Introduction

Maize (Zea mays L.), a staple crop critical to global food security, is the most widely cultivated cereal worldwide, achieving a yield of 27,800 kg per hectare surpassing rice, wheat, and millets (FAO, 2023). Its versatility extends to human nutrition, animal feed, and industrial processing, while its grain traits and maturation periods are genetically adapted to thrive across diverse agroecological conditions. In Ethiopia, maize dominates cereal production, accounting for 88.69% of the total output (Central Statistical Agency, 2021). However, productivity remains constrained by labor-intensive manual planting practices. Traditional methods, plagued by inconsistent seed spacing, uneven depth placement, and significant physical exertion for farmers, compromise germination rates and yield optimization (Sinhaet al., 2021; Soyoye, Ademosun, and Agbetoye, 2018).

The design of seed planters’ hinges on critical physical of seed properties. Maize kernels, characterized by their angular shapes and varying densities, require carefully designed metering systems to reduce mechanical damage during the singulation process (Pascual, Rafael, Remocal, and Regalado, 2021; Shahet al., 2022). Key parameters include sphericity (governing seed plate cell dimensions), angle of repose (dictating hopper wall slopes for uninterrupted flow), and terminal velocity (influencing seed tube aerodynamics) (Sinhaet al., 2021). Density further modulates grain friction coefficients and brittleness, necessitating adaptive components to maintain seed integrity across postharvest handling and planting phases (Dinberu and Megersa, 2023). Neglecting these properties risks planter inefficiencies, including clogging, seed fracture, and placement inaccuracy factors that erode farmer trust and adoption (Omaret al., 2023).

In Ethiopia, agricultural mechanization strategies disproportionately prioritize wheat production, systematically neglecting the mechanization needs of smallholder farmers reliant on maize cultivation. Current multi-crop planters, predominantly retrofitted from temperate-region prototypes, demonstrate limited functional compatibility with indigenous maize varieties and local agroclimatic conditions. These mismatches manifest in critical agronomic inefficiencies, including excessive depth variability and seed spacing (±25% inaccuracy), undermining crop establishment and yield predictability (Lianget al., 2021; Seyoum, Paul, and Sinafikeh, 2013; Theodrose, Kindie, Mezegebu, Nigussie, and Mengistu, 2024). These inefficiencies arise from a systemic failure to integrate agronomic and operational parameters into planter design optimization (Ayele, 2022; Kebede, 2019).

Resolving these inefficiencies requires engineering property optimized planter components tailored to Ethiopia’s agroecology. Critical priorities are fluted roller meters that are 10% larger than kernel sizes to lower shear stress (< 2 MPa) (Lianget al., 2021; Singh, Sahoo, and Bisht, 2017), double-disk furrow openers with optimized rake angles for consistent depth in different soils, and seed tubes calibrated for velocity to achieve at least 85% spatial accuracy. This research thoroughly analyzed essential engineering characteristics to enhance a tractor-drawn multi-crop planter in accordance with Ethiopia's agricultural standards. Key parameters, such as planting depth, intra- and inter-row spacing, and planting density per hectare, are presented in Table 1.

Materials and Methods

Study location

The experiments were conducted at the Melkassa Agricultural Research Center of the Ethiopian Institute of Agricultural Research (EIAR). Located in the East Shewa Zone of the Oromia Region, at an altitude of 1,550 m above sea level, approximately 107 km from Addis Ababa, Ethiopia (Central Statistical Agency, 2021).

Determining maize seed physical properties

A representative sample of 100 seeds per variety was subjected to dimensional analysis using a digital caliper (resolution: ±0.01 mm) to measure axial dimensions (length l, width w, thickness t), as shown in Fig. 1. These measurements were used to calculate derived parameters such as the geometric mean diameter, sphericity, and aspect ratio, which are essential for understanding seed behavior and optimizing planter components.

