Fruit Surface Research Articles

Exfoliation of a Coordination Polymer Based on a Linear π-Conjugated Ligand into an Ultrathin Nanosheet for Glyphosate Sensing.

Owing to the large-scale consumption of pesticides and their potential threats to the environment and human health, the development of sensing materials for pesticides has attracted considerable attention in recent years. In this work, a novel Cd(II)-based coordination polymer (CP) with the formula [Cd(H2O)2(L)]·DMF (Cd-1, DMF = N,N-dimethylformamide, H2L = 4,4'-[(2,5-dimethoxy-1,4-phenylene)di-2,1-ethenediyl]bis-benzoic acid) was synthesized under solvothermal conditions. Structural analysis revealed that coordination between central Cd2+ cations and the ligand L2- formed two-dimensional (2D) networks, which were further assembled by noncovalent hydrogen bonds into a three-dimensional (3D) supramolecular framework. Through ultrasonic treatment in isopropyl alcohol, Cd-1 was exfoliated to afford an ultrathin CP-based 2D nanosheet (Cd-1-NS) with a thickness of less than 1.8 nm. Compared to the bulk materials, the prepared Cd-1-NS exhibited enhanced fluorescence emission properties and superior sensing performance toward glyphosate (Glyph) in water with high selectivity, sensitivity, anti-interference, fast response, and good recyclability via the turn-off effect. The limit of detection (LOD) of Cd-1-NS for Glyph was as low as 41 nM (7 ppb) in the low-concentration range of 0-2.4 μM. In addition, the Cd-1-NS also showed excellent practicability and reliability for the detection of Glyph in real samples, including lake water, tap water, cabbage, and watermelon skin, and could realize the rapid visualized sensing of Glyph residues on the surfaces of vegetables and fruits.

Highly sensitive flexible SERS substrates with a sandwich structure for rapid detection of trace pesticide residues

Compared to rigid surface-enhanced Raman scatting (SERS) substrates, flexible SERS substrates offer significant advantages for the detection of pesticide residues on vegetable and fruit surfaces, primarily due to their convenient sampling process and shorter detection times. However, for paper-based SERS substrates, gold nanoparticles (AuNPs) are easy to form ineffective dispersion in the three-dimensional network structure of paper, resulting in unsatisfactory SERS enhancement. To address this challenge and achieve high-performance flexible SERS substrates, a novel sandwich structure is proposed. Specifically, AuNPs are aggregated on expanded graphite (EG) through a chemical enhancement process facilitated by LiCl. EG is found to improve the adsorption capacity of targeted molecules while preventing signal attenuation caused by filter papers. By employing an aggregating agent at specific concentrations, it is possible to significantly increase the amounts of hot spots to provide a more pronounced enhancement effect. Furthermore, the developed flexible SERS substrates are applied to qualitatively and quantitatively detect pesticide residues, including Thiram, Nitrofural and Dinotefuran. The flexible SERS substrates demonstrate high accuracy and robustness, making them easily storable and suitable for practical applications.

A multi-color fluorescent sensing system integrated with color recognition, liquid crystal display, and voice output module for intelligent detection of two targets

Both tetracycline antibiotics (TC) and Bacillus anthracis are highly resistant to extreme environments. However, there are few studies on the intelligence detection of these two substances by establishing different detection channels. In this research, dual rare-earth coordination polymers were prepared for the detection of Bacillus anthracis and tetracycline. As a unique biomarker of B. anthracis, 2,6-pyridine dicarboxylic acid (DPA) can enhance the green fluorescence emission of Tb3+, achieving a fluorescence change from red to yellowish-green under 282 nm excitation light. Under the excitation light of 395 nm, the TC can coordinate to Eu3+ and sensitize Eu3+ to emit light through the “antenna effect,” thus achieving the fluorescence change from colorless to red. To validate the protocol's applicability in environmental samples, we detected tetracycline and Bacillus anthracis in milk, honey, and tap water. In addition, quick sensing of Bacillus anthracis in soil and tetracycline on the surface of fruits was also achieved by glove-based portable sensors. Furthermore, combined with the color recognition, liquid crystal display, and intelligent voice output system in 51 microcontrollers, it can realize the intelligent and instantaneous detection of various target molecules in real life, which had a wide range of application value and prospects.

