Search Results (280)

Leaf area (LA) is a fundamental growth variable for understanding physiological processes and crop yield, but direct measurements are often destructive and time-consuming. This study aimed to develop non-destructive allometric models for estimating the leaf area of sweet potato (Ipomoea batatas [L.] Lam.) cultivars using leaf dimensions. Morphological data, including leaf length (L), width (W), and their product (L × W), were collected from various cultivars. Linear, power, and exponential models were tested and validated using statistical indices such as the coefficient of determination (R²), root mean square error (RMSE), and Willmott’s d-index. The results indicated that models based on the product of length and width (L × W) provided the most accurate estimations within the evaluated dataset, exhibiting high predictive accuracy (R² ≥ 0.96, RMSE ranging from 4.24 to 5.19 cm², and Willmott’s d-index ≥ 0.98). This non-destructive approach can support rapid, precise leaf area monitoring without leaf harvesting, particularly in the evaluated cultivars and experimental conditions. In conclusion, the proposed allometric equations provide practical and accurate tools for estimating sweet potato leaf area and supporting growth assessments in similar experimental contexts. Full article

Oxalis tuberosa (Oca) is traditionally cultivated in the high Andean regions of Peru and represents a promising alternative source of starch with potential industrial uses, ranking among the most essential tubers after the potato. This study aimed to evaluate the physicochemical, morphological, techno-functional, and thermal properties of starch isolated from three specific varieties of Oca (yellow, black, and white) harvested at the Ccanccayllo production center in Andahuaylas, Peru. The isolated starches exhibited high purity, characterized by high luminosity (L* > 92.28) and a whiteness index exceeding 92.10. Moisture content ranged from 9.36% to 10.01%, correlating with low water activity (a_w = 0.44), indicating stability. Notably, the amylose content was significantly higher than that of other previously studied Oca varieties. This composition contributed to a favorable water absorption capacity, solubility index, swelling power, and viscosity, with the white variety displaying superior functional performance. Colloidal stability in aqueous media was moderate, as indicated by zeta potential analysis. Particle size analysis revealed granules ranging from 26.32 to 27.74 μm, with elongated and oval morphologies confirmed by SEM, displaying characteristic functional groups. Thermal analysis (DSC) demonstrated gelatinization temperatures between 52.73 and 53.12 °C and enthalpies ranging from 4.92 to 6.11 J/g, while Thermogravimetric Analysis (TGA) indicated thermal degradation up to approximately 74–80%. These findings suggest that the studied Oca starches possess significant potential for application in the food and pharmaceutical industries due to their distinct functional properties. Full article

This study investigated whether storage changes the composition of Fontane and Challenger potatoes, including their starch characteristics, and whether these changes impact the properties of (deep-fried) mashes made from these potatoes stored for up to eight months. Fontane mashes showed an increase in firmness and viscoelasticity when potatoes were stored for a longer time. Moreover, when deep-fried mashes were made with Fontane potatoes, more water evaporated during deep frying and the resultant oil content increased as a function of the storage duration of the potatoes used to make them. This was not observed in mashes made from Challenger potatoes. Since the potato composition, starch characteristics and molecular mobility in mashes were minimally impacted by potato storage for both cultivars, it is assumed that storage-induced changes in potato cell walls and/or pectin methyl esterase activity contribute to the observed differences between deep-fried mashes made from fresh versus stored Fontane potatoes. The acquired insights help understand how potato storage can impact the properties of (deep-fried) potato mash-based products and highlight the potential to mitigate storage-induced declines in product quality by selecting cultivars based on the potato storage time. Full article

Vegetable sweet potato shoot tips are harvested repeatedly for fresh markets, but harvest timing and cut length are still determined largely by experience, limiting their translation into mechanized design parameters and control thresholds. We conducted a two-factor shear-mechanics experiment using three cultivars (‘Fu 23’, ‘Fu 18’, and ‘HD-V4’) and five shoot-tip length levels (10–30 cm), while also measuring stem diameter and moisture content. Because shear tests were performed on short stem segments sampled from a fixed internodal position relative to the apex, the length factor is interpreted mainly as a field-operable harvest criterion and only secondarily as a variable partly associated with tissue position. Moisture content was uniformly high and did not differ among cultivars (p > 0.05). In a pooled two-way ANOVA, length significantly affected maximum shear force (p < 0.01), cultivar was also significant (p < 0.05), and the interaction was not significant (p > 0.05). After including stem diameter as a covariate, both diameter and length remained significant, whereas cultivar became non-significant, indicating that stem diameter explains much of the apparent cultivar difference in absolute load. The reported stress is nominal shear stress. Laboratory-based 95th percentile design loads with γ = 1.3 provide conservative engineering thresholds for preliminary design and harvest-window back-calculation. Full article

