Mechanization and Intelligent Technologies for Ginger Harvesting: Evolution, Frontiers, and Prospects

Abstract

Driven by agricultural labor shortages and rising quality requirements, ginger harvesting increasingly demands high-throughput, low-damage operations and a reliable supply chain. This review summarizes harvesting modes and harvester types used in ginger production, with emphasis on critical process modules: digging and lifting, soil disintegration and cleaning, vine cutting and anti-tangling, gentle conveying, and collection. We compare major technical routes in terms of field capacity, control of soil and foreign materials, damage mitigation, and reliability under continuous operation, and identify the conditions under which each route performs best. Drawing on advances in harvesting systems for other root and bulb crops, we outline transferable approaches for intelligent sensing, precision control, and system-level integration. We then propose an online monitoring and closed-loop regulation framework for strongly coupled conditions, such as heavy clay soils, plastic-mulch residues, and vine interference. Key bottlenecks include limited cross-regional adaptability, persistent trade-offs between low damage and high throughput, cost constraints on intelligent functions, and the lack of shared datasets and standardized evaluation protocols. Future progress should be anchored in integrated equipment sets and supporting operating specifications, guided by multi-source sensing-based quality indicators and interpretable control strategy libraries, to reduce harvest losses, stabilize marketable quality, improve operational efficiency, and enable scalable adoption.

1. Introduction

Ginger (Zingiber officinale Roscoe) is an important economic crop worldwide with both medicinal and culinary uses, serving as a seasoning, for dietary therapy, medicinal applications, and as a raw material for processing. Its product range includes fresh ginger, dried ginger, ginger powder, essential oil, and functional foods, offering high added value and steady market demand [1,2,3,4]. International production is mainly concentrated in Asia and Africa, with global output maintained at a high level over the long term; China is one of the major producers and exporters, with production characterized by the clustering of advantageous regions [5,6,7,8]. Based on available statistics, China’s ginger production in 2022 was on the order of 10⁶ t, supported by cultivated area on the order of 10⁵ ha; major production is clustered in provinces such as Shandong, and the domestic value chain is characterized by large-scale cultivation, centralized processing, and region-based distribution hubs [9,10]. In major producing areas, film-covered high-ridge cultivation is widely adopted. Combined with factors such as high continuous cropping intensity and increasingly heavy clay soils, fieldwork conditions are marked by significant ridge variations, strong soil adhesion, and concentrated harvest windows. The harvesting stage has a decisive impact on ensuring stable production and supply, as well as reducing costs and improving efficiency [11]. The continued outflow of rural labor and peak seasonal labor demand during harvest further drives up harvesting costs and complicates scheduling, intensifying the urgent need for efficient, low-loss harvesting equipment.

Corresponding to the high yield value is the high labor input and high-risk characteristics in the harvesting stage; ginger has numerous root branches, irregular shapes, dense root systems, and thin epidermis with weak resistance to abrasion. Manual hoeing and digging require high labor intensity, have relatively low efficiency, and lack consistency in quality. Under conditions of sticky wet soil or high moisture content after rain, the proportion of adhering soil and debris increases, making separation and cleaning more difficult. Mechanical operations more easily cause damage such as peeling, breakage, and abrasion, which further reduce commercial value and storability, and amplify the risk of post-harvest rot [12,13]. From an engineering mechanism perspective, the ginger harvesting process requires a systemic balance among low-resistance digging, effective soil breaking, efficient separation, flexible conveying, and low damage control. Simply increasing operating speed or vibration intensity often leads to higher damage rates and impurity content. Therefore, parameterized design and optimization should be carried out based on full-process workflow coordination and key component mechanism constraints [14,15,16].

Over the past two decades, China’s ginger harvesting equipment has undergone an overall evolution from single excavation to composite operations, and then to integrated harvesting. Early machines primarily featured plow-shovel or vibrating excavation combined with simple conveying mechanisms, with working width and depth limitations and inadequate adaptability to ridge shapes and soil conditions. Subsequently, continuous iterations were carried out around key components such as shovel-sieve combinations, soil shaking and screening, cutting of seedlings, and soil cleaning, gradually forming multiple types of machines, including trailed, mounted, and crawler self-propelled units. In demonstration zones, integrated applications of excavation, soil cleaning, vine/seedling handling, and bin collection and transportation were promoted [13,14,15]. Related studies show that through theoretical analysis, bench tests, and field comparisons of excavation and soil cleaning devices, it is possible to effectively reduce low damage injury rates and soil content under the premise of balancing resistance control with cleaning performance, thereby providing quantifiable parameter references for low damage harvesting [16]. Crawler self-propelled platforms and complete-machine process integration help improve passability and operational continuity, better meeting the needs of large-scale farming and specialized service operations [15]. Internationally, dedicated ginger harvesting equipment remains primarily focused on adaptation and modification for small-scale applications, but the mature technical systems developed for root crops in low-damage excavation, fine cleaning, and reliable conveying offer significant reference value for optimizing the structure and improving the reliability of ginger equipment [13].

With the rapid diffusion of digitization and intelligent technologies in agricultural machinery, ginger harvesting is moving beyond basic mechanization toward quality-controllable operations. Online state monitoring and multi-source sensing enable adaptive regulation of key process parameters, including digging depth, screening intensity, and conveying posture. To address the strong coupling in the root-soil-machine system, discrete element modeling and bench experiments have been used to quantify parameter sensitivities and the mechanisms underlying draft resistance, thereby providing a mechanistic basis for low-resistance excavation and low-damage handling [13,17]. From a commercialization perspective, however, ginger harvesters still face pronounced regional heterogeneity in ridge geometry, strong soil adhesion, large fluctuations in impurity load, and persistent trade-offs between low damage and high efficiency, under tight cost constraints. Continued advances are needed in modular process chains, key-component reliability, standardized evaluation of operational quality, and closed-loop control [13,15,16]. Accordingly, this review synthesizes agronomic and industrial constraints, summarizes the evolution of equipment and the mechanisms of critical modules, and outlines intelligence-enabled pathways for engineering deployment and cross-regional adaptation.

2. Biological Basis and Agronomic Requirements of Ginger Harvesting

The harvest target of ginger is underground rhizomes, which are highly heterogeneous in morphology, have obvious branch clusters, a thin epidermis with low-damage tolerance, and are entangled with fibrous roots and adhered soil, together forming a typical root-soil-vine coupling system. This determines that the harvesting process must achieve a systemic trade-off among excavation resistance control, low-damage contact, root-soil separation, and vine handling coordination; any single-point enhancement may induce an increase in soil content or damage rate and reduce continuous operation stability [17,18,19]. Existing surveys and studies show that in China, the planting area and yield of ginger remain at a high level; in 2022, China’s ginger planting area was about 3.6 × 10⁴ hm² with a yield of about 1.2 × 10⁷ t. The world’s main ginger production areas are concentrated in China and other Asian countries, with recent total global production of about 15 × 10⁷ t. The overlap of industry scale expansion and constraints on labor factors has significantly increased the mechanization demand in the harvesting stage [20]. In engineering practice, agronomic factors such as ginger burial depth, ridge shape, moisture content, and residual mulch film directly affect the stability of excavation depth, soil-cleaning and separation load, and anti-tangling reliability. Localized measurement of key agronomic parameters should be taken as a prerequisite for machine adaptation and test evaluation, and core quality indicators such as harvest rate, damage rate, and omission rate should be simultaneously constrained in the index system, with relevant thresholds referring to industry standards. As shown in

Table 1. Key agronomic parameters for ginger harvest and mechanical adaptation requirements.