Study on the control effect and physiological mechanism of Wickerhamomyces anomalus on primary postharvest diseases of peach fruit

Brown rot, aspergillosis and soft rot are the primary diseases of postharvest peach fruit. Our study aimed to investigate the biocontrol effect of Wickerhamomyces anomalus on the primary postharvest diseases of peach fruit and to explore its underlying physiological mechanism. The findings demonstrated that W. anomalus had an obvious inhibitory effect on Monilinia fructicola, Aspergillus niger and Rhizopus stolonifer. At the same time, W. anomalus can grow stably on the wound and surface of peach fruit at 25 °C and 4 °C and can form biofilm. W. anomalus increased the activity of resistance-related enzymes such as PPO, POD, GLU and the content of secondary metabolites such as total phenols, flavonoids and lignin in peach. Furthermore, the application of W. anomalus led to a reduced MDA level in peach fruit and increased activity of the active oxygen-scavenging enzyme system. This increase involved various antioxidant defense enzymes such as SOD and CAT, as well as ascorbic acid-glutathione (AsA-GSH) enzymes, including APX, GPX, GR, DHAR, and MDHAR. Our findings demonstrate that W. anomalus exerts its biocontrol effect by growing rapidly, competing with pathogens for nutrition and space, and enhancing the disease resistance and antioxidative capabilities of the peach fruit.

Cuticular wax biosynthesis in blueberries (Vaccinium corymbosum L.): Transcript and metabolite changes during ripening and storage affect key fruit quality traits.

In fruits, cuticular waxes affect fruit quality traits such as surface color at harvest and water loss during postharvest storage. This study investigated the transcriptional regulation of cuticular wax deposition in northern highbush blueberries (Vaccinium corymbosum L.) in relation to fruit water loss and surface color during ripening and postharvest storage, as well as the effects of abscisic acid (ABA)-mediated changes in cuticular wax deposition on these fruit quality traits. Total cuticular wax content (μg∙cm-2) decreased during fruit ripening and increased during postharvest storage. Transcriptome analysis revealed a transcript network for cuticular wax deposition in blueberries. Particularly, five OSC-Likes were identified as putative genes for triterpene alcohol production, with OSC-Like1 and OSC-Like2 encoding mixed amyrin synthases, OSC-Like3 encoding a lupeol synthase, and OSC-Like4 and OSC-Like5 encoding cycloartenol synthases. The expression of three CYP716A-like genes correlated to the accumulation of two triterpene acids oleanolic acid and ursolic acid, the major wax compounds in blueberries. Exogenous ABA application induced the expression of triterpenoid biosynthetic genes and the accumulation of β-amyrin and oleanolic acid, as well as increased the ratio of oleanolic acid to ursolic acid. These changes were associated with reduced fruit water loss. The content of β-diketones was also increased by ABA application, and this increase was associated with increased fruit lightness (measured as L* using CIELAB Color Space by a colorimeter). This study provided key insights on the molecular basis of cuticular wax deposition and its implications on fruit quality traits in blueberries.

Green and sustainable self-cleaning flexible SERS base: Utilized for cyclic-detection of residues on apple surface

Advances in flexible SERS substrates has made it possible to approach the ultimate goal of rapid in-situ monitoring of fruit and vegetable safety, but its vulnerability under laser ablation results in low utilization. In order to solve this problem, a 3D framework of TiO2-doped PVDF\\PVP polymer was utilized to self-assemble gold-silver core-shell nanorods (Au@Ag NRs) to prepare a flexible SERS substrate with good physical stability and self-cleaning properties. This substrate showed excellent detection limit and recyclability after the detection of three pesticide residues in apple peel. The LOD of methyl-parathion (MP) was as low as 0.037 ng/cm2, with an RSD of 5.61 % for 5 cycle-detection. The recoveries of two additional pesticides thiram (TMTD) and chlorpyrifos (CPF) were 86.32 %−112.47 %. We hoped that this research will contribute to providing a recyclable and facile method for in-situ analysis of fruit and vegetable surface residues and functional manufacture of flexible SERS substrates.

Análise multirresíduos de pesticidas para determinar a influência do manuseio pós-colheita sobre os níveis de resíduos em mamão

Abstract The objective of this work was to adapt and validate a multiresidue method for pesticide analysis, to determine the influence of the current postharvest handling steps on the degradation of pesticide residues in papaya. 'THB' papaya of the Solo group were sampled at each postharvest handling step in the packinghouse. For the validation of the multiresidue analysis in papaya, the technique used for extraction was the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method, with modifications. Pesticide quantification was carried out using an ultra-high performance liquid chromatograph coupled to a triple quadrupole mass spectrometer with electrospray ionization (UHPLC-MS/MS). Fruit were analyzed before and after the handling procedures and were evaluated after ripening. The used methodology was successfully validated to detect the azoxystrobin, carbendazim, carbofuran, difenoconazole, imazalil, imidacloprid, flutriafol, prochloraz, pyraclostrobin, tebuconazole, thiabendazole, and thiacloprid pesticides in papaya. Fruit washing reduces azoxystrobin and difenoconazole residue levels in 78 to 90% and in 47 to 90% on fruit surface, respectively. Although the postharvest handling steps are ineffective in reducing the levels of thiabendazole, if this fungicide is applied at the appropriate rate, the residue levels will remain below the limits permitted by law.

