A Comprehensive Systematic Review of Precision Planting Mechanisation for Sesame: Agronomic Challenges, Technological Advances, and Integration of Simulation-Based Optimisation

Abstract

The mechanisation of sesame (Sesamum indicum L.) planting remains a significant challenge due to the crop’s small, fragile seeds and non-uniform shape, which hinder the effectiveness of standard seeding systems. Crop emergence and production are adversely affected by poor singulation and uneven seed distribution, which are frequently caused by conventional and general-purpose planting equipment. For sesame, consistency in seed distribution and emergence is very important, necessitating careful consideration of agronomic conditions as well as seed properties. This study was conducted as a systematic review following the PRISMA 2020 guidelines to critically evaluate the existing literature on advanced planting methods that prioritise precision, efficiency, and seed protection. A comprehensive search was conducted across Scopus, Web of Science, and Google Scholar for peer-reviewed studies published from 2000 to 2025. Studies focused on the agronomic parameters of sesame, planting technologies, and/or simulation integration, such as Discrete Element Modelling (DEM), were included in this review, and studies unrelated to sesame planting or not available in full text were excluded. The findings from these studies were analysed to examine the interaction between seed metering mechanisms and seed morphology, specifically seed thickness and shape variability. Agronomic parameters such as optimal seed spacing, sowing depth, and population density are analysed to guide the development of effective planting systems. The review also evaluates limitations in existing mechanised approaches while highlighting innovations in precision planting technology. These include optimised seed plate designs, vacuum-assisted metering systems, and simulation tools such as DEM for performance prediction and system refinement. A total of 22 studies were included and analysed using systematic narrative synthesis, grouped into agronomical, technological, and simulation-based themes. The studies were screened for methodological clarity, and reference list screening was performed to reduce reporting bias. In conclusion, the findings of this research support the development of crop-specific planting strategies tailored to meet the unique requirements of sesame production.

1. Introduction

Sesame (Sesamum indicum L.) is one of the oldest oilseed crops, highly valued for its uses in culinary, medical, and industrial applications, including food processing, whole seed consumption, oil extraction, and some pharmaceutical formulation [1,2,3]. The cultivation of sesame has expanded throughout the subtropical and tropical regions of Asia, Australia, Europe, and America [4]. Sesame seeds are characterised by significant oil content, ranging from 46% to 50%, with 83% to 90% unsaturated fatty acids. Furthermore, they contain approximately 20% protein and a variety of minerals and vitamins [5]. Sesame is widely used in biofuel production and the cosmetics and medical industries, which makes it a significant crop for its economic importance [6,7].

In 2021, 6,354,477 tonnes of sesame were produced from 12,507,504 hectares worldwide to meet high global demand [8]. It has been crucial to enhance the productivity of sesame, due to its strong market demand. However, despite its economic significance, the yield of sesame is relatively low compared to other major oilseeds. This is because several complications have been identified in the mechanisation of planting, harvest and post-harvest processes, and agronomic practices. While significant advancements have been implemented in mechanising the production of other crops such as wheat, rice, rapeseed, and sunflower, sesame still lags in the adoption of mechanisation, relying heavily on manual processes [9]. The manual farming of sesame, including hand planting, harvesting, and post-harvest processing, is not economically feasible for large-scale farming [10]. Therefore, addressing these challenges is crucial for improving the efficiency and sustainability of sesame production.

The mechanisation of sesame farming is faced with several biological and technical challenges, particularly in the process of planting, although the crop is highly priced and in growing demand. The most important challenges include the morphological characteristics of sesame seeds, their small size, light weight, and irregular shape—which complicates singulation, measurement, and equal distribution of seeds by means of traditional planting equipment [11,12]. For sesame, conventional seed drills and pneumatic planners, which are effective on larger and more uniform seeds, result in poor seed spacing, poor seed flow, and high seed loss [13,14]. These can lead to poor field emergence rates, poor standing establishment, and ultimately reduced production potential, especially in precision-based agriculture systems [12].

The absence of equipment specifically designed for sesame exacerbates the issues. Most of the machinery currently available is either repurposed from other crop systems or not tailored to the unique seed characteristics and agronomic conditions of sesame [15]. This issue is further intensified by the morphological characteristics of sesame seeds that can easily be damaged under intense planting conditions or due to inconsistent soil cover [16,17]. Furthermore, the lack of comprehensive mechanisation practices has deterred producers from engaging in sesame production, especially due to the unavailability of workforce or labour costs rising beyond acceptable levels [18].

Moreover, low plant productivity, poor seed retention, and seed loss in harvesting are major constraints in achieving optimal sesame production. These issues further complicate the adaptation of mechanised practices [19]. Ishpekov [20] stated that the use of combine harvesters causes significant seed losses of up to 50% before and during the harvesting process. As stated by Day [21], these issues can be overcome by enhancing the uniform plant maturity. Also, he suggested that it is hard to determine by time; however, it is possible by uniform sowing and plant breeding. Breeding of sesame have been continued by researchers through breeding programmes to develop non-shattering varieties which can reduce the complications in mechanised adaptation by enhancing seed retention [22,23]. As shown in Figure 1, some non-shattering sesame varieties slightly open the tip of the capsule, which helps enhance the drying process and achieve the optimal moisture level for machine harvesting.

Uniform sowing can be achieved using a planting system which is effectively adapted to sesame’s unique characteristics. Historically, sesame seeds used to be planted using broadcast methods by hand or machines [24,25]. Barut [26] suggested that sowing seeds in rows is important to achieve better uniformity and conventional drilling, and broadcasting practices should be changed to precision technologies which can stabilise plant growth and enhance productivity.

Given the intricate and interconnected nature of these issues, the mechanisation of sesame planting requires systematic research. Recently, some advancements have been made through precision agriculture technologies such as Global Positioning System (GPS) guided planters, precision seed metering units, seed plate design optimisation and Discrete Element Method (DEM) simulation [27]. However, these technologies are still underutilised for sesame production [28], due to a lack of guidelines in standardised seed metering, optimal seed spacing, and planting depth for sesame. Therefore, this study is essential to critically evaluate the current mechanisation practices, determine the fundamental limitations in the equipment, and recommend solutions based on sesame seed characteristics and agronomic requirements for handling seeds. The paper explores how current techniques can be enhanced or redesigned with the aid of simulation tools like the DEM, with an emphasis on developing optimised planting technologies tailored to the unique requirements of sesame production. By doing this, it addresses a key query: how may planting technologies be modified and improved to meet the mechanical and agronomic requirements of sesame cultivation? By filling these knowledge and technology gaps, this study aims to drive the development of crop-specific solutions that increase planting efficiency, boost productivity, and advance sustainable sesame production.

2. Materials and Methods

This comprehensive systematic review was conducted by following the Preferred Reporting for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines [29] to ensure the transparency and replicability of this study, shown in Figure 2 and the Supplementary Materials.