Fig. 1. Maize seed dimensions (length, width, and thickness), and digital caliper

Mathematical modeling of seed properties

The engineering properties of Maize seeds were calculated using established mathematical models. These properties are critical for understanding seed behavior and optimizing the design of a tractor-drawn multi-crop planter.

Mean diameters

Mean diameters are fundamental geometric parameters used to quantify seed size and uniformity, which are critical for designing and optimizing seed metering mechanisms, hoppers, and other planter components. The arithmetic mean diameter (D_a), calculated as the average of the three principal linear dimensions length (l), width (w), and thickness (t) is expressed in Equation (1) (Kawuyo, Aviara, Mari, and Ahmed, 2022; Zewdie, Olaniyan, Wako, Alemu, and Lema, 2024):

$\begin{array}{cc}{D}_a=\frac{(l+w+t)}{3}& \mathrm{(1)}\end{array}$

This parameter provides a simplified measure of seed size and ensures compatibility with diverse seed dimensions. Geometric mean diameter (D_g) is calculated as the cube root of the product of the three principal linear dimensions: length (l), width (w), and thickness (t) diameters, as stated in Equation (2) (Panwar, Swarnkar, Kumar, and Shukla, 2023; Soyoyeet al., 2018):

$\begin{array}{cc}{D}_g={(l.w.t)}^{\frac{1}{3}}& \mathrm{(2)}\end{array}$

It is particularly useful for characterizing irregularly shaped seeds and optimizing seed flow, spacing, and interaction with planter components. Square mean diameter (D_s) which approximates the effective size of irregularly shaped seeds, is calculated using Equation (3) (Zewdieet al., 2024):

$\begin{array}{cc}{D}_s={\left(\right(l.w)+(l.t)+(w.t\left)\right)}^{\frac{1}{3}}& \mathrm{(3)}\end{array}$

where, l is the longest intercept, w is the longest intercept normal to l, t is the longest intercept normal to l and w. These parameters collectively ensure efficient seed handling and mechanical design for multi-crop planters.

Geometric properties

Geometric properties of seeds, such as projected area, surface area, and cross-sectional areas, are critical for analyzing seed orientation, flow dynamics, and mechanical interactions within planter components. The projected Area (A_p), which represents the two-dimensional area of a seed as seen from a specific angle, is calculated using Equation (4 ) (Lianget al., 2021; Zewdieet al., 2024):

$\begin{array}{cc}{A}_p=\frac{\pi }{4}(l.w)& \mathrm{(4)}\end{array}$

This parameter is essential for understanding seed visibility in 2D planes and optimizing optical sorting systems. The surface area (A_s) representing the total outer surface area of the seed, is approximated using the geometric mean diameter and is expressed in Equation (5) (Lianget al., 2021; Zewdieet al., 2024):

$\begin{array}{cc}{A}_s=\pi D_g^2& \mathrm{(5)}\end{array}$

It is crucial for predicting seed friction and drag in airflow systems. The transverse surface area (A_t), which represents the cross-sectional area perpendicular to the seed’s major axis, is calculated using Equation (6) (Lianget al., 2021; Zewdieet al., 2024):

$\begin{array}{cc}{A}_t=\frac{\pi }{4}(w.t)& \mathrm{(6)}\end{array}$

This parameter quantifies the seed’s resistance in seed tubes and other mechanical components. Finally, the cross-Sectional area (A_cs), which represents the surface exposed when the seed is sliced along a specific plane, is given in Equation (7) (Lianget al., 2021; Zewdieet al., 2024):

$\begin{array}{cc}{A}_{\mathrm{cs}}=\frac{\pi }{4}(l.t)& \mathrm{(7)}\end{array}$

Shape indices

Shape indices are critical parameters for quantifying seed morphology, which directly influence seed flow, orientation, and mechanical interactions in planter components. The sphericity (Φ), which indicates how closely a seed resembles a sphere, is calculated using Equation (8) (Panwaret al., 2023):

