed by Pawe-03. Pawe-02 had the lowest hundred-seed weight (10.04 g), while the overall average was 12.31 g (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The variation in hundred-seed weight among the varieties may be attributed to differences in seed size influenced by the growth environment. These variations are consistent with findings from the Sudanian Zone of Burkina Faso and Southwestern Ethiopia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, a meta-analysis reported that differences in hundred-seed weight among soybean varieties could be attributed to crop yield potential, growth rate, enhanced nutrient translocation, and genetic superiority [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis of variance showed no significant differences among the varieties in terms of days to maturity (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Pawe-02 had the longest duration to maturity (99.33 days), followed by Pawe-01 (97.83 days), which was statistically similar to Gizo. The shortest duration (95.33 days) was observed in Gazale, which was also comparable to Pawe-01 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The effect of varieties on plant height was non-significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The tallest plants were recorded in Gizo (63.37 cm), while the shortest were recorded for Pawe-01 (54.73 cm), with an overall mean of 59.8 cm (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Variety had no significant effect on the number of pods per plant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The highest number of pods per plant (62.53) was recorded in Gazale, while the lowest (54.57) was observed in Pawe-02, with an overall mean of 59.1 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The highest grain yield was recorded for Pawe-03 (1978 kg/ha), which was statistically similar to Pawe-02 (1972 kg/ha). Pawe-01 had the lowest grain yield (1205 kg/ha). The higher yields of Pawe-03 and Pawe-02 may be attributed to differences in growth habits and genetic potential, which contributed to variations in yield performance. These findings align with similar results reported in Northwestern Ethiopia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Kelafo Center\u003c/h2\u003e \u003cp\u003eThe Gizo variety exhibited the longest time to maturity (91.67 days), while Pawe-01 matured the earliest (89.33 days). This result is consistent with the findings of a study conducted in Ethiopia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The highest number of pods per plant was observed in Pawe-01 (58.67), while Pawe-02 had the lowest (47.37). This finding aligns with previous studies conducted in Northwestern Ethiopia [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, variations in the days to 90% maturity across different genotypes have been reported by [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], who also observed significant differences in the number of pods per plant, ranging from 70 to 35. Pawe-01 recorded the highest number of seeds per pod (3.158), which was statistically similar to Pawe-03, Gizo, and Gazale. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] also reported variations in the number of seeds per pod, ranging from 129.1 to 72.6. The highest hundred-seed weight was recorded for Pawe-01 (9.173 g), while Gizo had the lowest (7.107 g).\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\u003eMean of agronomic traits of soybean varieties tested at Kelafo and Dolo-ado centers\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\"\u003e \u003cp\u003eVarieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation\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\u003ePH(cm)(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPPP(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNSPP(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTSW(g)(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYield (Y) (kg/ha)(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGazale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDolo-ado Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.83a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.33a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.53a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.333a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.617b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1508b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.83a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.37a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.97a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.633a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.767b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1449b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.17a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.73a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.47a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.433a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.083a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1205c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.83a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.10a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.57a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.467a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.033a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1972a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.83a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.37a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.77a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.633a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.250ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1978a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGrand Mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCV%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e182.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGazale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eKelafo Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.83abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.85a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.65abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.158a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.150b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e887d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.67a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.35a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.88ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.158a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.107c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e946d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.33c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.30a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.67a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.108a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.137c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1188c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.83bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.63a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.37c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.608b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.173a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1372b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.42ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.28a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.83bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.158a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.033b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1539a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGrand Mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCV%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e132.