2.1. Eligibility Criteria

This comprehensive review included peer-reviewed original research articles, technical notes, and review studies which focused on precision planting mechanisation for sesame. The inclusion criteria were:

• Studies that presented qualitative and/or quantitative data related to sesame agronomic parameters, sesame planting methods, planting equipment, precision planting practices, and the integration of simulation models (such as DEM).
• Articles published in the English language.
• Publications released from the year 2000 onwards, in order to identify the agronomic requirements.

Exclusion criteria were:

• Non-peer-reviewed materials such as theses and conference abstracts.
• Studies with a focus completely outside of this scope: studies focused completely on harvesting and post-harvest processing, without reference to plantings.
• Articles that were not available in full text.

2.2. Information Sources

A thorough literature search was performed across three major academic databases such as Scopus and Web of Science, with the final search completed 30 June 2025. Additionally, Google Scholar was used as supplementary search tool to enhance and identify other relevant studies. The included articles in the reference list were manually screened to ensure completeness. Furthermore, studies published in English and available in full text were included; however, there were no country-wise restrictions applied.

2.3. Search Strategy

The combination of controlled vocabulary and free-text keywords were used to conduct the literature search to ensure comprehensive coverage. The following key terms and their combinations were used across the databases: sesame, Sesamum indicum, oil seed, small seed, planting, precision agriculture, planter, seed drill, no-till, mechanisation, planter design, seed metering, vacuum, air-suction, pneumatic, DEM, DEM-CFD, simulation, agronomic, seed placement, singulation, multiples, skips, sustainable agriculture, emerging technologies, optimisation, germination, crop establishment, field trial, laboratory validation, simulation validation, and equipment calibration. Boolean operators (AND, OR) and truncation symbols were used to refine the literature search.

2.4. Study Selection

Following the elimination of duplicate records, the relevance of each study was assessed based on established eligibility criteria by evaluating the title and abstract. The studies that satisfied the inclusion criteria were obtained in full text and examined for final inclusion. The selection procedure is shown in the PRISMA flow diagram, which outlines the records that were identified, screened, excluded, and included.

2.5. Data Collection Process and Data Items

Data were obtained through a standardised data extraction table which was developed in Microsoft Excel. This was specifically developed to systematically obtain all relevant variables, including publication details, research methodology, equipment details (if used), agronomic details, and simulation parameters. The data extraction process was conducted precisely to ensure data accuracy and consistency according to the eligibility criteria.

Extracted data were organised into primary categories:

• Agronomic variables: Seed characteristics (e.g., seed size, shape, density, thousand seed weight, and moisture content), seed spacing, sowing depth, population rate, and seedling emergence.
• Technological variables: Planter type, seed metering mechanism, seed delivery mechanism, operational speed, seed plate design, vacuum pressure, and singulation rates.
• Simulation data: Particle shape, contact models, restitution and friction coefficients, integration methods for DEM and CFD, and model validation methods.

2.6. Risk of Bias Assessment

This review did not use any formal tools to assess the risk of bias due to the wide variety of study designs and the technical and engineering-oriented focus of the study. All studies were evaluated for relevance to the objectives, methodological transparency, and peer review status, to ensure a minimum level of quality.

Bias is still a concern when considering the minimal number of studies that specifically focused on sesame mechanisation and the likelihood of conflicting or negative findings. However, the risk was reduced using backward citation tracking, also known as screening reference lists, which determines any relevant studies that might not have been identified during the first round of the database search.

2.7. Synthesis Method

A quantitative meta-analysis is not feasible due to the wide variation in study design, techniques, and findings. Therefore, the results were analysed using a methodical narrative synthesis technique. As mentioned, the extracted data were categorised into main subject areas based on the objectives, such as agronomic parameters, planting technologies, and simulation-based optimisation methodologies.

The studies were evaluated by two reviewers independently, and any conflicts were resolved by discussion to enhance the consistency and reduce subjective interpretation. During the synthesis process, thematic categories were developed and iteratively refined to shape the review by enabling emerging patterns.

3. Results

The reviewed studies are categorised into three key areas: agronomic parameters, planting technologies, and simulation-based optimisation. The studies related to agronomic parameters examine how crop performance is affected by variables such as seed spacing, planting depth, and population rate. Planting technology-related studies focus on assessing the planter varieties and seedling techniques for stand uniformity. The studies focused on the integration of simulation in planting technology development used DEM and CFD to optimise the performance of the machine. When considered together, the studies provide a comprehensive overview of precision planting advances for sesame (

Table 1. Summary of selected studies on sesame planting and mechanisation.