Parameters or Indicators	Typical Range or Representation (Reporting Format)	Impact on Harvest	Key points for Mechanical Adaptation	Measurement and Recording Recommendations
Rhizome planting depth	Site-dependent; report mean ± SD and P10–P90 (mm)	Determines excavation depth setting and risk of missed harvest/cutting injury	Depth-limiting and depth-adjustment mechanisms; consider closed-loop depth control when variability is high	Protocol: dig transverse profiles across beds; measure vertical distance from soil surface to rhizome center/upper surface. Sampling: ≥30 points/field. Stats: mean ± SD; P10–P90; also report CV.
Ridge geometry & row spacing (ridge height, bed width, row spacing)	Site-dependent; report mean ± SD and CV (mm)	Affects chassis stability, passability, row-following accuracy, and depth stability	Adjustable track/row-spacing; adequate ground clearance; row guidance/auto-steering support	Protocol: measure ridge height and bed width with ruler/laser; row spacing with tape/GNSS. Sampling: ≥30 ridges/field. Stats: mean ± SD; CV; record ridge uniformity class.
Soil moisture content (working layer)	Site-dependent; report mean ± SD (% v/v or % w.b.)	High moisture increases adhesion/clodding, raises soil load, and amplifies collision/damage risk	Adjustable vibration/screening intensity; anti-clogging design; operating-window management	Protocol: measure at 0–10 cm and 10–20 cm using TDR/gravimetric method; record rainfall/irrigation history. Sampling: ≥15 readings/field. Stats: mean ± SD; P25–P75.
Soil type & cohesiveness/compaction (texture + cone index)	Texture class + cone index; report median [P25–P75] (kPa)	Cohesive soils increase draft resistance and adhesion; worsen separation/cleaning load	Drag-reduction tools + vibration cleaning; anti-adhesion surfaces/coatings; power matching	Protocol: texture by standard classification; cone index using penetrometer along 0–30 cm. Sampling: ≥5 profiles/field. Stats: median [P25–P75] for cone index; note clay content if available.
Mulch film presence & residual film level	Report coverage (%) and/or residual film mass per area (kg/ha), mean ± SD	Residual film drives entanglement/blockage and increases impurity content	Film breaking/guide device; anti-tangling end structures; improved separation/cleaning path	Protocol: quadrat survey (e.g., 1 m2) before harvest; collect and weigh residual film where feasible. Sampling: ≥10 quadrats/field. Stats: mean ± SD; record film type/thickness if known.
Stem/vine tenacity & twining tendency	Site-dependent; report tensile force at cut height mean ± SD (N)	Affects clamping/conveying stability and vine-cutting reliability; drives wrapping events	Tensioning + guided isolation; consistent cutting height; anti-wrapping layout	Protocol: measure vine tensile force using force gauge/spring scale at representative maturity; record vine length and canopy density class. Sampling: ≥30 stems/field. Stats: mean ± SD; P10–P90.
Surface condition (slope, roughness, stones)	Report slope (%) and roughness index; mean ± SD	Reduces passability and causes depth fluctuation, increasing missed harvest and damage	Tracked chassis or attitude correction; segmented operation; pre-leveling if needed	Protocol: slope by GNSS/clinometer; roughness by transect elevation RMS; stone density by counts per m2. Sampling: ≥3 transects/field + ≥10 stone-count plots. Stats: mean ± SD; report maximum slope.

. The cultivation techniques of ginger are shown in Figure 1.

Beyond measurement procedures, mechanism design requires quantitative property values that bound allowable contact stress, cutting force, and impact tolerance. Reported measurements show that ginger rhizomes exhibit distinct resistance levels between peel and flesh: peel-cut penetration forces are on the order of 10¹ N, whereas flesh-cut penetration forces are on the order of 10² N, and both increase after storage; peel penetration and rupture-compression forces are also measurable at the same order-of-magnitude level. These values vary with rhizome category (primary/secondary/tertiary fingers), moisture state (fresh vs. stored), and test configuration, so a minimum reporting set should include rhizome geometry, moisture content, loading rate, probe/blade geometry, and orientation.

2.1. Botanical and Biomechanical Characteristics of Ginger

The ginger rhizome consists of multiple segments connected in series, forming a clustered, branched structure. It lacks stable geometric references and repeatable load-bearing postures, which limits the universality of directional gripping and pulling strategies. In engineering practice, lifting-type excavation and flexible guiding-conveyance are more relied upon to stabilize posture evolution and reduce peak contact loads [20,21,22]. At the same time, dense fibrous roots and soil adhesion cause the harvested object to present as a composite of rhizome, fibrous roots, and soil. The mechanism of excavation resistance is closer to a coupled process of adhesion-shear and aggregate fragmentation. Simply increasing vibration intensity may enhance soil loosening and separation, but it easily raises relative speed and increases the risk of abrasion and breakage. Therefore, soil cleaning of low damage should be achieved through a combination of tool drag-reduction, sieve parameter matching, and smooth transition structures. The morphological parameters and mechanical measurement procedures of typical ginger rhizomes are illustrated in Figure 2, while the constraints and key control points imposed by ginger object properties on critical mechanism design are summarized in

Table 2. Constraints and key control points for critical mechanism design of ginger object properties.

Object Properties	Main Risks	Constraints on Mechanisms	Key Control Parameters/Structural Points	Quantitative Descriptors to Report (Template; Representative Order-of-Magnitude)
Cluster branching with unstable geometric reference	Unstable posture leading to secondary collision and fracture; limited repeatability for directional grasping	Avoid relying on single-point clamping or axial pulling as the primary strategy	Lift-type excavation path; guiding/limiting and complaining about buffering interfaces	Report rhizome category (primary/secondary fingers), size descriptors, moisture/storage state, and orientation. Use these to bound posture uncertainty and guide compliant-contact design.
Thin epidermis with low-damage tolerance	Bruising/cracking and peel abrasion reduce marketability and storability	Reduce peak contact pressure and impact energy; avoid sharp transitions and concentrated loads	Contact material/roughness; curvature radius; staged drop control; smooth transitions	Report probe/blade geometry, loading rate, moisture/storage state, and failure definition. Typical orders: peel-related forces ~100–101 N; peel rupture/compression ~101 N; flesh-penetration/cutting-related forces ~102 N (condition-dependent).
Significant entanglement of fibrous roots and adhesion to soil	Clod formation increases separation load; clogging elevates collision/abrasion risk	Soil cleaning must balance separation efficiency with low-damage constraints	Vibration frequency/amplitude; screen inclination/aperture; anti-clogging and anti-adhesion features	Report soil moisture (method + depth), texture, and cone index/penetration resistance; interpret separation-damage trade-offs under different soil states.
Seedling vines are tough and prone to twining/wrapping	Blockage, traction folding damage, and stoppage events dominate reliability losses	Above-ground handling and underground excavation must be coordinated	Tensioning and guiding isolation; uniform cutting height; anti-entanglement design at ends/inlets	Report vine interference level (canopy density class) and a tensile/drag proxy if available; report wrap events and mean time to recovery (MTTR) for reliability comparison.