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCV\u0026thinsp;=\u0026thinsp;Coefficient of Variation, LSD\u0026thinsp;=\u0026thinsp;Least Significant Difference. Means followed by different letters within columns are significantly different by Duncan\u0026rsquo;s new multiple range test (P\u0026thinsp;=\u0026thinsp;0.05). DM\u0026thinsp;=\u0026thinsp;Days to 90% maturity, PH (cm)\u0026thinsp;=\u0026thinsp;plant height(centi metter ), NPPP\u0026thinsp;=\u0026thinsp;number of pods per pl ant, NSPP\u0026thinsp;=\u0026thinsp;number of seed per pod, TSW (gram)\u0026thinsp;=\u0026thinsp;thousand seed weight, BM (kg/ha)\u0026thinsp;=\u0026thinsp;biomass\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Proximate composition of soybean varieties\u003c/h2\u003e \u003cp\u003eThe results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. K-Pawe-01 had the highest moisture content among all the varieties, though it was not significantly different from K-Pawe-02. The lowest moisture content was recorded in L-Jigjiga, which showed a significant difference compared to L-Gode. D-Pawe-01 showed the highest ash content, although this difference was not statistically significant except when compared to K-Gezale and the local varieties.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also indicates that D-Gezale had the highest crude fat content, while K-Pawe-03 showed no significant difference from G-Gezale. However, the regional varieties had the lowest crude fat content. The variations in crude fat content, particularly the lowest values observed in the Gizo variety at Dolo-Ado and the Gezale variety at Kelafo, may be attributed to environmental factors such as soil composition, temperature fluctuations, and water availability. These factors play a critical role in lipid metabolism, ultimately influencing fat accumulation and the overall nutritional profile of the soybean varieties.\u003c/p\u003e \u003cp\u003eAdditionally, the data revealed that the local varieties contained higher fiber content than the others. D-Pawe-03 had the highest protein content, while the local varieties had the lowest. Carbohydrate content was more pronounced in the regional varieties, with significant differences observed among them. K-Pawe-01 had the lowest carbohydrate content. In terms of energy content, D-Gezale recorded the highest value, with no significant differences from D-Pawe-01, D-Pawe-02, K-Gizo, K-Pawe-01, K-Pawe-02, and K-Pawe-03. The control samples from Gode and Jigjiga had significantly lower crude fat content, indicating non-standard quality. They were included to represent local soybeans and serve as a baseline for comparison. Their lower nutritional values highlight the need for improved varieties to ensure better nutritional outcomes.\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\u003eProximate Composition of Different Soybean Varieties\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\u003eVarieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMoisture (%)\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\u003eCrude Fat (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003cp\u003eProtein (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCrude Fiber (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCarbohydrate Content (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEnergy (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGezale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDolo-ado Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e450.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e399.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eefg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e489.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e487.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003efg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e481.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGezale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eKelafo Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.35\u0026thinsp;\u0026plusmn;\u0026thinsp;03\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e465.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e439.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e487.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e488.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e430.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e366.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJigjiga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e372.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGrand Mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e468.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCV %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLSD %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eAll values are the means expressed on a dry matter basis\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error. Means with the same superscripts do not differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), D\u0026thinsp;=\u0026thinsp;Dolo-Ado, K\u0026thinsp;=\u0026thinsp;Kelafo, CV\u0026thinsp;=\u0026thinsp;Coefficient of Variation, LSD\u0026thinsp;=\u0026thinsp;Least Significance Difference.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Mineral contents and anti-nutritional factors of different soybean varieties\u003c/h2\u003e \u003cp\u003eThe results of the mineral element analysis, including calcium, iron, magnesium, and zinc, are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, with concentrations expressed as mg/100 g in the dry matter of soybean flour. Variety K-Pawe-03 had the highest calcium content, followed by D-Pawe-03 and D-Gizo, though there was no significant difference between D-Pawe-03 and D-Gizo. K-Pawe-03 also had the highest iron content among all the varieties, while the local varieties showed the lowest mineral content overall. Regarding magnesium, K-Pawe-02 exhibited the highest content, with K-Pawe-03 ranking next. The results indicate that K-Pawe-03 had significantly higher levels of all the analyzed minerals than the other varieties. The lowest zinc content was found in L-Jigjiga.