Author(s)	Year	Title	Study Type	Key Findings	Geographic Focus
Studies related to agronomic parameters
Oloniruha et al. [30]	2021	Growth and Yield of Sesame as Influenced by Plant Population Density and Organo-Mineral Fertilizer Rates	Field experiment	Best yield (approximately 1.45 t/ha) achieved with 111,111 plants/ha. Wider spacing improved individual plant yield but reduced yield per hectare.	Nigeria
Tony [31]	2023	National Sesame Agronomy Trials: 2020 Field and Pot Trials	Field trials (report)	Mid-December sowing gave the highest yields (1.4–1.6 t/ha irrigated). Optimum plant density: 5–10 plants/m2. Emergence and yield were sensitive to sowing date and water availability. Seeding precision is not quantified.	Australia
Araujo et al. [32]	2018	Physical Properties of Sesame Seeds at Different Maturation Stages and Plant Positions	Field trials (report)	Thousand-seed weight of black: 2.71 g and cream: 2.48 g. Seeds from lower canopy larger than upper. Maximum seed mass at ~70% physiological maturity. Findings guide design of metering and sorting systems considering internal seed variability.	Australia
Day [19]	2000	The effect of plant growth regulator treatments on plant productivity and capsule dehiscence in sesame	Field experiment	Gibberellic acid increased capsule retention by 10%, but inconsistent yield benefits (5–7%). Increased plant height and delayed maturity. Not recommended under low-input systems.	New Zealand
Bennett and Conde [33]	2003	Northern Territory Sesame Variety and Agronomy Trial	Agronomy guide/report	Yield ranged from 0.5 to 1.0 t/ha depending on row spacing (30 cm). Mechanisation not tested, but results guided spacing and sowing date for Northern Territory conditions.	Australia
Elsayed et al. [34]	2023	Performance of a Cleaning Unit for Sesame Seeds Affecting Some Physical and Mechanical Properties	Experimental (machine)	Optimised parameters: sieve with 3 mm holes, 160 rpm oscillation, 3° inclination. Achieved 99.78% seed purity and 95.33% cleaning efficiency at a feed rate of 50 kg/h. Maintained seed integrity.	Egypt
Studies related to planting technologies
Topakcı et al. [13]	2011	Sesame Hill Dropping Performance of a Vacuum Seeder for Different Tillage Practices	Field experiment	Under reduced till: 78% emergence, 86% single-seed hills. Under no-till 62% emergence, 66% single-seed hills. Indicates 16–20% loss in seeding precision with no-till. Tillage improves planter performance significantly.	Turkey
Barut [26]	2008	Seed Coating and Tillage Effects on Sesame Stand Establishment and Planter Performance	Field experiment	Feed index improved with coating: ~81.3%. Miss rate decreased to 8.6% with coated vs. 11.1% uncoated. Emergence: uncoated seeds 4.5 days and coated 6.2 days. Tillage had negligible impact on feed rate but improved emergence slightly.	Turkey
Ali et al. [35]	2024	Effect of Planting Methods in Different Sesame Varieties during the Summer Season	Field experiment	Line sowing produced 1.58 t/ha yield, compared to 1.46 t/ha in broadcasting. Although broadcasting had a slightly better benefit–cost ratio (1.82 and 1.76), line sowing improved crop uniformity and emergence.	India
Shambhu & Thakur [36]	2019	Laboratory and Field Performance of Manual Seed Drill for Sowing Jute and Tiny Seeds	Prototype testing	Required draft: 75 N. Labour requirement: ~6 man-hours/ha. The manual seed drill achieved uniform spacing and better emergence than broadcasting. Shows potential for sesame where mechanised equipment is unavailable.	India
Duna & Pragna [37]	2017	Evaluation of Tractor-Drawn Seed Drill for Sesame	Field evaluation	Developed a 5-row planter with spacing accuracy ±2 cm. Emergence rate > 85%. Manual labour has reduced significantly. Suitable for broadacre sesame planting.	India
Barut & Çagırgan [11]	2006	Effect of Seed Coating on the Accuracy of Single-Seed Sowing of Sesame	Field experiment	Coated seeds: emergence around 62%, uncoated seeds: ~85%. Coated seeds had up to 3 days of delay in emergence. Demonstrate coating negatively affects field emergence.	Turkey
Bahnas [16]	2009	Requirements for Sesame Precision Planting Method	Experiment	Recommended settings: suction pressure −2.5 to −1.5 kPa, suction hole diameter 1.8–2.2 mm, 1 seed/hill, 30 cm row spacing. Based on sesame seed size (2.8 × 2.3 mm). Provides specific design criteria for pneumatic planters.	Egypt
Studies focusing on simulation integration
Sharaby, Doroshenko & Butovchenko [12]	2020	Simulation of Sesame Seeds Outflow in Oscillating Seed Metering Device Using DEM	Simulation (DEM)	DEM simulation of an oscillating hill drop planter showed each seed hole discharged 0–4 seeds (mean ≈ 2 seeds) per cycle, indicating very high variability in seed flow. The model tracks each seed’s trajectory and forces, enabling analysis of how kinematic (oscillation angle, speed) and geometric (hole size, drop height) changes affect output. These results can guide optimisation of planter parameters (e.g., reducing oscillation amplitude or adjusting exit-hole size) to improve singulation and stand uniformity. (Model was validated for sesame seed shape and could inform design of oscillating seeders.)	Egypt/Russia
Wang et al. [14]	2023	Design and Test of Air-Assisted Seed-Guiding Device of Precision Hill-Seeding Meter for Sesame	Design and testing (CFD/DEM + field)	Developed an air-guided seeder achieving 87% hill accuracy. Simulation and field trials validated optimal airflow and geometry settings, confirming improved precision hill-seeding for sesame.	China
Sharaby, Doroshenko & Butovchenko [38]	2022	Modelling and Verification of Sesame Seed Particles Using DEM	Simulation (DEM)	Validated multi-sphere DEM model for sesame seed geometry and flow. Optimal oscillation (20°), outlet (9 mm), and timing (0.022 s) achieved precise seed release (2.7 kg/ha). Supports simulation-guided design of metering units.	Egypt/Russia
Xu et al. [39]	2023	Design and Optimization of Seed-Metering Plate of Air-Suction Vegetable Seed-Metering Device	Simulation (DEM-CFD)	Hole spacing at 1.6× seed length improved single seed pick up from 39% to 75%. Rear air pulse enhanced seed retention. Though tested with cabbage, findings are transferable to sesame based on seed size and mechanics.	China
Other contextual studies
Jianbo et al. [40]	2014	Design of Integrated Control System for Precision Seed-Metering Device	Engineering design	Stepper-motor control achieved >98% plant spacing consistency across speed changes. Eliminated slippage issues found in mechanical ground-wheel drives. System adaptable to sesame planters.	China
Fisher et al. [41]	2011	Is Broadcasting Seed an Effective Cover Crop Planting Method?	Field study (cover crop)	Drilling improved uniformity and nitrogen uptake (30% more) compared to broadcasting. Broadcasting gave uneven establishment. Sesame is likely to respond similarly due to seed size.	USA
Brennan & Leap [42]	2014	Cover Crop Establishment on Bed-Formed Systems	Field study (cover crop)	Broadcast seeding without incorporation yielded <10% emergence. Drilling or incorporating seed led to 70–85% stand. Highlights importance of seed-to-soil contact, applicable to sesame planting	Hawaii
Li et al. [43]	2023	Experimenting and Optimizing Design Parameters for a Pneumatic Hill-Drop Rapeseed Metering Device	CFD Simulation + Experimental validation	CFD (Fluent) and experimental tests optimised suction hole design and operating settings for rapeseed planter. Best results at 30–70 rpm and −2.5 to −1.5 kPa, with >96% qualified holes and <3% empty drop rate.	China

).

3.1. Sesame Seed Characteristics and Their Impact on Mechanisation

The analysis of the characteristics of sesame seeds is an essential step in the design and optimisation of machinery for handling, cleaning, processing, and storage. Sesame seeds exhibit unique properties that vary depending on factors such as variety, environmental conditions, oil composition, and processing methods [17,44]. Seed characteristics have a significant influence on mechanisation, particularly in planting. Therefore, this section comprehensively analyses sesame seed characteristics that affect the mechanisation process.

Characteristics such as seed size, shape, weight, density, moisture content, and bulk density influence seed flow during planting, seed damage, and losses during post-harvest processes such as threshing and cleaning [32]. The physical properties in

Table 2. Physical properties of sesame seeds [34,45].

Physical Properties	Mean	Standard Deviation	Coefficient of Variance
Length (mm)	2.5	0.160	0.04
Width (mm)	1.65	0.130	0.02
Thickness (mm)	0.94	0.070	0.004
Volume (mm3)	2.03	0.450	0.19
Sphericity (%) *	62.84	1.980	4.75
Geometric diameter (mm)	1.57	0.089	0.011
Arithmetic diameter (mm)	1.29	0.087	0.010
Flat surface area (mm2)	3.24	0.840	0.718
Transverse surface area (mm2)	1.22	0.150	0.016
Mass of 1000 seeds (g)	10	-	-
Bulk density of seed (kg/m3)	640	-	-
Moisture content (%)	6–12	-	-

* Sphericity measures how close a seed’s shape is to a perfect sphere; geometric diameter refers to the mean diameter of seed, calculated from its three dimensions; arithmetic diameter is the mean of seed’s longest and shortest and intermediate diameters; flat surface area refers to the area of seed’s visible flat surface; and transverse surface area refers to the area of the seed’s surface perpendicular to its longest axis.

are based on data reported by Arafa [45] and Elsayed et al. [34], who examined a specific variety under controlled environmental conditions in Egypt. Although these figures provide a starting point for comprehending the mechanical and physical characteristics pertinent to mechanisation, variance is anticipated among various sesame cultivars and production settings. Consequently, caution should be taken when extrapolating these figures to all areas where sesame is grown.