. This provides a reusable experimental framework for subsequent mechanism design and parameter optimization.

2.2. Diversified Harvesting Models and Agronomic Standards

The harvesting methods of ginger can be summarized into three categories: manual digging, loosening-assisted harvesting, and mechanized harvesting. Mechanized harvesting aims to integrate processes such as digging, soil cleaning, separation, and material collection, with operational quality highly dependent on matching agronomic conditions. The core requirements include standardized ridge shapes and row spacing, management of film and residual film, selection of the optimal soil moisture window, and ensuring field passability [23,24]. Equipment represented by crawler-type self-propelled models integrates steps such as vibration digging, clamping and conveying, brush-based soil cleaning, cutting stalks, and conveying to collection boxes. Under experimental conditions, this system achieved a ginger recovery rate of 98.33%, a damage rate of 1.35%, and a miss rate of 0.32%, meeting industry standards for recovery, damage, and miss rates, with an operational efficiency of 0.081 ha/h, homologous value of manual harvesting [25]. Therefore, the coupling evaluation of agronomic standards and equipment capabilities should be upgraded from ‘harvestable’ to ‘quality-controllable’. The mechanized harvesting process of ginger is shown in Figure 3. The matching relationship between ginger cultivation agronomic conditions and harvesting modes, as well as engineering recommendations, are shown in

Table 3. Matching relationship between agronomic conditions and harvesting patterns and engineering recommendations.

Typical Condition Combination	More Suitable Harvesting Model	Main Risks	Supporting Agronomy and Equipment Recommendations
The ridge shape and row spacing are highly consistent, the plot is level, and the moisture content is moderate	Joint harvesting or semi-joint harvesting	Soil content rate and concurrent abrasions	Standardize ridge shapes and field-end spaces, and adjust screening parameters according to moisture content
Sticky, heavy soil or high moisture content after rain, with noticeable soil clumping	Crawler self-propelled or reinforced soil cleaning machine type	Heavy loading of loose soil increases the risk of collision	Prioritize drainage and moisture control, add anti-blockage measures, and strengthen soil structure
More residual film from mulching, and the seedlings and vines have high toughness	Strengthen seedling vine management and prevent entanglement	Entanglement blockage and traction folding damage	Membrane breaking and guiding with end anti-tangling, consistent seedling cutting height, and tension control
Uneven terrain or numerous ravines, insufficient accessibility	Tracked chassis or lightweight chassis	Deep Fluctuation and Missed Excavation	Chassis passability check, perform sectional operations, and optimize land leveling if necessary

.

2.3. Comparison with Harvesting Methods of Other Root Crops

As shown in

Table 4. Comparison between ginger and typical underground crop harvesting operation characteristics.

Crop	Harvest Target Morphological Features	Root-Soil Coupling and Burial Depth Characteristics (Revised)	Main Vulnerable Mechanism	Typical Mechanical Path	Transferable Insights for Ginger
Ginger	Clustered branched rhizomes, thin epidermis, weak morphological standards	Depth class: deep (>200 mm); strong root wrapping and adhesion	Scratches, fractures, and soil are causing secondary collisions	Lift-type excavation, soil separation, seedling vine handling, and material collection	Flexible contact + posture stability as core; coordinate anti-entanglement and multi-level soil cleaning
Potato	Tubers are relatively regular, with relatively good wear resistance	Depth class: moderate (100–200 mm); relatively concentrated distribution	Bruising and peeling	Chain digging, vibrating screening, graded boxing	Moisture-screening intensity matching; emphasize drop-height control
Sweet potato	The tuber is slender and easily bendable	Depth class: moderate (100–200 mm); wider lateral distribution	Bending, tearing, compression, and abrasion	Segmented excavation, guided support, and low-pressure conveying	Transfer guidance/support + low-pressure conveying principles for low-damage handling
Carrot	Axially defined root type	Depth class: moderate (100–200 mm); axial root, relatively concentrated	Root breakage and epidermal abrasion	Support or clamp lifting, soil separation	Clamping/lifting has limited applicability; separation/cleaning structures are transferable
Onion	Bulb with a distinct top structure	Depth class: shallow (<100 mm); near-surface bulb	Scrapes and crush injuries	Excavation and laying, collection and packing	Human–machine coordination for laying and aggregation placement
Turmeric-type crops	Rhizomes, prone to clumping with soil	Depth class: deep (>200 mm); clod adhesion is prominent in clay soils	Fracture with abrasion	Drag reduction, excavation, enhanced cleaning, and aggregation	Drag reduction + enhanced cleaning under sticky/heavy soils, with strict loss control
Peanut	Pods attached to roots; pulled up and shaken	Depth class: shallow (<100 mm); near-surface pod/root system; moisture-sensitive	Breakage and fallen pods	Pulling + shaking, laying/drying	Tensioning and vibration-control logic is transferable to vine handling/anti-entanglement

, the harvesting process of ginger for potatoes, sweet potatoes, carrots, onions, and turmeric crops involves loosening the soil, digging, separating, cleaning, and collecting. However, the shape of the crops, mechanisms of damage, and the intensity of root-soil coupling vary significantly, which determines the transferable boundaries and key aspects for modification in mechanization strategies [26]. The chain-type digging and vibrating screening system for potatoes is mature, with an emphasis on matching screening intensity to soil moisture content to reduce pressure damage and peeling; sweet potato tubers are slender and prone to bending, so guiding support and low-pressure conveying are more critical; carrots and onions have distinct axial or top structures, making a lifting harvest path feasible; in clay areas, turmeric crops often have soil clods adhering, and engineering approaches tend toward resistance reduction and enhanced cleaning combinations, but still require suppression of breakage and abrasion caused by vibration [27]. Accordingly, when ginger equipment draws on mature digging and screening structures, it should emphasize cradle-style digging with flexible contact interfaces, multi-stage separation with anti-blocking and anti-entangling features, parameter adjustability, and quality stability mechanisms to adapt to variations in moisture content and adhesiveness, and be constrained by comprehensive performance per industry standard indicators [28,29,30,31,32,33,34,35,36,37,38].

3. Technical Evolution and System Analysis of Ginger and Harvesting Machinery

The harvest target of ginger is the ‘rhizome cluster and root-soil complex’, whose mechanical response exhibits coupled characteristics of high adhesion, high dispersion, easy bruising, and easy breakage. The operation quality depends not only on whether excavation can lift the ginger, but also on the coordinated matching of root-soil disintegration, soil-ginger separation, stalk and vine handling, material conveying, and aggregation processes [39,40,41]. Under production conditions where ridge planting with plastic mulching, fluctuations in moisture content of heavy clay soils, and morphological differences among varieties coexist, ginger harvesting equipment has long shown multi-route parallel development: small loosening excavators focus mainly on reducing labor but rely on manual picking; medium shovel-sieve combination machines focus on soil cleaning but face damage constraints; self-propelled and combined machines focus on process integration but require higher reliability and parameter matching [42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68]. Therefore, this section takes ‘operation chain layering’ as the main thread, first presenting the machine type lineage and technical context, then systematically expanding on the structural forms and mechanism constraints of key components, and finally providing a comparative framework of parameters and indicators at the level of typical machine types.