\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\u003eTotal mineral contents of different soybean varieties\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVarieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eParameters (mg/100 g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalcium %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIron %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMagnesium %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZinc %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGezale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDolo-ado Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.570\u0026thinsp;\u0026plusmn;\u0026thinsp;36.07\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e930.9\u0026thinsp;\u0026plusmn;\u0026thinsp;36.07\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.040\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.765\u0026thinsp;\u0026plusmn;\u0026thinsp;111.75\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1144.1\u0026thinsp;\u0026plusmn;\u0026thinsp;111.75\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.030\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.105\u0026thinsp;\u0026plusmn;\u0026thinsp;67.80\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1073.5\u0026thinsp;\u0026plusmn;\u0026thinsp;67.80\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.000\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.990\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1231.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.075\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.815\u0026thinsp;\u0026plusmn;\u0026thinsp;16.23\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1140.0\u0026plusmn;`6.23\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.680\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGezale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eKelafo Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.165\u0026thinsp;\u0026plusmn;\u0026thinsp;11.90\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e978.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.90d\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.450\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGizo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.355\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ebcde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1117.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13cd\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.275\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30a\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.715\u0026thinsp;\u0026plusmn;\u0026thinsp;61.65\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1095.1\u0026thinsp;\u0026plusmn;\u0026thinsp;61.64\u003csup\u003ecde\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.385\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.110\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2429.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.120\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePawe-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.060\u0026thinsp;\u0026plusmn;\u0026thinsp;9.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1378.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.960\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.705\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e658.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.275\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJigjiga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.375\u0026thinsp;\u0026plusmn;\u0026thinsp;123.48\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e945.3\u0026thinsp;\u0026plusmn;\u0026thinsp;123.48\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.790\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGrand Mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1177.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCV %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLSD %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAll values are the means expressed on a dry matter basis\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error. Means with the same superscripts do not differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), D\u0026thinsp;=\u0026thinsp;Dolo-Ado, K\u0026thinsp;=\u0026thinsp;Kelafo, CV\u0026thinsp;=\u0026thinsp;Coefficient of Variation, LSD\u0026thinsp;=\u0026thinsp;Least Significance Difference.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Proximate composition of Soybean\u003c/h2\u003e \u003cp\u003eThe study revealed that soybeans have a low moisture content, ranging from 4.78\u0026ndash;7.34%, which implies that soybeans can be stored for extended periods since low moisture levels inhibit the growth of microorganisms. This finding is consistent with a study conducted in Nigeria, which reported a moisture content of 6.12%, highlighting the potential for long-term storage without significant microbial growth [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The ash content in the soybean samples was notably high, ranging from 3.82\u0026ndash;6.30%, indicating that these soybeans are rich in minerals. This aligns with another Nigerian study reporting an ash content of 4.29% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The protein content ranged from 19.65\u0026ndash;30.35%, reflecting a high concentration of protein compounds, making soybeans a promising solution for addressing malnutrition, particularly protein-energy malnutrition conditions such as marasmus and kwashiorkor. The crude fat content in this study ranged from 5.37\u0026ndash;21.61%, with varieties like D-Gezale and K-Pawe-01 showing the highest values at 21.61% and 21.60%, respectively. Although the overall fat content was lower than that of some other sources, these results are consistent with the findings reported in the study [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The fiber content ranged from 3.75% (D-Gezale) to 6.29% (L-Jigjiga), which provides health benefits such as aiding digestion and reducing colon cancer risk [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Carbohydrate content ranged from 44.75\u0026ndash;68.82%, offering a high carbohydrate level essential for managing protein-energy malnutrition. These findings correspond to carbohydrate content values of 34.97\u0026ndash;39.86% reported in other studies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The energy content of the soybeans ranged from 403.1 kcal/100 g to 450.21 kcal/100 g, comparable to values reported in Ghana [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Mineral Concentrations of Soybean\u003c/h2\u003e \u003cp\u003eThe calcium content in soybean varieties ranged from 48.9\u0026ndash;157.21%, indicating their potential to develop complementary foods for infants. This is crucial, as calcium plays a significant role in bone and tooth development, which aligns with the findings reported in the study [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The iron content was high, ranging from 5.37\u0026ndash;12.06%, with K-Pawe-03 showing the highest value. This finding supports efforts to address iron deficiencies in vulnerable populations, aligning with the study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which highlights the critical role of iron in oxygen transport within the bloodstream. By addressing these deficiencies, it is possible to improve overall health outcomes, particularly for those at greater risk. Magnesium content is also significant and supports protein formation, calcium retention, and energy release. Zinc content ranged from 3.79\u0026ndash;6.45%, which is critical for immune health. These findings align with earlier studies on magnesium and zinc's roles in human health [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study highlights the superior nutritional value of soybean varieties from Kelafo and Dolo-Ado, particularly the Pawe and Gezale types. These varieties, such as K-Pawe-01, K-Pawe-03, D-Pawe-03, and D-Gezale, are rich in protein (28.73%-30.35%), fat (up to 21.61%), and carbohydrates (52.77%), making them ideal for food product development to combat protein-energy malnutrition. While the fiber content (3.75%-5.94%) is relatively low, it still supports digestive health. The high ash content indicates significant levels of essential minerals like calcium, magnesium, zinc, and iron, which are vital for bone health, immunity, and metabolic function. The findings suggest that these soybeans could be beneficial for food fortification and improving nutritional intake in regions facing malnutrition.