Understanding the connection between the physical properties of seeds and machinery performance is also important to enhance efficiency.

Table 3. Impact of physical properties of sesame seeds on mechanisation of planting and harvesting.

Physical Properties	Impact on Planting	Impact on Harvesting and Post-Harvesting Processes
Length, Width, Thickness, Volume	These properties can affect seed placement during the metering of seeds while planting and the calibration of metering devices where the seed plant needs to be changed according to seed size [46]. Large seeds may require adjustments in seed depth depending on soil conditions.	Larger seeds are likely better suited for mechanised processing, while smaller seeds require gentle handling to minimise damage and loss [47].
Sphericity	Better uniformity or singulation could be achieved with higher sphericity [48].	Better seed flow can be achieved with higher sphericity and is also easy to separate seeds and trashes during the cleaning process [48,49].
Geometric diameter (Dg), Arithmetic diameter (Da)	Seed metering accuracy can be affected [50]. Large diameter seeds are easy to meter.	The probability of seed damage increases with larger Dg and Da [51]. Therefore, it is crucial to adjust the machine settings accordingly.
Flat surface area, Transverse surface area	Seed flow could be affected inside the seed metering unit due to friction [52].	An increase in flat surface area can enhance friction, thereby influencing the separation and seed flow inside the harvester [49,52].
Mass	Influences the planting depth control and the movement of seeds inside the seed metering unit [32].	Lightweight nature of the seed is susceptible to being blown away with trash [34].
Bulk Density	Higher density facilitates uniform seed distribution; it also results in obstructions in the seed hopper when a larger quantity of seeds is loaded inside.	Higher-density seeds minimise losses which facilitate enhanced separation and collection.
Moisture Content	Excessive moisture can lead to clogging in the seed meter unit, while insufficient moisture levels may result in seed damage.	Moist seeds can clog harvesting machinery and extend the processing time [49]. Excessive or insufficient moisture levels may complicate post-harvesting processes [53,54].

outlines the influence of each property on the adaptation of mechanisation and facilitates the understanding of necessary modifications in mechanised systems to obtain uniform, effective, and economical operations. The adaptation of mechanisation must take these parameters into account, as the machine settings depend on the physical properties of the seed chosen for planting and harvesting.

Following the analysis of the physical properties of sesame seeds and their implications for mechanisation, it is also essential to analyse the mechanical properties of sesame seeds, which are critical for enhancing the efficiency of the mechanisation process. Soyoye et al. [55] highlighted that mechanical properties such as hardness, elasticity, and friction can influence the seeds’ ability to withstand mechanical forces or impacts during planting, harvesting, and post-harvesting practices. Meanwhile, Yamin [56] stated that any damage caused to the seeds will affect their germination rates. The understanding of mechanical properties is crucial in this study to effectively customise mechanised systems. Arafa [45] and Jing et al. [57] conducted experiments to find some of the mechanical properties of sesame seeds (

Table 4. Mechanical properties of sesame seeds [38].

Mechanical Properties	Value
Friction angle
- Stainless steel	22°
- Metal surface	34°
- Wood surface	40°
Coefficient of friction
- Stainless steel	0.404
- Metal surface	0.675
- Wood surface	0.839
Angle of repose	25°–30°
Hardness	11.02 N/mm2
Modulus of elasticity	1.64–7.06 MPa
Maximum deformation under static compression test	0.23–1.05 mm
Crushing load (flat compression)	12.9 N
Crushing load (lateral compression)	Lower than flat, higher than vertical
Crushing load (vertical compression)	1.84 N (minimum)

).

The mechanical properties are linked to physical properties, which can be proved from the experimental results of Jing et al. [57]. Their study revealed that the elastic modulus, crushing loads, and hardness were significantly influenced by the moisture content of the seeds. Also, it shows that sesame seeds exhibit varying crushing loads based on the direction of the applied force, which reveals the least resistance during vertical compression. Such sensitivity to mechanical damage requires a special handling technique when adapting sesame to mechanisation. Furthermore, the mechanical strength of sesame seeds reduces with increasing moisture content, which highlights the need for precise timing in harvesting [44].

Various sesame varieties are used globally, and each has its distinctive characteristics, including growth habits, seed and plant characteristics, shatter resistance, and overall yield. The selection of seed varieties is critical for the adaptation of mechanisation, because Qureshi et al. [58] highlighted that mechanised harvesting can cause up to 50% of seed loss due to pod shattering. However, such seed losses can be reduced by selecting shatter-resistant variants [15,59,60].

There are different colour variations in sesame seeds, such as white, yellow, red, brown, grey, and black. Each has a different purpose of usage and regional preferences [61,62]. Seed colours do not have a direct effect on mechanisation; however, they can indirectly influence mechanised operations in specific conditions. The visual contrast of seed colours may assist operators or systems in identifying seed flow or placement during the planting process. An example of this is the Furrow Vision system developed by John Deere, which is a real-time seed placement monitoring system that helps operators make adjustments, if required, to enhance seed placement accuracy [63].

In conclusion, the size, shape, moisture content, and texture of the seed coat are all important aspects of sesame seeds’ mechanical and physical characteristics that influence whether mechanised systems are appropriate for handling and processing. However, the traits of the sesame plant itself also affect how well mechanisation works. The impact of plant characteristics such as height, branching habit, and capsule structure on the mechanisation of cultivation and harvesting is examined in the next section.

3.2. Seeding and Crop Establishment of Sesame

The period from seeding to establishment of sesame crops is a critical stage that lays the foundation for successful farming, including land preparation, selection of seeds, effective sowing, and ensuring better growth conditions for strong plant development. Rani et al. [64] stated that traditional farming practices often highlight the importance of natural pest control, crop rotation, and the preservation of soil fertility, which help to maintain soil health and biodiversity. However, the environment can be harmed due to excessive usage of modern techniques. Therefore, efficient crop planting requires a balance between traditional farming techniques and modern agricultural advancements to maximise yield and sustainability.

Land preparation is a key step in planting sesame which requires well-drained, sandy loam soils with a pH range between 5.5 and 8.0 [65]. Also, Langham et al. [66] suggest planting in a formed seed bed that helps maintain optimal moisture and improve the aeration and drainage of soil, as sesame is sensitive to waterlogging. The next step is seed selection, and Ahmed et al. [67] found that seed quality, in terms of ability to tolerate drought stress, directly impacts germination rates. Poor quality seeds may have lower germination rates and weaker seedlings. Additionally, Gebregergis et al. [68] stated that sesame should be stored at a 6% moisture content level or lower. In the tropical regions where temperatures can reach 33 °C and relative humidity hovers around 80%, seeds experience rapid deterioration, leading to reduced germination rates. Moreover, they state that different varieties of sesame seeds have changing storage capabilities, affecting their capability to germinate over time.