Potato is one of the most important food crops worldwide, playing a critical role in global food security and agricultural production. The broken and impurity rates are important indicators for evaluating the harvesting quality of potato combine harvesting operations. To address the difficulty of achieving continuous and online detection using traditional methods, this study investigates an online monitoring approach for potato combine harvesting based on machine vision. Considering the characteristics of large material volume, severe overlap, and similar appearance features under field operating conditions, an online monitoring device suitable for potato combine harvesters was designed, along with a corresponding image acquisition and processing workflow. For the online monitoring device, an improved You Only Look Once version 11 (YOLOv11) detection model, was proposed to meet the requirements of multi-object detection in complex operating scenarios. The model incorporates Multi-Scale Depthwise Convolution (MSDConv), C2PSA_DCA (with Directional Context Attention, DCA), and Directional Selective Attention (DSA) modules, and introduces the Efficient Intersection over Union (EIoU) loss function to enhance recognition capability for broken potatoes and multiple types of impurity targets. While maintaining lightweight characteristics, the improved model demonstrates favorable detection accuracy. Field experiment results show that when the combine harvester operates at a forward speed of 3 km/h, the relative errors for broken and impurity rates are measured as 3.78% and 3.67%, respectively. Under extreme operating conditions with a speed of 4 km/h, the corresponding average relative errors rise to 8.30% and 8.72%, respectively. Overall, the online detection results exhibit satisfactory consistency with manual measurements, providing effective technical support for real-time monitoring of harvesting quality in potato combine harvesting operations. Future research will focus on expanding multi-scenario datasets under diverse soil and illumination conditions, as well as integrating detection results with adaptive control strategies to further enhance intelligent harvesting performance. Full article

To address the problems of high digging resistance, elevated energy consumption, and severe soil adhesion encountered during mechanized potato harvesting, a bionic potato digging shovel inspired by the corrugated dorsal structure of the white grub was developed. Based on reverse-engineered geometric curves, two longitudinally corrugated shovel models (L-S-1 and L-S-2) were constructed, and a coupled soil–potato–shovel model was established using the Discrete Element Method (DEM) to evaluate soil disturbance characteristics and digging resistance at a forward speed of 0.5 m/s and an entry angle of 35°. The simulation results indicated that the longitudinally corrugated shovel L-S-2 exhibited the best overall performance, reducing digging resistance by 13.87% and increasing the soil fragmentation rate by 20.67% compared with a conventional flat shovel (P-S). Using L-S-2 as the baseline design, additional DEM simulations were conducted at forward speeds ranging from 0.4 to 0.6 m/s to systematically investigate the influence of operating speed on digging performance. To further enhance anti-adhesion performance, a composite bionic shovel (H-L-S-2) was developed by embedding polytetrafluoroethylene (PTFE) hydrophobic material into the surface of L-S-2 and reinforcing the shovel tip using laser cladding. Soil-bin experiments were then performed under controlled conditions with forward speeds of 0.4–0.6 m/s and soil moisture contents of 15–20% at an entry angle of 35°, and the results showed an average resistance reduction rate of 17.46%, with a maximum reduction of 18.02%. Both DEM simulations and soil-bin tests confirmed the effectiveness of the composite bionic shovel in reducing soil adhesion, with the number of adhered soil particles decreasing by 41.2% in simulations and the mass of adhered soil reduced by 37.5% in physical tests. These results demonstrate that coupling a bionic corrugated structure with surface material modification can effectively reduce digging resistance, enhance soil fragmentation, and mitigate soil adhesion, providing a practical approach for optimizing the design of potato digging shovels. Full article

Mechanical harvesting damage is a critical factor constraining potato quality and storage performance. Field curing is a commonly employed pre-treatment prior to mechanical picking of potatoes, which promotes skin suberization and reduces mechanical damage; however, the determination of optimal curing duration lacks a theoretical basis. This study investigated ‘Xisen No. 6’ potatoes at harvest maturity. Curing was performed by field sun-drying (open-air exposure) immediately after mechanical excavation, with five duration gradients (0, 1, 2, 3, and 4 h) established under the recorded meteorological conditions. Twenty-two physical–mechanical and damage parameters were measured, and principal component analysis (PCA) was employed for comprehensive evaluation. The results demonstrated that curing induced a transformation of tubers from “soft-elastic bodies” to “hard-brittle bodies”. This study first revealed the contradictory evolution pattern between skin abrasion damage and tissue impact damage, which exhibited a strong negative correlation (r = −0.89, p < 0.01). PCA indicated that a 3 h curing duration could effectively balance the control of both damage types. These findings provide a quantitative solution to the dilemma of reducing skin damage while controlling impact damage during mechanical potato harvesting, offering significant guidance for optimizing harvesting process parameters and reducing postharvest losses. Full article