3.1. Classification and Technical Development History of Harvesting Machinery

As shown in

Table 5. Ginger harvester model lineage and operation chain classification.

Route Category	Typical Operation Chain	Key Structural Modules	Advantages/Strengths	Main Weaknesses & Risks	Applicable Boundary Conditions	Representative Reference(s)
Loosening-digging with manual picking [42,45,46,47]	soil loosening and penetration; digging and lifting; windrowing/spreading; manual picking	digging share/blade; depth-control wheels; simple soil-shaking mechanism	low cost; simple structure; easy maintenance	high soil carryover; labor-intensive; large variability in missed digs	small plots; fragmented farming; relatively loose soils	Small plots, dispersed farming, relatively loose soil
Digging with screening and windrowing or gathering [42,45,49,50,51,52,53]	digging and lifting; vibrating screening; soil removal; windrowing or gathering	share-sieve combination; vibrating sieve; transition chutes/flow guides	improved soil cleaning; better operational continuity	aggressive screening can cause abrasion/bruising; prone to clogging	moderate soil moisture; well-formed, uniform ridges/beds	Moderate moisture content, relatively standard ridge shape
Digging-conveying with multi-stage separation and continuous cleaning [42,45,54,55,56,57]	digging; conveying; multi-stage soil separation/cleaning; impurity removal; collecting	rod-chain web; belt conveyor; secondary cleaning unit	low soil residue; convenient for bulk collection and transport	impact damage due to drop heights; complex structure	large-scale production bases; strong demand for continuous operation	Large-scale bases have strong demand for continuous operations
Clamp-pull extraction with assisted separation [42,45,54,55,56,57]	clamping and extraction; soil shaking; separation; collecting	clamping chains; tensioner; extraction guides	high efficiency potential in specific soils	clamp slippage; stalk/vine breakage; difficult to control abrasion	loose soils; vines/stems adequately handled beforehand	Loose soil, seedlings and vines properly handled
Fully integrated combine-type harvesting [42,45,58,59,60,61,62,63,64]	vine cutting; anti-wrapping; digging; soil cleaning; separation; conveying; boxing/binning	vine cutter; vine separation/guide device; vibrating sieve; collection bin/box	major labor reduction; improved controllability of quality	complex matching/integration; higher cost and maintenance requirements	custom service operations; standardized production bases	e.g., integrated/self-propelled harvester sources compiled in Section 3.3 and Table 8

, the classification of ginger harvester models should be centered on the operation chain, rather than simply divided by power source or chassis type. Practice has shown that the same power platform can be equipped with different digging and cleaning modules, and the key factors determining operational quality and damage levels are still the combination of “digging and lifting method, soil separation strategy, seedling vine handling path, conveying drop control, and material collection scheme” [42,45]. Based on the operation chain and the degree of functional integration, existing equipment can be summarized into five routes: (i) soil-loosening digging with manual picking; (ii) digging with screening and spreading or collecting; (iii) digging with conveying and separating for continuous cleaning; (iv) clamping and pulling with assisted separation; and (v) fully integrated whole process harvesting. As shown in Figure 4. The primary challenges for each route shift in stages: in the early stage, focusing on ‘being able to lift out,’ in the middle stage on ‘being able to separate,’ and in recent years on achieving ‘low damage stable continuity’ [46,47].

3.2. Key Functional Components and Technical Principles

The ginger harvesting system can be broken down into four categories of subprocesses: (i) soil entry excavation and lifting; (ii) root-soil disintegration and soil separation; (iii) seedling vine handling and anti-entanglement; and (iv) low damage conveying and aggregation. The common constraint across these four processes is to control the peak impact load and relative slip speed of the root-soil composite within an acceptable range, while ensuring disintegration and discharge efficiency of the soil, so that harvesting rate, soil content rate, and damage rate form a compatible combination [49,50]. To create a reusable review structure,

Table 6. Key component structural form library and applicable boundaries.

Component Stage	Typical Structural Configurations	Mechanism Highlights	Common Failure Modes	Key Tunable Parameters
Digging Penetration and Lifting	straight share; curved share; V-shaped or winged share; lifting/guide plate	forms a stable fracture plane and lifting trajectory to reduce soil bulldozing that buries the ginger rhizomes, and to limit cutting damage	missed digs; soil bulldozing/burying; cutting injuries; sudden draft spikes causing attitude drift	digging depth; penetration angle; rake/leading-edge angle; share width; wing angle
Drag Reduction and Anti-Adhesion	contoured low-drag surfaces; optimized share materials; surface coatings; soil-disturbing teeth or breaker teeth	reduces adhesive shear and material build-up, stabilizing draft power and penetration attitude	clay build-up; smeared/clogged share (soil sticking); entanglement by residual mulch film and roots	radius of curvature; surface roughness; tooth spacing; tooth height
Loosening, Disintegration, and Screening Soil Separation	vibrating digging share; eccentric-excited sieve; rod-chain vibrating web; double-deck screening	periodic excitation promotes disintegration and detachment, improving soil discharge rate	vibration-induced bruising; structural fatigue; screen blinding/clogging	frequency; amplitude; screen inclination; aperture size; linear speed
Conveying and Secondary Soil Cleaning	rod-chain web conveyor; belt conveyor; drum separator; rotary brush cleaning; airflow-based impurity removal	conveys while screening or performing secondary cleaning, reducing both soil carryover and impurity content	drop-impact abrasion/bruising; jamming at bends/turns; clogging	conveying speed; staged drop height; guide radius; material bed thickness
Vine/Stem Cutting and Anti-Wrapping	rotary cutter (disk/drum type); reciprocating cutter; circular disk blade; vine guiding and tensioning; isolation/deflector plates	separates vine and rhizome pathways to suppress wrapping and tensile pulling that can cause breakage	incomplete cutting; wrap-induced stoppage; pulling-induced breakage	blade speed; travel-speed matching; tension force; clearance/gap
Collection, Boxing, and Unloading	side collection bin; rear collection bin; soft-lined cushioning chute; tipping/unloading mechanism	controls drop height and secondary impacts to protect market quality and improve handling efficiency	bruising from excessive drop height; attitude changes as the bin becomes fully loaded	unloading drop height; cushioning structure; bin position

categorizes key components according to the “structural form library,” and specifies the mechanism essentials, failure modes, and adjustable parameters for each form.