The seeding process is an important step for uniform and timely crop establishment to obtain maximised yield. Optimal row spacing and depth control is required to achieve better yield [69,70]. Uniform seed distribution is essential to achieve stronger and healthier crops by minimising excessive competition for nutrients, water, and sunlight. Furthermore, timely planting is also essential to ensure favourable environmental conditions supporting uniform crop development, leading to synchronised flowering and maturity and reducing the risk of seed loss in harvesting.

In addition, land preparation, seed selection and planting, irrigation, and nutrient management are also important. Mohamoud et al. [71] found that the average value of water requirement is 24.1 mm during germination and early growth stages in semi-humid sites. There are 17 essential elements, nitrogen (N), phosphorus (P), potassium (K), carbon (C), Hydrogen (H), oxygen (O), sulphur (S), calcium (Ca), magnesium (Mg), chlorine (Cl), boron (B), zinc (Zn), manganese (Mn), iron (Fe), copper (Cu), molybdenum (Mo), and nickel (Ni), that are essential for plant growth and development [72], and the use of fertilisers containing these elements can enhance the yield and quality of the capsules [73]. Moreover, pest infestations and weed competition can affect the early growth stages of seeds and good health of the crop. Therefore, appropriate pest and weed management practices are crucial to maintaining the health of the crop in optimal condition. Overall, balancing these factors in planting practice could enhance overall crop quality and productivity.

3.2.1. Agronomic Requirements of Mechanised Systems for Planting

The successful mechanisation of sesame planting depends on integrating agronomic practices with the crop’s specific establishment requirements. The small size of sesame seeds makes them highly sensitive to planting depth. Inappropriate placement could impact germination and emergence [70], resulting in asynchronous germination. This section focuses on the requirements of mechanisation practices to obtain a well-optimised planting system.

3.2.2. Germination Process

Germination is a process by which a seed transforms into a new plant. It initiates when the seed absorbs water, activating metabolism and breaking dormancy, allowing for the growth of the embryo. The seedling then forms roots and shoots until it matures [74]. Seeds remain dormant until the environmental conditions are favourable to germination [75]. Germination is a crucial phase in sesame production because it defines the initial success of crop establishment. Jyoti et al. [76] stated that sesame seeds thrive in consistently moist soil to break dormancy and initiate seed germination, but should not be waterlogged. Rathore et al. [77] found that excessive moisture conditions may promote fungal infections which significantly affect seed germination, especially if fungal spores are present in the soil or on the seed. Terefe et al. [28] mentioned that the optimal soil temperature for sesame seed germination is 25 °C to 27 °C. Potential delay in germination could occur below 20 °C, and if the temperature goes below 11 °C, the seed will not germinate at all. Therefore, optimum soil temperature is essential for germination. The seed varieties selection for planting also considers certain factors such as germination rates and biochemical compositions, in particular, the oil content and protein content of the seed could affect germination efficiency [56,78]. Furthermore, Shim et al. [79] determined that pre-sowing treatments such as priming and scarification enhance germination efficiency.

3.2.3. Planting Depth

The planting depth of seeds is a critical factor for improved emergence. Soureshjani et al. [80] stated that appropriate planting depth ensures optimal moisture content absorption and sufficient soil contact with seeds, for better germination. Research in northern Australia indicates that the optimal planting depth for better germination ranges between 10 mm and 25 mm [81]. Additionally, Crawford and Williams [82] highlighted that seeds planted too near the soil surface can be exposed to variable soil moisture conditions, particularly rapidly drying soil in warm conditions, leading to desiccation of the seed. Additionally, these seeds are more vulnerable to predation. Seeds planted too deeply may not emerge, resulting in poor or failed germination based on the soil texture. Thus, maintaining planting depth at the optimal range is essential to achieve synchronised seedling emergence. To support this argument, Ahmed et al. [83] highlight that better soil-to-seed contact at optimal depth facilitates moisture absorption into the seed, which is essential for activating the metabolic process which drives germination. Precise planting depth could be achieved through mechanisation and could ensure the uniform placement of seeds, leading to synchronised seedling emergence and even competition between plants for nutrients [84].

3.2.4. Plant Population

Plant population is a critical factor in sesame cultivation, because it significantly influences crop establishment, resource utilisation, and overall yield. According to Oloniruha et al. [30], the competition between plants for water, sunlight, and nutrients could be reduced by optimising the spacing, which helps to grow healthier plants and better seed production. Based on the report produced by Rixon et al. [81], the recommended spacing between rows typically ranges from 25 cm to 100 cm, depending on the farming system. Moreover, Roy [85] specified that maintaining intra-row spacing between 5 cm and 10 cm could maximise overall yield by optimising land use while reducing the competition between plants. Excessive competition could affect plant strength, plant health, number of capsules per plant, and seed count per capsules [85]. Conversely, lower plant densities could result in increased weed growth, insufficient use of land, and land drying due to direct sunlight exposure, which ultimately affect the overall yield [86]. Thus, optimised plant population is essential for boosting sesame productivity. As per the study by Bennett et al. [33], approximately 250,000–300,000 plants/ha is recommended for sesame, which equates to around 3–3.5 kg/ha.

3.3. Adaptation of Mechanised Planting Practices in Sesame Cultivation

Appropriate selection of planting equipment is critical for ensuring optimised plant population, uniform seed placement, and maximised utilisation of resources. Different planting technologies have been evolved for different types of crops; however, each of them has their distinct advantages and disadvantages when it comes to sesame production.

3.3.1. Broadcast Planting

Broadcast planters can cover wider areas quickly; therefore, they are commonly used in large-scale cultivation [41]. Broadcast planting can distribute the seeds randomly over the field without controlling depth and spacing (Figure 3a). Brennan and Leap [42] suggested that broadcast planting is a low-cost option with minimal equipment. However, drawbacks such as high seed waste, inefficiency in plant population control, and asynchronous germination make it less suitable for sesame cultivation. Moreover, the absence of depth control affects soil-to-seed contact, which reduces the germination rate and overall yield. This has been proved by Ali et al. [35] through a field experiment, and it is suggested that broadcasting is not recommended for sesame planting.

3.3.2. Drill Planters

Drill planters can place the seeds in continuous rows at a controlled depth and spacing (Figure 3b), which provides enhanced seed placement and better control on plant population and density compared to broadcasting [42]. Drill planters are commonly used in medium-scale sesame production, where resource efficiency and field management are critical. Duna and Pragna [37] evaluated the seed drill method for sesame and determined that even though it enhanced the mechanisation process, the drill method causes significant seed damage, seed clogging, and inconsistencies in depth control, which leads to asynchronous emergence and lower yield. Moreover, they suggested that modifications are required in seed metering and furrow opening systems, particularly for sesame seeding. Figure 4 shows a 50-foot seed drill which is used for seeding in large scale farming.