New Zealand’s kiwifruit and apple industries generate substantial quantities of organic residues during thinning and harvest, much of which is composted or disposed of in landfills due to logistical constraints. This study evaluates the potential of these residues as feedstock for biomethane production via anaerobic digestion (AD), followed by hydrogen generation through steam methane reforming (SMR). Two feedstock mixtures were examined: a 50:50 kiwifruit–apple blend and a 40:40:20 kiwifruit–apple–potato mixture, designed to mitigate acidification. Cow manure served as a cost-effective inoculum. Physicochemical analysis confirmed high moisture and volatile solids content, indicating strong biodegradability, although low nitrogen content suggests the need for co-digestion in full scale systems. Biomethane potential (BMP) tests yielded up to 45 mL CH₄/gVS at an ISR of 4, corresponding to 46.5% carbon conversion. Scaling to an annual waste volume of 476 t suggests a potential biomethane yield of approximately 18,000 m³. SMR simulations demonstrated technical feasibility, with methane conversion increasing from 46% under baseline conditions to >85% under optimized steam to carbon ratios and residence times. Hydrogen yields of ~7600 m³/year were estimated. This study provides a practical foundation for valorizing fruit waste into renewable biomethane and hydrogen, supporting New Zealand’s circular economy and decarbonization goals. Full article

This study evaluates the environmental performance of plywood manufactured from thermally modified birch veneers using the Thermovuoto^® process, bonded with a birch bark–derived suberinic acids adhesive. Framed within the context of sustainable materials development and the circular bioeconomy, the research examines the potential of bio-based adhesive systems as alternatives to conventional phenol–formaldehyde resins. A cradle-to-grave life cycle assessment (LCA) was performed, encompassing birch bark harvesting, adhesive production, veneer thermal modification, plywood manufacturing, distribution to the customer, and end-of-life management. Environmental impacts were modelled using openLCA 2.4 in combination with the Ecoinvent 3.11 database, in accordance with ISO 14040 and ISO 14044, applying the ReCiPe 2016 v.1.03 (H) midpoint life cycle impact assessment method. The results indicate that the birch bark extraction stage, particularly ethanol use derived from potato fermentation, constitutes the dominant contributor across all assessed impact categories. Overall, the LCA outcomes suggest that thermally modified, suberinic-acid-bonded birch plywood represents a promising niche bio-based material, with clear potential for further environmental improvement through process optimization. Full article

Potato combine harvesters often face the challenge of balancing efficient potato–soil separation with minimizing tuber mechanical damage, which significantly affects harvest quality and economic returns. To address this issue, a dual-vibration potato–soil separation conveyor was designed based on agronomic planting parameters and soil physical characteristics. A high-fidelity DEM-MBD coupling simulation model was developed to analyze soil clod breakage behavior and potato collision-induced jumping dynamics, and to identify key operational factors influencing separation performance. The porosity was verified using computer vision combined with CT technology to ensure the model’s fidelity. Single-factor simulations and a central composite design (CCD) response surface experiment were conducted using potato damage rate and soil removal efficiency as evaluation indices. The results showed that the inclination angle α, conveying line speed V_f, and vibration frequency f were the dominant factors affecting separation efficiency and tuber integrity. Multi-objective optimization determined optimal operating parameters of α = 18.51°, V_f = 1.995 km·h⁻¹, and f = 6.22 Hz, under which soil removal efficiency reached 98.43% and the minimum damage rate was 1.60%. Field experiments using a 4U-1000 combine harvester verified the simulation results, with an average soil removal efficiency of 97.8% and an average damage rate of 1.62%. These findings confirm the accuracy of the DEM-MBD simulation model and provide theoretical guidance for optimizing separation devices in large-scale potato harvesting equipment. Full article