$\begin{array}{cc}\Phi =\frac{{(l.w.t)}^{\frac{1}{3}}}{l}& \mathrm{(8)}\end{array}$

A perfect sphere has a sphericity of 100 %, and this parameter is essential for optimizing seed flow in hoppers and tubes. The flakiness ratio (F_r), which measures seed flatness, is expressed in Equation (9) (Lianget al., 2021; Panwaret al., 2023; Zewdieet al., 2024):

$\begin{array}{cc}{F}_r=\left(\frac{t}{w}\right)\mathrm{100}\%& \mathrm{(9)}\end{array}$

It helps prevent clogging in seed metering mechanisms. The aspect ratio (A_r), which quantifies the relative width-to-thickness proportion, is calculated using Equation (10) (Panwaret al., 2023):

$\begin{array}{cc}{A}_r=\left(\frac{w}{t}\right)\mathrm{100}\%& \mathrm{(10)}\end{array}$

This parameter is crucial for assessing seed stability during orientation. The shape index (S_I), which provides an indication of the relative proportions of the seed’s dimensions, is given in Equation (11) (Lianget al., 2021; Zewdieet al., 2024):

$\begin{array}{cc}{S}_I=\frac{1}{\sqrt{w.t}}& \mathrm{(11)}\end{array}$

It is useful for analyzing shape irregularities and optimizing seed sorting systems. Finally, the roundness (R) which quantifies how closely the two-dimensional profile of a seed approximates a perfect circle and is calculated using Equation (12) (Ghabshyam, Raghunandan, Pankaj, and Kripanarayan, 2023; Zewdieet al., 2024):

$\begin{array}{cc}R=\frac{4A_p}{\pi l^2}& \mathrm{(12)}\end{array}$

where, A_p is the projected area of the seed and l is the seed length.

Determination of angle of repose

The angle of repose for maize seeds was determined using a funnel setup, where seeds flowed freely onto a closed container to form a conical heap, following methodologies validated in seed flow studies (Huang, 2022; Kawuyoet al., 2022). The apex height (h) and the base radius (r) of the formed cone were measured to calculate the angle of repose (θ), as mentioned in Equation (13) below (Zewdieet al., 2024). Using the trigonometric relationship, the angle of repose is computed as:

$\begin{array}{cc}\theta ={\tan }^{\mathrm{-1}}\left(\frac{h}{r}\right)& \mathrm{(13)}\end{array}$

Determination of the gravimetric parameters

The gravimetric properties of three maize varieties, including porosity, density ratio, and true and bulk density, were analyzed using toluene displacement and weight-volume methods as presented in Equations (14)-(18) below (Soyoyeet al., 2018; Zewdieet al., 2024). Each variety's thousand-seed mass was determined using a digital balance with a precision of 0.001 g, complemented by supplementary tools like graduated cylinders, beakers, and stirring rods, as illustrated in Fig. 2 (Panwaret al., 2023).

True density ρ_t (kg m^-3):

$\begin{array}{cc}{\rho }_t=\frac{\mathrm{Weight\; of\; the\; maize\; sample}\left(g\right)}{\mathrm{Volume\; of\; toluene\; displaced}\left({\mathrm{cm}}^3\right)}& \mathrm{(14)}\end{array}$

Bulk density ρ_b (kg m^-3):

$\begin{array}{cc}{\rho }_b=\frac{\mathrm{Weight\; of\; the\; maize\; sample}\left(g\right)}{\mathrm{Volume\; of\; toluene\; displaced}\left({\mathrm{cm}}^3\right)}& \mathrm{(15)}\end{array}$

Porosity ε (%):

$\begin{array}{cc}\epsilon =(1-\frac{{\rho }_b}{{\rho }_t})\mathrm{100}\%& \mathrm{(16)}\end{array}$

Density ratio R_ρ (%):

$\begin{array}{cc}{R}_{\rho }=\left(\frac{{\rho }_b}{{\rho }_t}\right)\mathrm{100}\%& \mathrm{(17)}\end{array}$