3.2.1. Multi-Form Mechanisms and Design Essentials of Excavation Components

The primary objective of the excavation component is to achieve a stable soil entry for “lifting-type excavation” and to deliver the root-soil composite into subsequent separation stages with a controllable posture. As shown in Figure 5. A straight-blade structure offers a clear cutting path, but under heavy, sticky soil conditions it tends to cause soil accumulation and pushing, leading to buried ginger and missed digs; the curved-blade type forms a lifting trajectory via curved surface guidance, which can reduce instantaneous cutting peaks and improve the continuity of lifting, but is more sensitive to entry angle and depth; V-shaped or wing-shaped blades can alter the direction of crack propagation, making the soil easier to break apart and reducing the tendency for accumulation, suitable for scenarios with severe soil adhesion, but excessive wing angles will increase soil disturbance and resistance, leading to higher power consumption and unstable posture [49,50,51,52]. From an engineering parameter tuning perspective, excavation depth and entry angle determine whether “cutting and lifting” are well coordinated: insufficient depth causes missed digs and breakages, excessive depth sharply increases resistance and flips large soil chunks, raising the load for subsequent screening; a small entry angle easily pushes soil to bury ginger, while a large angle enhances cutting and increases the probability of crop damage. It is recommended to use a depth-limiting mechanism together with a guiding lifting plate to jointly constrain excavation depth and posture, so as to maintain repeatability under fluctuations in soil moisture and reduce the risk of simultaneous missed digs and damage at the source [49,50,51,52]. In practice, missed digs and cutting injuries are the dominant failure modes when depth control and soil-entry attitude are unstable, especially under ridge-height variability and cohesive clays that promote bulldozing and re-burying. Increasing penetration depth or entry angle can reduce missed harvest but often increases draft spikes and posture drift, which propagates downstream into higher screening load and collision risk. Therefore, the excavation module should be calibrated as a coupled “depth-attitude-draft” subsystem with allowable ranges that jointly constrain missed-harvest risk and peak contact load.

3.2.2. Classification of Soil Cleaning Forms in Vibrating Screening and Dual-Objective Constraints

The essence of the soil screening and cleaning process is to unify ‘soil disintegration efficiency’ and ‘damage risk’ within the same parameter system. As shown in Figure 6. Eccentric vibration screens and chain rod vibration screens are two mainstream forms: the eccentric vibration type promotes soil breakage and separation through periodic acceleration, while the chain rod screen achieves soil discharge via screen gaps and relative motion, also serving a conveying function. A double-layer screening structure can perform large chunk disintegration and coarse soil removal on the first layer, and fine soil discharge and soil content control on the second layer, making it suitable for severe adhesion conditions; the trade-off is that the material undergoes multiple excitations and transitions, and without drop control and buffered transitions, abrasions and collisions can increase significantly [53]. Therefore, soil screening and cleaning should not be guided solely by the principle of ‘faster soil discharge,’ but should adopt dual-objective constraints: measuring separation performance with harvest rate and soil content, and measuring quality risk with damage rate and skin-breaking rate, then optimizing through a combination match of screen surface inclination, screen hole size, screen surface linear velocity, and vibration parameters [53]. Tests and optimization results of shovel-screen combination machines show that when digging depth, screen surface inclination, screen hole size, and screen surface linear velocity are harmoniously matched, efficiency can be improved while keeping damage at a controllable level, thus forming a parameter range suitable for broader application [53]. Screening is a dual-objective problem: stronger excitation and larger relative motion can improve soil disintegration but elevate abrasion/bruise probability and fatigue risk. Under wet cohesive soils, the bottleneck often shifts from “separation efficiency” to “screen blinding and clogging,” where anti-adhesion and anti-clogging features can be more effective than simply increasing vibration intensity. We therefore recommend interpreting (and reporting) screening settings together with soil moisture/texture so that performance-damage trade-offs are transferable across sites.

3.2.3. Conveying Separation and Low Damage Control: Drop Management and Posture Shaping

Conveying and separation components often perform the “rhythm control” function for continuous operations, and their performance determines whether the system can stably output low soil content and low damage rates. As shown in Figure 7. The advantage of chain-rod screening conveyance is that it can achieve conveying and screening simultaneously; however, increasing the gap between rods and the speed will intensify the tumbling of ginger rhizomes, leading to segment collisions and abrasions. Belt conveying is more friendly to the skin surface and can reduce localized contact stress, but its soil removal capability depends on an external secondary soil removal device; under wet and sticky soil conditions, clogging and soil return are prone to occur [54,55,56]. Drum separation and roller-brush soil cleaning can be used for secondary soil and debris removal, but excessively high drum linear speeds can cause frictional abrasion, while excessively low speeds result in insufficient soil removal and material accumulation. In engineering practice, low damage control is recommended to focus on three operative points: reducing drop heights in sections and installing soft-lined buffer slides, increasing the guiding curvature radius at turning points to lower peak normal impacts, and controlling material layer thickness and uniform feeding structures to reduce the probability of random collisions [54,55,56]. When the system needs to adapt to residual film and root structures, a diversion isolation and pre-loosening disturbance should be installed at the conveying inlet to reduce entanglement and clogging occurrences, thereby ensuring that reliability indicators meet engineering deliverability requirements [57]. For conveying and secondary cleaning, the main damage drivers are staged drop impacts at transitions and repeated tumbling on fast chain-rod webs. A practical design rule is to treat each transfer point as a risk node and minimize its drop height and curvature-induced collision, while maintaining a controlled material bed thickness to avoid random impacts. This shifts low-damage control from single-component tuning to path-level impact-energy management.

3.2.4. Seedling Cutting and Anti-Tangling: Precondition for Continuous Operation Reliability

The function of vine handling lies not only in removing the above-ground parts, but also in achieving ‘path isolation between the vines and the tubers’, thereby preventing downtime incidents such as entanglement at the end of the conveying chain, blockage in the screening section, and pulling-induced breakage [58]. As shown in Figure 8. Disk-type vine cutters offer strong continuity in cutting and are suitable for higher walking speeds, but mismatches between cutter speed and walking speed can lead to incomplete cutting or excessive pulling. Reciprocating cutters are more sensitive to cutting precision and are suitable for dense vines under lower speed conditions. Circular disk cutters can be used for directional cutting and boundary severing, but depend heavily on vine guiding posture and tension control. The vine guiding tension and the isolation guide plate determine the vines’ degrees of freedom: insufficient tension will cause the vines to rebound into the conveying system, whereas excessive tension may pull the tubers and cause breakage. It is recommended to design the vine-cutting module and the isolation structure at the conveyor inlet as an integrated unit, forming a clear discharge path and anti-backflow boundary after cutting, with reliability indicators as hard constraints for system integration [58]. Vine and residual-film interference is a reliability-limiting factor because wrap-induced stoppage can dominate downtime even when basic digging and screening are adequate. The design target should therefore be “wrap suppression + fast recovery”: cutting completeness, clear vine-rhizome path isolation, and anti-backflow boundaries at inlets. For field evaluation, wrap events and mean time to recovery should be treated as hard reliability indicators rather than incidental observations.

3.3. Performance Comparison and Development Status of Typical Models

The comparison of typical ginger harvester routes should be grounded in quantitative evidence and consistent metric definitions; otherwise, reported efficiency and quality outcomes across studies are not directly comparable. Therefore, we synthesize field performance indicators from published studies, including field capacity (ha/h), recovery/harvest rate, missed-harvest/loss, damage rate, and soil carryover where available, and interpret these indicators jointly with operating conditions that strongly affect performance (e.g., soil texture and moisture, ridge geometry, residual mulch film, and vine interference). Within this framework,

Table 7. Mapping of the assignment quality evaluation index system and criteria.