3.3.3. Precision Planters

To address these issues, precision planters offer a better solution in terms of seed placement accuracy, depth control, and uniform spacing. Precision planters are advanced agricultural implements designed for accurate and efficient seed placement. They incorporate GPS guidance systems for precise navigation and individual row unit controls to ensure uniform spacing [88]. Precision planters use mechanical or air-based seed metering mechanisms to ensure singulation, delivering one seed at a time while maintaining uniform spacing. Singulation significantly reduces seed wastage and provides enhanced field establishment [14]. Precision planters provide flexibility to adjust planting parameters based on field variability and environmental conditions, which further enhances their compatibility with various varieties of seeds. Additionally, adjustable furrow opening mechanisms with the invention of real-time depth sensors (furrow vision by John Deere) ensure the precise placement of seeds [63,89]. Figure 5 illustrates a vacuum-assist precision planter.

Precision planters could be a promising solution to address the issues with manual and traditional mechanised sesame seed planting. Bahnas [16] recommended using precision planters for sesame for better seed placement, consistent depth control, and flexibility to adjust planting parameters according to field variability and environmental conditions, which helps to achieve uniform emergence. Furthermore, precision planting helps achieve uniformity across the field, which significantly enhances weed suppression [91]. The study conducted by Weiner [92] demonstrated that a uniform seeding pattern resulted in higher yields in 76% of trials, and fewer weeds in 73% of trials. In addition, crop competitiveness was increased by consistent planting patterns, which suppressed weeds by 15% more than random patterns and 8% more than row planting, particularly when weeds appeared alongside crops.

Though it is a suitable method for sesame seed planting, some limitations persist that could affect the effectiveness of singulation, such as seed size, sphericity, surface texture, seed density, and moisture [26]. Precision planters are not only made for sesame. Therefore, these issues should be addressed, and optimisation is crucial to achieve better planting practices.

In summary, precision planters have great potential to improve planting uniformity, crop emergence, and seed efficiency. In contrast to conventional broadcasting techniques (5–6 kg/ha), vacuum-based precision planters can achieve up to 90% seed singulation and germination with far lower seed rates (2.5–3 kg/ha), as the comparative

Table 5. Comparison of sesame seeding equipment types.

Planter Type	Configuration	Metering Mechanism	Seed Rate (kg/ha)	Farmer Adaptability	Performance	Emergence Rate (%)	Limitations	Reference
Manual Broadcasting	Broadcast/dibble	Human	5–6	Easily adopted, no investment needed. Widely used by smallholders in India and Africa.	Evenness highly variable (around 80–90%), highly reliant on skill and consistency	30–50	Labour intensive, time consuming, poor uniformity in placement and excessive seed usage.	[35,42]
Single-row drop seeder	Mechanical planter	Belt/roller	4–5	Low cost and simple to operate; some training needed. Suitable for small plots.	Emergence rate around 80–90%, skips around 5–10%	50–65	Limited to 1–2 rows, requires coated seed to achieve better results.	[26,36]
Broadcast drill	12+ rows, air sowing	Blower plans/shaker	4–5	Requires tractor or power-tiller; more suited to small-scale commercial farms.	Low singulation accuracy and poor uniformity	60–70	Excessive seed usage, requires smooth seed bed.	[35,42,93]
Multi-row air drill	4–12 rows, air seeder	Seed plate, Air	3–4	Effective in medium-to-large farms. May be available via cooperatives.	Variation in seed placement around 15–30%	70–85	Better performance in tilled soil, tubes are prone to blockage without air-guides and excessive power consumption.	[13,36]
Vacuum precision planter	4–12+ rows	Vacuum-disc	2.5–3	High initial cost and technical complexity limit use by smallholders. Most viable in commercial sesame operations.	Seed singulation around 90%, 50% higher planting speed and lower seed damage rate (with calibration) than conventional drills	<90	Requires calibration, better performance with good-quality, cleaned seed. Blockage in seed disc holes affects singulation.	[39,40,94,95]

shows.

This reduction in seed wastage directly contributes to lower input costs over time. However, because of the high capital expenditures and the requirement for expert calibration, adoption is still restricted [96]. For smallholder farmers, these obstacles frequently render mechanised sowing economically impractical [97]. The majority of smallholder farmers may not be able to afford or operate precision planters independently, but programmes such as farmer cooperatives, subsidies, and/or shared machinery can make them a practical and effective alternative [98].

3.4. State of the Art in the Precision Agriculture Mechanisation of Sesame and Other Small Seed Crops

Table 6. Comprehensive summary of studies on mechanised planting advancements in small-seeded crops.

Reference	Method	Motivation	Findings and Recommendations
[13]	Field experiment of a modified vacuum hill drop planter. Sesame was sown with no till and reduced and conventional tillage.	Enhance the performance of a vacuum seed drill under reduced or no till condition	No-till condition provides poor hill-spacing and low emergence, while conventional tillage provides good spacing with higher emergence. For no-till, the design of opener and furrow-closer must be enhanced to achieve optimal depth and consistency. Also, some seed blockage in tubes encountered.
[12]	Discrete Element Method to model and analyse sesame seed dynamics in an oscillating metering device.	To forecast and enhance the consistency of seed discharge in oscillating seed metering systems	The simulation model examined seed outflow from an oscillating mechanism, considering seed morphology and interactions. Results indicate that optimising device parameters may improve seed distribution uniformity.
[38]	Employed Discrete Element Method (EDEM) simulations to model non-uniform sesame seed particles, facilitating the design of seed metering machinery.	To create a model and simulate sesame seed particles for the purpose of equipment design	The ideal settings for the oscillating seed metering device were determined to be a hole clearance of 9 mm, an angle of 20°, and an opening duration of 0.022 s, resulting in a sesame seed application rate of 2.7 kg/ha. While these parameters enhanced planting efficiency and seedling emergence, additional research is required to optimise them for varying conditions and sesame cultivars.
[14]	Design and optimisation of an air-assisted seed-guiding model for centralised hill drop planter. CFD-DEM simulation was used to optimise the design.	Optimise the design of the model including guide depth, tube diameter, and air flow speed to reduce the seed block in the metering tube	Optimised the design (guide depth = 2.6 mm and tube diameter = 19 mm and air speed = 6.3 m/s). This study suggested using the parameter values for optimal metering performance. However, there will be 2 ± 1 seeds per hill, which might negatively impact the overall yield.
[31]	An assessment was conducted on sowing time and density in four distinct environments in northern Australia, examining various sowing dates and densities for both white sesame (Equinom) and black sesame (AgriVentis) varieties	To assess the impact of planting time and population density on sesame production in northern Australia	Sowing in mid-December at moderate densities, resulting in 1.5 tonnes per hectare, was identified as the most effective method. Effective weed control, including both pre-plant and in-crop management, is crucial for maximising yields.
[43]	CFD simulation and bench experiments on pneumatic (air suction) hill drop seed meter. Fluent used to model airflow with different hole shapes and diameters.	Enhance the high-density precision planting of small rapeseeds by optimising the design of air suction seed meter.	Achieved over 96% of single drop and less than 3% of misses. However, smaller seeds than rapeseed, such as sesame, may encounter blockage.
[99]	In a controlled laboratory experiment, a seed metering system was evaluated using seeds of various sizes. The experimental study did not incorporate sesame seeds; however, the results, especially regarding seed damage and the rate of seed cell filling, can be relevant to sesame seeds by making comparisons with the mustard seeds utilised in the research.	The physical characteristics of the seeds were measured and analysed, focusing on key outcomes such as seed-cell filling rate, seed damage extent, and germination rate.	The seed damage significantly increases with the peripheral velocity of the seed meter, which affects the germination of the seed. For mustard seed, seed-cell filling rate reduced and damage increased with increasing peripheral velocity. Germination rate also decreased after the seeds passed through the seed metering device when operated at high speed.

summarises peer-reviewed studies (2000–2025) on the advancement of precision planting technologies for small-seeded crops. This gives a detailed analysis of the methods, motivation, key findings, and recommendations of each study.