Thousand seed mass T_sm (g):

$\begin{array}{ccc}{T}_{\mathrm{sm}}=\left(\frac{{\sum }_i^n\mathrm{weight\; of\; the\; Maize\; samples}\left(g\right)}{n}\right)\mathrm{1000},& i=1,2,3,\mathrm{...},n& \mathrm{(18)}\end{array}$

Fig. 2. Instruments for measuring gravimetric properties: (a) Digital balance, (b) 250 ml cylinder, (c) funnels, and (d) toluene; Photo taken during lab experiment by author

Statistical analysis

Statistical analysis was conducted using Minitab Statistical Software to compute key metrics, including means, standard deviations, and variance. These statistical parameters were used to validate the robustness of the data and inform the design and optimization of the multi-crop planter. The results ensured compatibility with the physical properties of maize seeds, enhancing the planter’s efficiency and performance (Lianget al., 2021; Zewdieet al., 2024).

Results and Discussion

The physical properties of three maize varieties (CML-539, Melkassa 3, and Melkassa 6Q) were analyzed to optimize multi-crop planter design, as illustrated in the Table 3 and Table 4 below. Kernel dimensions varied significantly across varieties. Melkassa 3 and CML-539 exhibited the longest seed lengths of 10.99 ± 0.94 mm and 9.42 ± 8.06 mm, respectively, as shown in Table 2. This data highlights the need for adjustable seed plates with cell sizes that are 15-20% larger than the maximum seed dimensions to avoid any clogs, corroborating the findings of Lianget al. (2021) and Sinha (2021). The thickness, essential for effective singulation, remained consistent within the range of 4.824-4.984 mm. However, Melkassa 3 exhibited a higher variance of 0.892, which corresponds with Lianget al. (2021) findings that attribute this variability to the wear of seed plates.

Elongation ratios revealed critical design differences: Melkassa 3 and Melkassa 6Q exhibited higher thickness elongation (2.337± 0.514 and 2.334± 0.457, respectively) than CML-539 (1.997± 0.383), increasing tilt risks during free fall. This aligns with Panwar (2023b), which associates ratios greater than 2.0 with trajectory errors, highlighting the need for curved seed tubes. Mean diameters further guided hopper design: CML-539’s geometric mean diameter (8.019± 2.736 mm, CV 34.12%) highlighted irregular shapes, contrasting with Melkassa 6Q’s stability (8.198± 0.382 mm, CV 4.66%), and enabled more uniform flow dynamics, supporting conventional hopper design. Such variability aligns with Dinberu (2023), who noted similar challenges in Ethiopian maize, advocating steeper hopper angles (> 35°) for low-sphericity grains.

A Comparative analysis underscored Ethiopia’s unique needs. Melkassa 3’s width (8.913 mm) exceeded the 8.5 mm threshold for fluted rollers (Sharma and Dewangan, 2023), while CML-539’s arithmetic mean diameter of 7.509 mm (Table 2), fell below the 8.0 mm benchmark, explaining reported spacing deviations (Omaret al., 2023). Melkassa 6Q’s sphericity mirrored commercial hybrids, suggesting compatibility with standardized planters. CML-539's irregular seeds (CV of 34.12%) require vibration-assisted metering to prevent mechanical damage, while Melkassa 3's high elongation ratio exceeding 2.3 demands air-assisted tubes to ensure stable seed orientation crucial for smallholder planting.