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate Declarations\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have agreed to submit and publish this manuscript. We confirm that the manuscript, including any identifiable information, does not violate any confidentiality agreements and that consent for publication has been obtained from all relevant parties\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated and analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe confirm that all experimental and field research involving plants, whether cultivated or wild, including the collection of plant samples, complied with applicable institutional, national, and international guidelines and laws. No specific approvals were necessary for this study, as it adhered to all relevant regulations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSomali Region Pastoral and Agropastoral Research Institute (SoRPARI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMahamed Dol Ateye conceived the study, contributed to the study design, performed the analysis, and wrote the manuscript. Abdulkarim Mohammed Ali, Shamsedin Mahdi Hassan, and Hodo Mohamed Jama contributed to data duration and visualization. Mahamed Dol Ateye reviewed and edited the manuscript. All authors read and approved the final manuscript. Abdikadir Sheik has comprehensively analyzed various agronomic traits in soybeans, including yield, number of days to maturity, plant height, number of pods per plant, first pod height, and the weight of 1,000 seeds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the Somali Region Pastoral and Agropastoral Research Institute (SoRPARI) for their support and resources.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eByth, D. (1968). Comparative photoperiodic responses for several soya bean varieties of tropical and temperate origin. \u003cem\u003eAustralian Journal of Agricultural Research, 19\u003c/em\u003e(6), 879-90. https://doi.org/10.1071/ar9680879\u003c/li\u003e\n\u003cli\u003eBayero, A., Datti, Y., Abdulhadi, M., Yahya, A., Salihu, I., Lado, U., et al. (2019). 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Response of yield and quality of soybean [Glycine max (L.) Merrill] varieties to blended NPSZnB fertilizer rates in Northwestern Ethiopia. Heliyon, 8(5), e09499. https://doi.org/10.1016/j.heliyon.2022.e09499 \u003c/li\u003e\n\u003cli\u003eSileshi, Y., Yirga, M., Atero, B., Tesfaye, A., Bosa, D., \u0026amp; Hailemaria, M. (2022). Performance of Newly Released Early Maturing Soybean (Glycine max (L.) Merr.) Variety,\u0026lsquo;Guda\u0026rsquo;in the Major Growing Agro-ecologies of Ethiopia. Ethiopian Journal of Crop Science, 10(1). https://www.ajol.info/index.php/ejcs/article/view/243237 \u003c/li\u003e\n\u003cli\u003eNwosu, D. J., Olubiyi, M. R., Aladele, S. E., Apuyor, B., Okere, A. U., Lawal, A. I., Afolayan, G., Ojo, A. O., Nwadike, C., Lee, M.-C., \u0026amp; Nwosu, E. C. (2019). Proximate and mineral composition of selected soybean genotypes in Nigeria. Journal of Plant Development, 26, 67\u0026ndash;76. https://doi.org/10.33628/jpd.2019.26.1.67 \u003c/li\u003e\n\u003cli\u003eEtiosa, O. R., Chika, N. B., \u0026amp; Benedicta, A. (2017). Mineral and proximate composition of soya bean. Asian Journal of Physical and Chemical Sciences, 4(3), 1-6. https://doi.org/10.9734/ajopacs/2017/38530 \u003c/li\u003e\n\u003cli\u003eEshun, G. (2012). Nutrient composition and functional properties of bean flours of three soya bean varieties from Ghana. African Journal of Food Science and Technology, 3(8), 176-181. http://www.interesjournals.org/AJFST\u003c/li\u003e\n\u003cli\u003eMehas, K. Y. (2001). Food science: The biochemistry of food and nutrition. McGraw-Hill Education. https://doi.org/10.1108/nfs.2001.01731baf.006\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-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Soybean varieties, Proximate composition, Mineral content, Nutritional analysis","lastPublishedDoi":"10.21203/rs.3.rs-5416187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5416187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eSoybean is a valuable source of high-quality protein and oil, widely used in human diets. This study aimed to evaluate the proximate composition and mineral content of soybean varieties from two research centers (Kelafo and Dolo-ado centers). Mature soybean seeds were collected from Kelafo, Dolo-ado, and local markets. Proximate composition (moisture, ash, fat, protein, fiber) and mineral content (calcium, iron, magnesium, zinc) were analyzed using standard methods, with triplicate measurements.\u003c/em\u003e Data analysis and modeling were conducted using GenStat version 18 and Excel 2019. \u003cem\u003eMoisture content ranged from 4.78\u0026ndash;7.34%, protein 19.65\u0026ndash;30.35%, fat 5.37\u0026ndash;21.61%, and fiber 3.75\u0026ndash;6.29%. Calcium ranged from 48.9-157.2 mg/100g, iron 5.37\u0026ndash;12.06 mg/100g, magnesium 658.5-2429.1 mg/100g, and zinc 3.79\u0026ndash;6.45 mg/100g. Varieties K-Pawe-01, K-Pawe-03, D-Pawe-03, and D-Gezale exhibited high nutritional value, making them suitable for addressing protein-energy malnutrition and mineral deficiencies, particularly in vulnerable populations such as infants and lactating mothers.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Nutritional Composition: Proximate and Mineral Content of Soybean Varieties","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 08:22:01","doi":"10.21203/rs.3.rs-5416187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-29T05:34:12+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"230953293330731443182987253003170013824","date":"2025-05-07T12:05:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T16:12:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93444295121642307624843532263704986159","date":"2025-04-21T09:02:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88098387726879875415526816277067758643","date":"2025-04-14T15:03:21+00:00","index":"hide","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-01T11:10:13+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-24T09:44:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-22T06:07:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Food","date":"2025-03-05T14:18:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5ad061c3-2a10-4600-ac5b-0a272cb01292","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-03T13:24:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 08:22:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5416187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5416187","identity":"rs-5416187","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}