These advancements in precision planting of small-seeded crops like sesame, canola, rapeseeds, and vegetable seeds have aimed at enhancing seed placement consistency and emergence rate. Precision vacuum planters have performed with high singulation rates and better seed placement accuracy when they are specifically tuned for the crops. Also, this analysis emphasises the critical function of simulation in enhancing precision planting. Specifically, DEM facilitates the virtual evaluation of factors such as seed plate design, vacuum pressure, and seed metering design, which significantly reduces both development time and expenses. Finally, this analysis suggests the need for crop-specific planter adjustments to ensure better establishment and yield.

3.5. Functional Requirements of Precision Planting Equipment in Sesame Planting

Typical planters are designed to perform particular functions such as furrow opening, seed metering, seed delivery into the furrow, covering the furrow, and pressing the seed bed [100]. However, Shaner and Beckie [101] mentioned that some advanced planters could perform other functions, including weed control and fertiliser supply. Figure 6 illustrates the basic functions performed by soil-interacting components of a typical precision planter. The functional and operational requirements of each component are described in

Table 7. Functional and operational requirements of components.

Components	Functional Requirements	Operational Requirements
Soil Cutting Device	Cut and loosen soil to facilitate seed placement	Should operate efficiently in varying soil conditions with minimal clogging
Row Preparation	Prepare a suitable seedbed with optimal tilth and moisture retention	Must break clod, remove weeds, and retain moisture for uniform emergence
Furrow Opening Device	Create a furrow of the right depth and width for seed placement	Should be adjustable for different crops and soil types
Seed Firming Device	Ensure proper seed-to-soil contact to enhance germination	Should apply uniform pressure to prevent seed displacement
Row-Specific Seedbed Firming Devices	Firm the soil in the seed row to maintain consistent seed depth	Should exert controlled pressure along the seed row for uniform emergence
Non-Row-Specific Seedbed Firming Devices	Level the entire seedbed to provide uniform field conditions	Should smoothen the surface to avoid water stagnation and erosion

.

Seed metering units regulate the flow of seeds from the seed hopper to the seed tubes or delivery system [103]. The seed metering systems can be classified as either precision or mass flow system based on the working principle. Precision seed metering systems typically handle low seed densities (range 10–150 seeds/m²) and are specifically used to plant one seed at a time. Conversely, mass flow seed metering systems handle higher seed densities (ranging 150–1500 seeds/m²) and do not meter individual seeds; rather they attempt to meter a consistent amount or volume of seed per unit of time [100]. Based on the planting requirements of sesame seeds, precision seed metering would be a suitable option to maintain space, depth, and singulation [12].

Different types of precision metering units, such as plate, brush, vacuum, air, or finger pick-up, may be used depending on the planter’s design and specifications [88].

Table 8. Types of seed metering units [88,104].

Seed Metering Types	Metering System	Working Principle
Finger pick-up	Mass metering *	Spring-loaded fingers in the seed hopper pick up and release seeds onto a stationary disc. Seeds then drop onto a placement belt for transport to the seed tube.
Air pressure	Mass metering	Seeds are securely held within cells located around the circumference of a rotating disc by positive pressure from a blower. As the seeds approach the seed tube, a gentle brush cuts off the airflow, causing the seeds to fall into the seed tube.
Vacuum	Precision metering	Seeds are held in cells on a rotating disc using negative pressure. They are then released into the seed tube with the assistance of a cutoff wiper, which stops the vacuum once the seed reaches the outlet.
Plate seed meter	Precision metering	Plate has multiple holes or cells. During the rotation of the plate, the seed cells will pick the seeds from the seed chamber. Seed will be delivered to the seed tube and travelled downwards by gravity.
Brush seed meter	Precision metering	Single seeds in each grove will be held by the brush and excess seeds will be removed to the seed chamber and picked seed will be delivered into seed tube.

* Mass metering typically uses a system to distribute seeds according to their volume or weight, which can differ with seed size, and it cannot meter individual seeds. Precision metering refers to systems designed to plant seeds with high accuracy, ensuring the right quantity is sown at the correct depth and spacing.

describes the working principles of seed metering types, while Figure 7 shows the 3D models of these meters.

Sharaby et al. [104] recommended pneumatic seed metering systems as a promising method for small or lightweight seeds like sesame. They highlighted that mechanical seed meters could damage the seed and would supply an inconsistent distribution of seeds, whereas pneumatic seed meters handle seeds with air pressure to ensure gentle contact and precise placement.

Figure 8 illustrates the exploded view of the vacuum seed metering system of precision planters. The brass agitator ensures appropriate movement of seeds towards the seed plate holes. The seed singulator/scraper plays a critical role in eliminating excess seeds while ensuring that only a single seed passes through the point. The seed wiper helps to release the seed into the seed tube for the precise placement into the soil.

Khan et al. [105] mentioned that conventional precision planters commonly rely on a ground wheel and chain and sprocket system to drive seed meters. This setup is prone to planting inaccuracies, especially at higher speeds, due to ground wheel slippage and chain vibration. To tackle these challenges, a new power transmission approach has emerged [106]. This method has replaced the traditional mechanical driving system with an electrical motor to power the seed meters, resulting in increased planting accuracy.

3.6. Integration of Simulation Techniques in Precision Agriculture

In agricultural engineering, the Discrete Element Method (DEM) is one of the most common numerical tools for simulating particle interactions. It is very suitable for analysis on seed handling, seed flow, crop and machine interactions, and crop processing, as it enables the prediction and study of mechanical behaviours, including separation, collision, and flow of granular materials. From the studies of Xing et al. [107] and Ding et al. [108], it is observed that the ability of DEM to describe airflow and particle-fluid interaction is further improved by its integration with Computational Fluid Dynamics (CFD), which is especially useful in machinery such as combine harvesters and pneumatic planters.

Recent research supports DEM’s feasibility for sesame seed modelling and its potential to enhance equipment performance throughout the planting and harvesting processes [108,109]. DEM offers promising applications in both precision planting and harvesting for sesame mechanisation. Accurate simulation and optimisation of machinery are essential due to sesame’s small seed size and fragility during processing, but there are few direct studies on sesame [12,38], so methods from similar crops such as rice and maize must be adapted [39,107,110].