Table 3 highlights key geometric properties of maize varieties critical for planter optimization. The square mean diameter demonstrated only slight variation, ranging from 5.631 to 5.791 mm, with CML-539 showing higher variability (CV 10.74%) compared to Melkassa 3 (3.95%) and Melkassa 6Q (3.31%). This observation, shown in Table 3, is consistent with Dinberu (2023), who attributed this stability to the reliable performance of seed plates. Surface area and projected area revealed stark contrasts: CML-539 exhibited extreme variability, with a surface area coefficient of variation (CV) of 43.78% and a projected area CV of 82.22%. This variability underscores the irregular shape of the kernels, which poses a challenge for achieving uniform seed distribution in non-spherical grains. In contrast, Melkassa 6Q’s lower surface and projected area variability (CV 11.27-11.96%) suggests suitability of this variety for the standardized metering systems (Kara, 2011; Masa, Tana, and Abdulatif, 2017).

Sphericity further differentiated varieties: CML-539 (78.31±13.09%) surpassed Melkassa 3 and Melkassa 6Q, indicating marginally better flowability (Table 3). However, its high sphericity variability (CV 16.72%) contrasts with Melkassa 6Q’s uniformity (CV 9.37%), reinforcing the need for adaptive hopper designs, particularly because low-sphericity grains below 75% necessitate steeper angles to prevent clogging (Girma, Tola, and Olaniyan, 2024; Rabbani, Hossain, Asha, and Khan, 2016). Shape index and roundness underscored design risks: CML-539’s higher shape index (1.485 ± 0.224) and roundness variability of 62.98% correlate with Panwar (2023b) findings of increased seed bridging in asymmetric grains, necessitating vibration-assisted hoppers.

CML-539’s flakiness ratio of 57.73± 13.63 and cross-sectional area variability of 160.75% far exceed values reported by Sharma (2023) for commercial hybrids of flakiness < 50% and CV < 20%, demanding robust metering mechanisms. Conversely, Melkassa 3 and Melkassa 6Q’s moderate aspect ratios align with Omar (2023) guidelines for gravity fed seed tubes but require air assistance to counter tilting caused by elongation. These results validate that Ethiopia’s maize diversity, particularly CML-539’s irregularity, demands planter components tailored to local varietals, such as adjustable cell sizes and aerated seed tubes, to achieve the precision required for smallholder farming systems.

The gravimetric properties essential for optimizing the design and functionality of maize planter hoppers and storage systems are presented in Table 4. True density showed a near-perfect negative correlation with thousand seed mass (-0.991) and a strong negative correlation with porosity (-0.904), while bulk density positively correlated with flowability metrics. Melkassa 6Q's optimal combination of high bulk density (811.62 kg m-3), low porosity (36.99%), and favorable density ratio (0.630) suggests superior flow characteristics compared to CML-539's high-porosity grains (49.30%), which require greater aeration power (Lianget al., 2021; Panwaret al., 2023; 33 Soyoye et al., 2018).

Thousand-seed mass varied significantly among varieties, with Melkassa 6Q (297.06 g) and Melkassa 3 (290.84 g) exceeding CML-539 (224.11 g) by 32.5% (Table 4). This highlights the impact of varietal mass loading on seed metering mechanisms, as higher thousand seed mass of greater than 280 g increases torque and drive power requirements, consistent with Dinberu (2023) and Panwar (2023b). Melkassa 6Q's steeper angle of repose (31°) aligns with its high bulk density and correlates with increased inter-kernel friction, necessitating steeper hopper angles, while Melkassa 3's smoother grains (26° repose) may require flow restrictors. These findings, consistent with Lianget al. (2021) and Panwar (2023b), demonstrate how correlated physical properties directly inform equipment specifications for different maize varieties.

Table 5 provides a comprehensive overview of the physical characteristics of different maize varieties, focusing on geometric parameters, shape indices, and gravimetric properties. This information is vital for the optimal performance of adaptive multi-crop planters, as it directly impacts mechanical reliability, reduces seed damage and variation, and ensures precise depth control for improved spacing accuracy. This integrated system enhances seed placement precision while simultaneously improving input use efficiency and operational reliability across diverse seed morphologies and field conditions, demonstrating robust improvements in both agronomic outcomes and field productivity.