Metric	Recommended Operational Definition	Measurement Location and Method	Engineering Significance	Typical Influencing Factors
Harvest Rate	ratio of the mass of intact ginger rhizomes that enter the collection stream or are windrowed/spread to the total harvestable mass in the field	weigh samples from defined plots; grade if necessary	system’s ability to recover the target material	digging depth; missed digs; windrowing/spreading losses; secondary drop-back losses
Missed-Harvest Rate/Loss Rate	proportion of ginger not excavated or not entering the collection chain	re-check and weigh the remaining material within the sample plots	integrity of the digging and conveying chain	insufficient digging depth; soil clodding; drop-back during conveying
Damage Rate	proportion (by mass) of ginger with damage such as skin abrasion/peeling and breakage	graded tally with explicit damage categories	marketability and storage/transport safety	vibration intensity; drop height; impact at turns; friction
Soil Carryover Ratio	proportion (by mass) of soil carried with the collected ginger	weigh before and after soil cleaning	cleaning effectiveness and downstream handling cost	screening settings; soil moisture; screen blinding/clogging
Blockage-Related Downtime Frequency	number of blockage-induced stoppages per unit area or per unit time	log stoppage events and causes during operation	system reliability and service capacity	residual mulch-film entanglement; inadequate vine/stem removal; excessive material bed thickness
Energy Consumption per Unit Area	fuel use or energy consumption per unit area	log power/energy and travel speed (and/or area covered)	energy efficiency and operating load	digging draft; soil adhesion; screening load

provides the operational definitions and measurement mappings of key indicators, and

Table 8. Comparison of structural parameters and operational indicators of typical ginger harvester models.

Machine Model/Study Object	Route Type	Chassis/Powertrain Type	Key Module Combination	Field Capacity/Throughput	Harvest Rate/Ginger Recovery Rate	Loss/Missed Harvest	Damage Rate	Typical Applicability Description
DC4US 600 Ginger Harvester	loosening-digging with manual picking	walk-behind or small power unit	digging share; depth control; soil shaking	1333–2000 ha/h	≤70%	≤30%	≤0.8%	suitable for small plots with low-cost labor savings, but overall labor reduction is constrained by the manual picking stage
Share-Sieve Combination Ginger Harvester	digging with screening and windrowing or gathering	tractor-towed or semi-self-propelled	digging and lifting; vibrating screening	0.41 ha/h	96.0%	not reported	4.1%	markedly improved soil cleaning; damage must be constrained through screening parameter optimization
Self-Propelled Ginger Harvester (Design and Experimental Prototype)	fully integrated combine-type harvesting	self-propelled chassis	digging; soil cleaning; vine cutting; separation; conveying; collecting	0.081 ha/h	98.33%	0.32%	1.35%	emphasizes low damage and consistent quality, reflecting the trend toward full integration
Tracked Self-Propelled Ginger Harvester	digging-conveying with separation and continuous cleaning	tracked self-propelled	digging; soil cleaning; separation; collecting	0.120 ha/h	94.41%	4.56%	1.93%	better stability under cohesive/heavy soils and uneven ground; reliability is a key challenge
Clamp-Pull Ginger Harvesting Test Platform	clamp-pull extraction with assisted separation	experimental test rig	clamping extraction; soil shaking; separation	not reported	93.8%	not reported	4.3%	highly sensitive to clamping stability and damage control; narrow applicability envelope

Note: Performance indicators are condition-dependent; where the original source reports test conditions (e.g., soil texture/moisture, ridge or mulch context, operating speed), they are considered in the interpretation; unavailable items are marked as not reported in the cited source.

compiles representative machine routes with reported performance to support evidence-based comparison and engineering interpretation [57,58,59,60,61,62,63,64,65,66].

Table 8 highlights that throughput and quality metrics vary substantially across technical routes and test environments. Walk-behind loosening-digging systems can reach an effective field capacity on the order of 10⁻¹ ha/h (converted from 1333 to 2000 m²/h), but their overall system performance is constrained by manual picking and typically exhibits lower recovery and higher loss. Shovel-sieve combination harvesters can achieve higher reported field capacity (e.g., 0.41 ha/h) with high recovery (96.0%), yet damage can increase (e.g., 4.1%), indicating that screening intensity must be tuned against bruise/peel risk under specific soil moisture and clod conditions. Integrated or tracked self-propelled systems show comparatively lower but stable reported capacity (e.g., 0.081–0.120 ha/h) with high recovery (94.41–98.33%) and lower damage (1.35–1.93%); however, their advantage is most evident when continuity and adaptability matter, such as cohesive or heavy soils and uneven ground, where blockage, soil adhesion, and vine-film interference can dominate downtime and quality loss. These comparisons also reveal a persistent reporting gap: key test-condition descriptors and missing indicators are not consistently documented across studies, which limits cross-study comparability and further motivates standardized evaluation protocols and condition-stratified reporting [57,58,59,60,61,62,63,64,65,66]. Specific representative aircraft models at home and abroad are shown in Figure 9.

4. Intelligent Harvesting and Agricultural Machinery Automation: Cutting-Edge Technologies and Application Pathways

Intelligent harvesting in ginger production is evolving from purely mechanical capability toward quality-controllable operation, where performance is evaluated not only by throughput but also by loss, damage, impurity load, and operational continuity under variable field conditions. In this review, we frame ‘intelligent technologies’ as deployable, function-oriented modules embedded into the harvesting operation chain, including multi-source perception, operating-condition recognition, risk prediction (blockage and damage), adaptive parameter regulation, quality monitoring, and traceability, which together form a closed-loop workflow of perception, decision, execution, and evaluation (Figure 10). Importantly, while fully autonomous ginger harvesting remains limited in current practice due to cost and data constraints, several sub-functions are already feasible and can be progressively integrated into commercial machines, such as assisted driving and row alignment, load and blockage early warning, and condition-triggered adjustment of digging depth, screening intensity, and conveying posture [69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84].

4.1. Multi-Source Perception and Key State Variable Construction

For the intelligent harvesting of ginger, the primary focus lies on ‘seeing clearly, measuring accurately, and calculating effectively’. Under the soil-ginger-machine strong coupling conditions, it is necessary to simultaneously obtain the morphology of the working object, soil physical properties, and the operating status of the machinery. A feasible approach is multi-source perception fusion: vision (RGB/near-infrared/depth) for identifying seedling vine distribution, exposed ginger rhizomes, and impurity detection; force/vibration/current/pressure for assessing digging resistance, conveying load, and early detection of blockages; GNSS/IMU for trajectory and ridge-alignment tracking; and soil moisture and compaction for working-condition classification and prior parameter estimation. The key is to construct a quality-oriented system of state variables, providing interpretable interfaces for subsequent control and adaptation [69,70,71,72,73,74,75,76,77,78,79,80].

The Internet of Things (IoT) and edge computing should serve the goals of “process traceability, parameter reusability, and quality comparability.” By leveraging onboard positioning, wireless communication, and task management, parameters such as speed, vibration, excavation depth, load/energy consumption, and evaluation results on impurities and damage are recorded as operational logs, thereby forming a cross-field and cross-season operating condition database [81,82]. This database not only supports remote operation and maintenance as well as fault diagnosis, but also provides sample data for training models based on “operating condition classification-parameter recommendation-quality prediction,” enabling the gradual transformation of experience-based parameter tuning into data-driven, interpretable rules [75,78].