Potato harvesters operating in hilly and mountainous areas are often subjected to harsh working conditions such as high temperature, sun exposure, and high torque excavation. Due to the fluid sealing characteristics, closed loop hydraulic systems are prone to high temperatures during long-term continuous operation, resulting in a decrease in fluid viscosity, poor lubrication, severe wear, and power attenuation. This study investigates the hydraulic system of potato harvesters in hilly terrain, systematically analyzing its energy transfer process and identifying key heat-generating components. Based on an optimization strategy that extends the flow path of high-temperature fluid within the tank, four distinct tank designs were proposed. Computational fluid dynamics (CFD) and thermodynamic simulations were conducted to evaluate their heat dissipation performance, followed by full-machine validation testing. Results indicate that the walking and lifting systems are the primary heat sources. The dual pump contributes the highest proportion of heat (52.07%), followed by the walking motor (20.54%). The heat exchanger dissipates 72.91% of the heat, while the hydraulic oil tank accounts for 14.93%. Among the four tank designs, Tank 0 exhibited the fastest temperature rise, reaching a thermal equilibrium of 83.27 °C, whereas Tank 1 had the lowest equilibrium temperature (78.62 °C). Heat dissipation efficiencies for the tanks were 7.8%, 12.9%, 10.1%, and 11.6%, respectively. The residual gas volume fraction decreases significantly as the bubble diameter increases, due to the higher buoyancy and faster rise velocity of larger bubbles, which leads to shorter residence times and more effective precipitation. Tank 1 achieved the lowest equilibrium temperature, indicating the best thermal efficiency. Tank 3 showed the best overall degassing performance, particularly for medium-to-large bubbles. Tank 1 was selected as the optimal final design because it could offer an excellent balance, with very good cooling and competitive degassing (especially for small bubbles). Field tests confirmed a 14.8% reduction in thermal equilibrium temperature for Tank 1 (75.6 °C) compared to Tank 0 (88.7 °C). Simulation and experimental data showed strong agreement, with maximum errors of 9.2% for return fluid temperature, 12.7% for cooling return fluid temperature, 9.7% for pressure, and 8.5% for flow rate. Average errors remained below 8.4% for pressure and 7.6% for flow rate. These results validate the accuracy of the simulation model and the effectiveness of the tank optimization method. Full article

Potato tubers can be dormant for 1–15 weeks after harvest, and the germination of tuber eye-buds is suppressed by cold. Genetic mechanisms regulating bud dormancy at low temperatures are not completely understood. We performed RNA-seq to compare gene expression in tubers after 0.5, 3.5, and 6.5 months of cold storage. Differentially expressed genes (DEGs) in non-dormant (3.5/6.5 months) vs. dormant (0.5 months) tubers were associated with transcriptional and translational activation, cell growth, metabolism, hormonal signaling, meristem development, dormancy break, and reproduction, confirming the non-dormant state of the meristem in the middle of storage. DEGs encoding transcription factors (TFs) (CBF1, FLC, SVP, HY5, GI, CO, FT, SOC1, CDF1, POTM1) were associated with the regulation of dormancy, flowering, and tuberization. TF DEGs upregulated (78) or downregulated (224) over four times in non-dormant vs. dormant tubers are considered potential coordinators of the endo- to non-dormancy transition and upcoming tuber sprouting during cold storage. RT-qPCR analysis of non-dormant and germinating buds revealed the upregulation of tuberigens (StSP3D, StFTL1-1, StFTL1-2), anti-tuberigens (StSP5G-like), and TF genes positively associated with tuberization or flowering/germination (StFDL1, StFDL, StCDF1, StCO-like). Our results should further investigation of the mechanisms underlying tuber meristem dormancy release and sprouting during long-term cold storage. Full article

An advanced artificial intelligence (AI)-powered mobile automated impurity removal system was developed and integrated into potato harvesting machinery for decentralized agricultural environments in Japan. As opposed existing stationary AI systems in centralized processing facilities, this mobile prototype enables on-field impurity removal in real time through a systematic dual-evaluation methodology. The system integrates the YOLOX-small architecture with precision pneumatic actuators and achieves 40–50 FPS processing under dynamic field conditions. Algorithm validation across 10 morphologically diverse potato varieties (Danshaku, Harrow Moon, Hokkaikogane, Kitaakari, Kitahime, May Queen, Sayaka, Snowden, Snow March, and Toyoshiro) using count-based analysis showed exceptional recognition, with potato misclassification rates of 0.08 ± 0.03% (range: 0.01–0.32%) and impurity detection rates of 89.99 ± 1.25% (range: 80.00–93.30%). Cross-farm validation across seven commercial farms in Hokkaido confirmed robust algorithm consistency (PMR: 0.08 ± 0.03%, IDR: 90.56 ± 0.82%) without farm-specific calibration, establishing variety-independent and environment-independent operation. Field validation using weight-based analysis during actual harvesting at 1–4 km/h confirmed successful AI-to-field translation, with 0.22–0.42% potato misclassification and adaptive impurity removal of 71.43–85.29%. The system adapted intelligently, employing conservative sorting under high-impurity loads (71.43% removal, 0.33% misclassification) to prioritize potato preservation while maximizing efficiency under standard conditions (85.29% removal, 0.30% misclassification). The dual-evaluation framework successfully bridged the gap between AI accuracy in laboratory settings and effectiveness in agricultural operations. The proposed AI algorithm surpassed project targets for all tested conditions (>60% impurity removal, <1% potato misclassification). This successful integration demonstrates technical feasibility and commercial viability for widespread agricultural automation, with a validated 50% reduction in labor (four workers to two workers). This implementation provides a comprehensive validation methodology for next-generation autonomous harvesting systems. Full article