Conclusion

This study analyzes three maize varieties (CML-539, Melkassa 3, and Melkassa 6Q) to establish quantitative relationships between seed physical properties and planter design parameters for adaptive multi-crop systems. The distinct physical properties of each variety dictate specific design requirements: CML-539's irregular dimensions (9.42 mm length, 49.30% porosity) and steep repose angle (31°) necessitate aerated seed tubes, vibration-assisted hoppers, and enlarged seed plates (15-20% oversizing), while Melkassa 6Q's uniform sphericity (71.11 ± 6.66%), high bulk density (811.62 kg m-3), and lower repose angle (26°) enable simpler gravity-fed systems. Melkassa 3's intermediate characteristics, specifically an elongation ratio > 2.3 and density variation of 19.31%, require adjustable furrow openers with 25-30° rake angles to maintain consistent sowing depth. These findings demonstrate that varietal specific modifications, particularly for seed metering, hopper design, and depth control, are essential for optimizing planting efficiency and seed integrity. The results demonstrate a seed-property-driven framework for modular planters that addresses diverse maize varieties while meeting standard agronomic requirements of 75 cm row spacing, and 4-7 cm planting depth, offering a scalable precision agriculture solution. Future field tests and real-time sensing could enhance this seed-specific planter design for precision agriculture.

Acknowledgments

We express our gratitude to the Department of Agricultural Engineering at Awash Melkassa Agricultural Research Center for providing the improved common maize seed varieties and the Department of Chemistry at Adama Science and Technology University for the laboratory facilities.

Conflict of Interest: The authors declare no competing interests.