According to the studies [12,38], a multi-sphere approach can be used to represent sesame seeds during planting. This approach properly replicates particle behaviour based on physical parameters, including density and repose angles. These studies used DEM to model sesame seed particles, using a multi-sphere technique with 28 spheres for accuracy, which was validated by piling experiments and oscillating seed meter simulations (Figure 9). Pneumatic planter DEM-CFD simulations are based on this model. To enhance seeding accuracy, vegetable seed metering systems were used with DEM-CFD, employing EDEM-Fluent using the Lagrangian approach and optimising airflow and mechanical components (Figure 10) [39]. By modifying variables like suction pressure and seed spoon geometry, these techniques may be modified for sesame, guaranteeing precise placement and minimal seed loss.

In general, combining DEM and CFD modelling offers an effective approach to assist with the adaptation and improvement of mechanised sesame planting and harvesting. This technology may enhance machinery efficiency, precision in seed handling, and recovery by utilising lessons from comparable crops and customising simulations to sesame’s specific characteristics. This can ultimately lead to more sustainable and scalable sesame production.

4. Integration of Findings and Recommendations

There are several challenges in the mechanisation of planting for sesame seed due to its unique characteristics. This study integrates findings from simulation models, field performance data, economic evaluations, and farmers experiences to develop a practical and scalable precision planting framework for sesame.

The studies that have been reviewed indicate that technically vacuum/pneumatic metering systems can perform better when the equipment is set at optimal settings for specific crop. However, the performance observed in the field is still affected by field conditions and other components in the planting system, such as the tillage system, furrow closing wheels and pressure wheels [111]. This underscores the necessity of validation with real-world conditions.

The integration of simulation tools in the study, especially DEM, provides a significant platform for evaluating the machine parameters with seed characteristics under virtual tests prior to field deployments [12,39,112]. DEM enables researchers to evaluate seed flow, singulation performance, and interactions between seed particles and machine parts when varying the equipment parameters/controls. Furthermore, Zhao et al. [113] highlight that DEM helps reduce development time and cost.

From an economic perspective, precision planters offer significant long-term advantages despite their high initial cost, ranging from approximately USD 3,500 to over USD 70,000, depending on factors such as number of rows, drive type (electric or mechanical), metering system, and optional features like GPS integration [95,114]. Precise singulation and spacing can reduce seed usage by 40–50%, improve field emergence rates, and increase yield potential compared to other planting practices. In contrast, traditional methods such as manual broadcasting or simple drop planters, while initially more affordable, often result in poor seed distribution, increased seed rates, and lower plant stand uniformity, frequently necessitating replanting and more intensive weeding [115]. As mentioned, precision planting significantly enhances weed suppression, potentially reducing weed management costs, which account for over 50% of total sesame production expenses [97]. Therefore, increased output and improved input efficiency make investing in precision equipment financially viable for medium- to large-scale farms.

Despite these advantages, several challenges hinder the adoption of precision sowing methods. These include the high cost of machinery, limited access to professional assistance and training, the incompatibility of machines with various field conditions, and the scarcity of precision equipment designed for small-scale farms [93,116]. A combination of technical solutions, such as the creation of more affordable or modular planter systems and more easily available training programmes, and policy-level interventions, including subsidies and equipment rental services, would be needed to address these issues [117].

To fill the gap between field deployment and simulated performance, this research introduces an experimental framework (

Table 9. Machine parameters of vacuum-based precision planting for sesame.

Parameter	Units	Levels (min, max)	Rationale
Ground speed	km/h	4, 8	Minimal speeds (around 4 km/h) will increase the singulation of smaller seeds and will minimise skipping and bouncing. For the most precise planting, Monosem advises a speed of 5–7 km/h; in light stands, this speed could reach up to 8–10 km/h. Increased speed could have the danger of producing doubles or missing seeds [118].
Vacuum Pressure	kPa	3.7, 5.0	In order to prevent damage and ensure correct pickup, Monosem advises using 15–20 inches of H2O (equivalent to 3.7-5.0 kPa) vacuum for smaller seeds; higher vacuum or speed could split seeds or clog the meter [66,118].
Seed plate hole Diameter	mm	0.8, 1	Depending on seed size, a plate needs to be selected that causes the least damage and breakage to the seed as possible, while ensuring that only one seed is placed on each hole for best singulation when planting. Other considerations for plate selection include hole blockage.
Scraper	Indicator	−1, +1	A setting of −1 to +1 is recommended for smaller seeds, such as canola, to balance missing and doubles [118]. The settings can go up to −5 (fully engaged with seed hole) and +5 (fully disengaged with seed hole).
Population	Seeds	250,000, 350,000	Aim for about 300,000 plants per hectare for weed control and maximum output. Yield could decrease below 250,000; lodging and stress could result in above 350,000. To meet the objective, use seed rate of about 3–3.5 kg/ha [33,81,119].

) that recommends an initial set of operating parameters of a vacuum-based precision seed metering unit for sesame seed planting, such as planter speed, vacuum pressure, seed plate hole diameter, scraper/simulator angle and population. These parameters can be tested through the combination of DEM simulation and field trials to determine an optimised configuration that balances precision, efficiency, and adaptability for field conditions.

These parameters are recommended for the vacuum-based seed metering unit, which is shown in Table 9. In order to provide the machine parameter values, the Monosem NG Plus 4 model was selected [120].

In the future, the integration of field validation, adaptive machine controls, and simulation-guided design will create a potent methodology for sesame, as well as other small-seeded crops like flax, kalonji, and rapeseed [121,122]. Precision sowing systems designed for various field conditions are likely to become the new norm as simulation tools become more widely available and planter technology advances. By providing a proven, technically robust foundation for optimal sesame planting, this study contributes to that progression.

5. Strengths and Limitations

The article provides a targeted overview of precision planting mechanisation for sesame, a crop with agronomic difficulties that are frequently disregarded in more general mechanisation research. Its practical significance for crop-specific equipment adaptation or design, thorough examination of agronomic and technological factors, and integration of simulation and experimental results, are its main advantages.

However, the review is limited by the relatively small number of high-quality studies on sesame, language and access restrictions, and heterogeneity in study methods and outcomes. Furthermore, only planting is included; harvesting and post-harvest management are not included in this scope.

6. Conclusions

Mechanised precision planting for sesame and other small-seeded crops requires a nuanced understanding of seed characteristics, equipment capabilities, and field interactions. While significant advancements have been made in vacuum and pneumatic metering technologies, achieving consistent field emergence and uniform spacing remains a challenge due to complex seed–soil–machine dynamics.

This review has outlined the current state of the art in planting mechanisation, including both equipment design and post-planting considerations, as well as the emerging role of DEM-based simulation in optimising planting systems. By combining simulation-driven design with field validation, the proposed experimental approach aims to identify an optimal parameter range for sesame seeding that can serve both research and practical mechanisation efforts.

Future research should continue integrating simulation and sensor-driven feedback systems to refine precision planting technologies, especially for crops with delicate agronomic and mechanical requirements like sesame.