Potatoes intended for chip production must meet strict quality requirements. The objective of the study was to determine the optimal cultivation approach most favorable for chip potato cultivars (Beo, Picus, Pirol) through the application of various agronomic treatments, including a biostimulant and a fungicide. In the fresh tuber mass, the following components were determined: dry matter, starch, total and reducing sugars, as well as carotenoid and chlorophyll pigments. The chips were evaluated in terms of organoleptic traits: color, taste, aroma and consistency. All analyses were carried out directly after harvest and after 6 months of storage under constant temperature (8 °C) and relative air humidity (95%). In general, all experimental factors had a significant effect on the parameters studied. The potato cultivars differed significantly in the chemical composition of their tubers. The cultivar ‘Beo’ was characterized by the highest dry matter and starch content and, at the same time, the lowest content of total and reducing sugars (respectively, : 23.9%, 18.4%, 5.77 g kg⁻¹ f.m., 459 mg kg⁻¹ f.m.). The cultivar ‘Pirol’, on the other hand, contained the highest amounts of carotenoid and chlorophyll pigments (a, b and total): 10.31, 1.87, 0.927, 2.80 mg kg⁻¹ f.m., respectively. The preparations Moncut 460 SC (MC) and Supporter^® (SP) used in potato production showed a positive effect on the chemical composition of the cultivars studied. It was demonstrated that the combined use of both agents proved to be the most beneficial in this regard. The chips produced were characterized by high overall quality, averaging 4.6 points after harvest and 4.5 points after storage, fully meeting the standards required for this type of product. Chips fried from the tubers of the ‘Beo’ cultivar received the highest organoleptic scores: color—4.9, consistency—4.6, and taste—4.6 points. Regardless of the experimental factors, the chips were characterized by a very good aroma (5.0 points). The studies conducted generally demonstrated a positive effect of the potato seed treatments used in cultivation on the individual quality traits of the chips. The combined application of the preparations (MC and SP) generally had a significantly positive effect on the organoleptic characteristics of the chips. After long-term storage, the quality of tubers and chips slightly decreased overall, which indicates that appropriate conditions were maintained throughout the storage period and that proper handling of the tubers immediately after harvest was ensured. Full article

Growing concern about the environmental impact of traditional packaging has driven the development of biodegradable edible films made from natural and functional biopolymers. Various by-products generated during harvesting can be subjected to valorization. Potato, a tuber with high starch content, and carrot, rich in β-carotene, represent important sources of polymeric matrix and bioactive compounds, respectively. Similarly, the use of biodegradable plasticizers such as pectin and polysaccharides derived from nopal mucilage is a viable alternative. This study assessed the physical and chemical properties of edible films composed of potato starch (PS), cactus mucilage (NM), carrot extract (CJ), citrus pectin (P), and glycerin (G). The films were produced by means of casting, with three mixtures prepared that had different proportions of CJ, P, and PS. The experiments were adjusted to a simple mixture design, and the data were analyzed in triplicate, using Pareto and Tukey diagrams at 5% significance. Results showed that adding CJ (between 5 to 6%), P (between 42 to 44%) and PS (between 43 to 45%) significantly affects all of the evaluated physical and chemical properties, resulting in films with luminosity values greater than 88.65, opacity ranging from 0.20 to 0.54 abs/mm, β-carotene content up to 26.11 μg/100 g, acidity between 0.22 and 0.31% and high solubility with a significant difference between treatments (p-value < 0.05) and low water activity (around of 0.47) (p-value > 0.05). These characteristics provide tensile strength up to 5.7 MPa and a suitable permeability of 1.6 × 10⁻² g·mm/h·m²·Pa (p-value < 0.05), which ensures low diffusivity through the film. Similarly, increasing the CJ addition enables the functional groups of the other components to interact. Using carrot extract and potato starch is a promising approach for producing edible films with good functional qualities but with high permeability. Full article