Author Contributions

D. Girma Gadisa: Main Researcher, Conceptualization, Methodology, Data Collection, and Writing

K. Purushottam Kolhe: Formal Analysis, Writing Review and Editing

S. Kedir Busse: Supervision, Writing Review and Editing

M. Mohammed Issa: Data Collection, Resources, and Supervision

T. Assefa Abeye: Data Collection, Analysis

D. Alemu Anawte: Review, Editing

References

1. Alemayehu, A., Tamado, T., Nigussie, D., Yigzaw, D., Kinde, T., and Wortmann, C. S. (2017). Maize common bean intercropping to optimize maize-based crop production. The Journal of Agricultural Science, 155(7), 1124-1136.DOI
2. Ayele, S. (2022). The resurgence of agricultural mechanisation in Ethiopia: rhetoric or real commitment? Journal of Peasant Studies, 49(1), 137-157.DOI
3. Balanian, H., Karparvarfard, S. H., Mousavi Khanghah, A., Raoufat, M. H., and Azimi-Nejadian, H. (2021). Prediction of Seed Flow Rate of a Multi-Slot Rotor Feeding Device of a Corn Planter. Journal of Agricultural Machinery, 11(1), 17-27.DOI
4. Bhiman, J., Patel, S., Yaduvanshi, B., and Gupta, P. (2019). Optimization of the operational parameters of a picking-type pneumatic planter using response surface methodology. Journal of AgriSearch, 6(1), 38-43.DOI
5. Bisrat, G., Laike, K, A., and Hae, K. K. (2015). Evaluation of Conservation Tillage Techniques for Maize Production in Ethiopia. Ethiopian Journal of Agricultural Sciences, 25(2), 47-58.
6. Central Statistical Agency. (2021). Farm Management Practices Agricaltural Sample Survey 2020/21. In Central Statistical Agency: Vol. III (Issue 12). Retrieved from https://www.statsethiopia.gov.et
7. Dinberu, A., and Megersa, M. (2023). Effect of Inter and Intra Row Spacing on Growth , Yield and Yield Components of Sorghum (Sorghum bicolor (L.) Moench ) at Assosa District , Western Ethiopia. American Journal of Plant Biology, 8(1), 20-24.DOI
8. FAO. (2023). Standard operating procedure for soil bulk density; Cylinder method. Food and Agriculture Organization of the United Nations.DOI
9. Getaneh, L., Belete, K., and Tana, T. (2016). Growth and Productivity of Maize (Zea mays L.) as Influenced by Inter- and Intra-Row Spacing in Kombolcha, Eastern Ethiopia. Journal of Biology, Agriculture and Healthcare, 6(13), 90-101.DOI
10. Ghabshyam, P., Raghunandan, S., Pankaj, G., and Kripanarayan, S. (2023). A review of methodologies and influencing factors in planter performance evaluation for higher maize yield. The Pharma Innovation Journal, 12(12), 1465-1471. Retrieved from www.thepharmajournal.com
11. Girma, O., Tola, S., and Olaniyan, A. (2024). Design and development of a tractor-drawn multi-row garlic planter. Agricultural Engineering International: CIGR Journal, 26(2), 34-56.
12. Huang. (2022). Measurement of physical properties of sorghum seeds and calibration of discrete element modeling parameters. Agriculture (Switzerland), 12(5), 2-19.DOI
13. Jyotirmay, M., Prem, S. T., Krishna, P. S., Balaji, M. N., Jagjeet, Singh, A., and Ramesh, K. S. (2024). Flexible orifice seed metering plate to address variability in seed shape, size and orientation enhances field performance of a pneumatic planter. Discover Applied Sciences, 6(11).DOI
14. Kara, B. (2011). Effect of seed size and shape on grain yield and some ear characteristics of maize. Research on Crops, 12(3), 680-685.
15. Kawuyo, U. A., Aviara, N. A., Mari, H. H., and Ahmed, B. M. (2022). Physical properties of four varieties of sorghum grain at different moisture contents. Arid Zone Journal of Engineering, Technology and Environment, 18(1), 159-168. Retrieved from www.azojete.com.ng
16. Kebede, M. B. (2019). Effect of Inter and Intra Row Spacing on Growth , Yield Components and Yield of Hybrid Maize (Zea mays L.) Varieties at Haramaya, Eastern Ethiopia. American Journal of Plant Sciences, 10(7), 1548-1564.DOI
17. Kimmelshue, C. L., Goggi, S., and Moore, K. J. (2022). Seed Size, Planting Depth, and a Perennial Groundcover System Effect on Corn Emergence and Grain Yield. Agronomy, 12(2).DOI
18. Liang, G., Chi, B., Li, N., Chen, W., Qin, W., Wu, X., and Huang, X. (2021). Evaluating agronomic factors for maize production in a semi-arid Loess Plateau. Agronomy Journal, 113(6), 5157-5169.DOI
19. Masa, M., Tana, T., and Abdulatif, A. (2017). Effect of Plant Spacing on Yield and Yield Related Traits of Common Bean Varieties at Areka ,Southern Ethiopia. Journal of Plant Biology and Soil Healt, 4(2).DOI