4.2. Adaptive Decision-Making and Closed-Loop Control

Based on multi-source perception, the key to intelligence is upgrading parameter adjustment from empirical rules to verifiable closed-loop control. It is recommended to adopt a hybrid framework of “mechanism constraints + data-driven” approaches: on one hand, use discrete element/multibody dynamics together with field calibration to establish mappings between sensitive parameters of key mechanisms and quality indicators (e.g., amplitude/frequency-separation efficiency, conveying speed/collision intensity, excavation depth/missed harvests, and root breakage); on the other hand, apply machine learning to perform online prediction of operating condition classification, blockage, and damage risks, thereby achieving parameter self-adaptation (speed, vibration, sieve angle, air volume, gap between cutting/stem guiding mechanisms, etc.) and operating condition switching (light load/heavy load, clay/sandy loam). The control objectives should be expanded from a single “maximum efficiency” to a multi-objective trade-off: under the constraint of operational capability, minimize damage and soil/impurity content while suppressing blockage risks and simultaneously ensure energy consumption and reliability [75,76,77,80].

As shown in

Table 9. Ginger intelligent harvesting: Key points and quantitative indicator recommendations for perception, decision-making, and execution.

Stage	Core Objective	Sensed Variables	Decision and Control Logic	Actuators	Suggested Metric Definitions
Digging Depth and Attitude Control	reduce missed digs and suppress draft/load fluctuations	depth displacement and attitude; draft force or drive current	operating-condition recognition with constraint-based gain scheduling; error feedback with saturation/limiting	depth-adjustment mechanism and attitude adjustment	missed-dig rate; energy consumption per unit area; coefficient of variation in draft/load
Coordinated Speed Control	increase throughput while meeting damage constraints	material flow rate; blockage precursors; proxy for soil moisture	dynamic update of speed ceiling based on load and damage risk	travel drive system	effective field capacity; number of stoppages; damage rate
Screening and Soil-Cleaning Intensity Control	reduce soil carryover while limiting abrasion	vibration parameters; material bed thickness; proxy for soil carryover	intensity tiering with real-time correction	exciter and screen drive	soil carryover ratio; impurity content; abrasion rate
Conveying and Drop-Height Management	minimize secondary impacts/collisions	acceleration; drop height; flow rate	staged drop-height design with matched cushioning strategy	conveyors and cushioning chutes	peak impact acceleration; skin-abrasion/peeling rate; breakage rate
Vine Cutting and Anti-Wrapping	reduce wrap-induced stoppages	rotational speed; torque; vine accumulation indicators	adaptive adjustment of speed and tension based on load	cutter drive and tensioning mechanism	cutting completeness rate; number of wrapping events; mean time to recovery
Blockage Early Warning and Intervention	intervene early to reduce downtime losses	current; vibration; vision-based blockage indicators	anomaly detection with a graded intervention strategy	reverse drive, shaking, or bypass mechanism	number of stoppages; mean time to recovery; operational continuity

, for root and tuber crops like ginger, a more practical direction for field harvesting is an ‘automated operation system’ rather than a single-point ‘robotic terminal.’ The focus can be on three implementable technologies: first, automatic row alignment/automatic navigation and ridge direction maintenance to reduce operator workload and stabilize digging depth [73,74]; second, adaptive parameter adjustment based on operating condition recognition, achieving fault-tolerant control with blockage warning-bypass/reverse-recovery functions [78,79]; third, online monitoring and traceability of operation quality, linking soil and impurity content, damage rate, and grading results to post-harvest cleaning, grading, and storage/transport processes, forming a ‘harvest-post-harvest’ collaborative optimization [81,82].

4.3. Assisted Driving, Automated Operations, and System Integration

In terms of system integration, it is recommended to adopt a modular and interface-standardized approach: the perception module (vision/mechanics/pose/soil), execution module (excavation, separation, conveying, collecting/packing), control module (edge computing and controllers), and data module (operation logs and quality archives) should be relatively decoupled to facilitate rapid integration and upgrades across different machine models; at the same time, with consideration for the industry chain, priority should be given to connecting quality indicator interfaces with post-harvest cleaning, grading, storage, and preservation, so that field indicators such as “low damage, low impurities, low clogging” can be directly translated into improved post-harvest efficiency and commodity yield.

For large-scale and high-intensity scenarios, the priority focus of automation is “assisted driving + online management of operational quality”: on one hand, reducing missed rows and duplicate operations through row and ridge alignment as well as turn path planning, while stabilizing digging depth and soil entry angle [83,84]; on the other hand, establishing an online monitoring-alert-response strategy centered on blockage, load, and damage risks to improve continuous operation reliability. Compared with full unmanned operation, this approach relies less on infrastructure and data conditions and is more aligned with the current service-oriented operational organization model of ginger production in China [75,78,79].

4.4. Data Standards, Evaluation Methods, and Open Sharing

One of the key bottlenecks in implementing intelligent solutions lies in the lack of standardized data and evaluation criteria: for the same machine model, statistical definitions and test scenarios for indicators such as missed harvesting, root breakage, bruising, skin damage, soil and debris content vary under different soil moisture levels, ridge shapes, vine coverage, and variety conditions, resulting in ‘poor comparability and weak reproducibility.’ It is recommended to establish a graded evaluation system for ginger harvesting: using damage (external/internal), soil and debris content, missed harvesting, and blockage as core indicators, supported by unified sampling and measurement methods, and providing practical measurement schemes for key process variables (collision intensity, digging resistance, screening load, etc.) [69,70,71,72,75,77,78,79,80,81,82,83,84].

At the same time, efforts should be made to promote open data and test benchmarks: build reusable “working conditions-parameters-results” datasets within typical soil types and moisture ranges to support reproducible algorithm verification and cross-model migration; and achieve interface linkage in the post-production stage through operation logs and quality archives, providing an evidence chain for industrial-scale promotion [69,70,71,72,75,77,78,79,80,81,82,83,84].

5. Challenges, Trends, and Prospects

5.1. Main Challenges Currently Faced

Although ginger equipment has undergone continuous iterations, its large-scale application in China and other major producing countries still faces multiple constraints, mainly reflected in the following aspects:

(1)

Complex operating environments and insufficient engineering adaptability: Ginger planting spans ecological types and operational models with significant differences. In major production areas such as China’s Huang-Huai region, high ridges with film covering and irrigated fields are predominant, while rainfed hillside ginger gardens are typical in countries such as India and Nigeria, and certain regions of Japan and South Korea feature facility-based or semi-facility cultivation forms. There are marked differences between regions in soil texture, fluctuations in moisture content, slope gradient, plot regularity, and field road conditions. Existing machine models are mostly designed for flat, dry land with relatively uniform soils, and in high-moisture, heavy clay soils, sloped farmland, and fragmented small plots, issues such as slipping, getting stuck, conveyor blockages, increased missed digging rate, and reduced operational continuity tend to occur, undermining the reliability of cross-regional promotion and raising retrofit and maintenance costs. Road limitations and turning radius constraints are more prominent in hilly and mountainous areas, making it difficult for medium and large combined machinery to enter the plots, thus highlighting the urgent need for lightweight, high-mobility equipment suited to complex terrains.