20. Meseret, A. (2024). Performance Evaluation of Two Row Animal Drawn Maize Planter with Fertilizer Applicator. Turkish Journal of Agricultural Engineering Research, 5(2), 153-166.DOI
21. Muhidin, B. (2019). Effect of Inter-and Intra-Row Spacing on Yield and Yield Components of Maize QPM Hybrid, BHQPY545 in Southwestern Ethiopia Muhidin. International Journal of Research Studies in Agricultural Sciences, 6(10), 19-26.
22. Omar, S., Abd Ghani, R., Khalid, N., Jolánkai, M., Tarnawa, Á., Percze, A., Mikó, P. P., and Kende, Z. (2023). Effects of Seed Quality and Hybrid Type on Maize Germination and Yield in Hungary. Agriculture, 13(9), 2-14.DOI
23. Pandey, H. S., and Sawant, C. P. (2023). Design and Development of a Seed Metering Mechanism for Ginger Planter. Journal of Scientific and Industrial Research, 82(10), 1071-1080.DOI
24. Panwar, G., Swarnkar, R., Kumar, N., and Shukla, K. (2023). Evaluation of physical properties of maize and pigeonpea seeds for seed metering mechanism. Journal of Experimental Agriculture International, 45(12), 89-97.DOI
25. Pascual, K. S., Rafael, M. L., Remocal, A. T., and Regalado, M. J. C. (2021). Development and evaluation of four-wheel tractor-attached multi-crop planter for mechanized seeding of maize in the Philippines. CIGR Journal, 23(3), 143.
26. Patel, S. K., Bhimani, J. B., Yduvanshi, B. K., and Gupta, P. (2024). Radish (Raphanus raphanistrum subsp. sativus) Seed Planter Parameters Optimization using Response Surface Methodology. Journal of Scientific and Industrial Research, 83(5), 483-489.DOI
27. Rabbani, M. A., Hossain, M. M., Asha, J. F., and Khan, N. A. (2016). Design and development of a low cost planter for maize establishment. Journal of Science Technology and Environment Informatics, 4(1), 270-279.DOI
28. Seyoum, A., Paul, D., and Sinafikeh, A. (2013). Crop production in Ethiopia: Regional patterns and trends. Food and Agriculture in Ethiopia: Progress and Policy Challenges, 9780812208, 53-83.DOI
29. Shah, K., Alam, M. S., Nasir, F. E., Qadir, M. O., Haq, I. U., and Tahir Khan, M. (2022). Design and performance evaluation of a novel variable rate multi-crop seed metering unit for precision agriculture. IEEE Access, 10(September), 133152-133163.DOI
30. Sharma, P. T., and Dewangan, K. N. (2023). Design and development of a vertical plate precision seed metering device with positive seed knockout mechanism. Agricultural Engineering International: CIGR Journal, 25(1), 27-42.
31. Singh, S., Sahoo, D. C., and Bisht, J. K. (2017). Development and performance evaluation of manual/bullock operated multicrop planter for hilly region. Agricultural Engineering International: CIGR Journal, 19(1), 81-86.
32. Sinha, A. K., Sinha, A. K., Sharma, S., Khar, S., Gupta, V., Parkash, S., Mishra, S. K., and Gupta, S. (2021). Maize sowing with multi crop planter under rain fed conditions in Rajouri District of J and K proved beneficial. Journal of Krishi Vigyan, 9(2), 120-123.DOI
33. Soyoye, B. O., Ademosun, O. C., and Agbetoye, L. A. S. (2018). Determination of some physical and mechanical properties of soybean and maize in relation to planter design. Agricultural Engineering International: CIGR Journal, 20(1), 81-89.
34. Theodrose, S., Kindie, T., Mezegebu, G., Nigussie, D., and Mengistu, K. (2024). Calibration and Evaluation of CERES-Maize and CROPGRO-Dry Bean Crop Simulation Models of the DSSAT in the Great Rift Valley Region of Ethiopia. International Journal of Applied Agricultural Sciences, 10(4), 149-156.DOI
35. Tolossa, A., and Gizawu, T. (2024). Effect of Intra and Inter Row Spacing on Yield, Yield Components and Growth Parameter of Hybrid Maize at Mettu, South Western Ethiopia. Journal of Environment and Earth Science, 10(1), 16-19.DOI
36. Van Loon, J., Krupnik, T. J., López-Gómez, J. A., Timsina, J., and Govaerts, B. (2020). A standard methodology for evaluation of mechanical maize seed meters for smallholder farmers comparing devices from Latin America, Sub-Saharan Africa, and Asia. Agronomy, 10(8).DOI
37. Woldesenbet, M. (2014). Effect of Spacing on the Growth Parameters of Common Bean at Keker, Southwestern Ethiopia. International Journal of Research in Agricultural Sciences, 1(5).
38. Zewdie, B., Olaniyan, A. M., Wako, A., Alemu, D., and Lema, T. (2024). Engineering properties of common bean in perspective of physical and frictional parameters for threshing machine design. INMATEH Agricultural Engineering, 73(2), 771-783.DOI