(2)

The conflict between low damage and high-efficiency processing: The epidermis of ginger rhizomes is sensitive and irregular in shape, and mechanized operations inevitably introduce compression, impact, and shearing forces. Under conditions of increased heterogeneity in production scenarios, influenced by factors such as soil cohesion, variation in burial depth, differences in block shape, and changes in cortex strength, skin breakage, fracturing, and latent tissue damage tend to be magnified in a fluctuating manner. Both engineering tests and international experience indicate that increasing the digging angle, forward speed, or vibration intensity can help reduce missed harvesting and increase excavation rate, but this is often accompanied by a rise in damage rate, manifesting as an unavoidable trade-off between excavation rate and damage rate. How to establish mechanisms and control strategies that can dynamically balance excavation rate and damage rate with changing operating conditions, through drag reduction and flexible contact structures, optimization of soil separation and cleaning paths, and precise parameter control, is a key issue for subsequent research and development.

(3)

Limited level of intelligence and cost-effectiveness constraints: Globally, there is still a lack of mature equipment capable of achieving full-process perception and closed-loop decision-making for ginger. Engineering applications mostly remain at the stages of navigation assistance, basic payload sensing, remote monitoring, and simple operating condition recording. Compared with grains and staple root crops, the planting scale of ginger is relatively small and spatially dispersed, with limited annual service area per machine. High-cost sensors and onboard computing platforms are difficult to amortize economically through operational volume within the depreciation cycle, resulting in a gap between technical feasibility and economic viability. In regions dominated by smallholders and small- to medium-sized farms, the mismatch between intelligent retrofit costs and per-crop returns is even more pronounced, impeding the large-scale penetration of advanced functions into the ginger sector.

(4)

Weak data and standards system: Ginger harvesting lacks systematic basic data and unified standards. At the basic testing level, there is insufficient measured data on ginger rhizome geometry statistics, tissue mechanical parameters, and responses of digging resistance and separation processes under different soil moisture conditions, making structural design and numerical simulation prone to relying on experience or crop analogy. At the operational quality evaluation level, no quantitative correspondence between damage grades and product rate or storage performance has been established, and there is a lack of universally applicable testing procedures and evaluation standards, resulting in insufficient comparability of test results between different machine models and regions. At the algorithm training resource level, field images and videos, as well as multi-source sensing data, lack standardized collection and sharing, making it difficult to support high-quality training and cross-regional transfer of recognition, separation discrimination, and working condition diagnosis models.

(5)

Differences in industrial organization and social acceptance: The promotion of equipment is constrained not only by technical performance but also by organizational and institutional conditions. In China, the industry is moving toward moderately scaled operations, cooperative organizations, and socialized service systems, yet smallholder fragmentation remains pronounced. Some growers have uncertain expectations regarding soil disturbance, block damage, and input-output ratio, while maintenance support and service networks are still underdeveloped in certain regions, leading to a longer transition cycle from demonstration to commercial operation. In countries such as India and Nigeria, there is a lack of machinery acquisition and maintenance resources at the regional scale and insufficient cross-regional operation entities, which increases the investment risk and operational difficulties for specialized equipment. The absence of financial tools, training systems, and service organization models matched to the equipment will significantly weaken the speed of technology diffusion.

5.2. Future Development Trends

Addressing the common needs of China and major producing countries, the ginger and harvesting machinery will evolve toward systematization, layering, and servitization in terms of integration and intelligence, with key trends as follows:

(1)

Evolution from single dedicated machines to a platform-based and modular equipment system: The crop-specific characteristics of ginger determine that key operational units must still remain specialized, but its planting scale and spatial distribution make it difficult to support a completely independent, high-cost equipment lineage. The optimal path is to promote platformization of chassis and power systems, and modularization of operational functions. On a unified platform, by replacing digging and drag-reduction components, vibration soil-cleaning units, conveying buffers, and end-point collection modules, rapid switching between root crops such as potatoes and carrots can be achieved. Through parameter calibration, the operational constraints of ginger and low damage can be met, thus improving utilization and spreading R&D and manufacturing costs.

(2)

Development of lightweight intelligent equipment for smallholder farmers and hilly terrain: In major production areas of Asia and Africa, sloping land, small plots, and limited road conditions are common, making medium- and large-scale combined machinery difficult to become mainstream. Centered on a lightweight self-propelled chassis, equipped with a flexible digging mechanism with adjustable digging depth and a simple, reliable vibrating soil cleaning unit, and embedded with low-cost positioning and row-spacing recognition functions, this design creates an operating mode combining semi-automatic driving with manual-assisted sorting. This approach better meets the needs of small and medium-scale operators in terms of purchase cost, maintenance difficulty, and maneuverability, and is expected to become an important path for improving coverage in developing countries.

(3)

Systematic collaborative optimization of agricultural machinery and agronomy varieties: The mismatch between agricultural machinery and agronomy is a common bottleneck for ginger mechanization. At the variety level, it is necessary to balance quality and stress resistance, enhance adaptability to mechanization, and pay attention to tuber shape uniformity, peel wear resistance, and root distribution characteristics. At the agronomy level, mechanical operability should be incorporated into cultivation system constraints, promote standardized ridge shapes and row spacing, improve land preparation quality, optimize film mulching and residue removal management, and establish more quantifiable methods for determining the optimal harvest period. At the machinery level, multiple parameter schemes should be preset for variety-soil combinations, and association databases between variety-soil-agronomic features and equipment parameters should be established through calibration trials, thereby reducing the difficulty for operators to adjust parameters under complex conditions and improving operational consistency.

(4)

Data-driven intelligent decision-making and service model innovation: With the widespread adoption of operation monitoring terminals and agricultural cloud platforms, the ginger harvester can be conditionally integrated into a full-cycle data closed loop. By accumulating long-term data on soil and weather conditions, variety characteristics, field management, and operational processes, it is possible to develop models for optimizing harvest timing, diagnosing equipment health, and assessing operational quality, thereby enhancing the interpretability and reusability of decisions. At the organizational level, a service-centered operational model can be explored, where cooperatives or third-party service organizations centrally allocate equipment. Through order scheduling and quality-based pricing mechanisms, equipment utilization rates and risk-sharing capabilities can be improved, promoting the formation of a closed-loop ecosystem that integrates algorithms, data, equipment, and services.

6. Summary

Ginger harvesting machinery transformation and intelligentization are critical links that urgently need breakthroughs in high-value specialty crop production systems. The technical challenges are concentrated in adapting to complex working conditions, ensuring high integrity protection for low-damage-sensitive materials, improving operational continuity, and balancing economic scalability. International experience shows that the advanced capabilities of root and tuber crop harvesting equipment depend not only on the structural performance of individual machines but also on system integration of sensing and monitoring, parameter control, and operational organization. The ginger scenario, characterized by strong soil adhesion, interference from remaining stalks and mulch, and susceptibility of blocks to damage, requires a closed-loop optimization path guided by quality indicators. Looking forward, the main focus should be on building platform-based and modular equipment spectra to form a layered equipment system covering both large-scale bases and fragmented hilly areas; promoting standardization of cultivation systems and regional parameter calibration based on agri-machinery-agronomy-variety collaboration; improving testing and evaluation specifications and open data resources through data and standard system development; and enhancing the utilization rate and diffusion speed of specialized equipment through innovations in socialized services and financial tools. By advancing in tandem through technological innovation, standard guidance, and service organization, ginger harvesting will gradually progress from single-machine labor reduction to system-wide quality and efficiency improvement, providing solid support for the efficient, green, and sustainable development of the specialty crop industry.