ИНТЕЛЛЕКТУАЛЬНАЯ АВТОМАТИЗИРОВАННАЯ СИСТЕМА УПРАВЛЕНИЯ СОРТИРОВКОЙ ФРУКТОВ

The development of effective technologies to reduce labor costs for the production, storage and processing of agricultural products is a difficult task. One of the promising directions of increasing the efficiency of technological processes in the agro-industrial complex is the full use of vision systems and artificial intelligence algorithms. Assessment of the quality of crop production is applied at various stages of production and allows detecting its damage, including during sorting. Due to the high productivity of production lines at the facilities of the agro-industrial complex, it seems effective to use intelligent information and control systems operating on the basis of machine learning algorithms. (Research purpose) The research purpose is proposing an approach to the creation of an intelligent automated control system for the fruit picking process using a vision system. (Materials and methods) Considered the structure of the information and control system of fruit sorting using a system of technical vision and machine learning. We implemented the test architecture of the neural network using the Keras library based on the Python language, the research was carried out in the google.collaborate service. A prepared data set based on images obtained on the production line was used to train the neural network. (Results and discussion) The structure of the convolutional neural network architecture was obtained, which allows us to adequately and with a sufficient accuracy solve the problem of classifying fruits into healthy and damaged ones in order to integrate it into an intelligent information and control sorting system. (Conclusions) Proposed an approach to improving the fruit sorting process, for example, for further processing into juice, using a technical vision system and machine learning. The structure of a convolutional neural network was developed to solve the problem of classifying apples by appearance, which became the basis for creating an intelligent information and control system for assessing the area of damage to the surface of fruits.

CucumberAI: Cucumber Fruit Morphology Identification System Based on Artificial Intelligence.

Cucumber is an important vegetable crop that has high nutritional and economic value and is thus favored by consumers worldwide. Exploring an accurate and fast technique for measuring the morphological traits of cucumber fruit could be helpful for improving its breeding efficiency and further refining the development models for pepo fruits. At present, several sets of measurement schemes and standards have been proposed and applied for the characterization of cucumber fruits; however, these manual methods are time-consuming and inefficient. Therefore, in this paper, we propose a cucumber fruit morphological trait identification framework and software called CucumberAI, which combines image processing techniques with deep learning models to efficiently identify up to 51 cucumber features, including 32 newly defined parameters. The proposed tool introduces an algorithm for performing cucumber contour extraction and fruit segmentation based on image processing techniques. The identification framework comprises 6 deep learning models that combine fruit feature recognition rules with MobileNetV2 to construct a decision tree for fruit shape recognition. Additionally, the framework employs U-Net segmentation models for fruit stripe and endocarp segmentation, a MobileNetV2 model for carpel classification, a ResNet50 model for stripe classification and a YOLOv5 model for tumor identification. The relationships between the image-based manual and algorithmic traits are highly correlated, and validation tests were conducted to perform correlation analyses of fruit surface smoothness and roughness, and a fruit appearance cluster analysis was also performed. In brief, CucumberAI offers an efficient approach for extracting and analyzing cucumber phenotypes and provides valuable information for future cucumber genetic improvements.

Fruit Water Stress Index of Apple Measured by Means of Temperature-Annotated 3D Point Cloud.

In applied ecophysiological studies related to global warming and water scarcity, the water status of fruit is of increasing importance in the context of fresh food production. In the present work, a fruit water stress index (FWSI) is introduced for close analysis of the relationship between fruit and air temperatures. A sensor system consisting of light detection and ranging (LiDAR) sensor and thermal camera was employed to remotely analyze apple trees (Malus x domestica Borkh. "Gala") by means of 3D point clouds. After geometric calibration of the sensor system, the temperature values were assigned in the corresponding 3D point cloud to reconstruct a thermal point cloud of the entire canopy. The annotated points belonging to the fruit were segmented, providing annotated fruit point clouds. Such estimated 3D distribution of fruit surface temperature (T Est) was highly correlated to manually recorded reference temperature (r 2 = 0.93). As methodological innovation, based on T Est, the fruit water stress index (FWSI Est) was introduced, potentially providing more detailed information on the fruit compared to the crop water stress index of whole canopy obtained from established 2D thermal imaging. FWSI Est showed low error when compared to manual reference data. Considering in total 302 apples, FWSI Est increased during the season. Additional diel measurements on 50 apples, each at 6 measurements per day (in total 600 apples), were performed in the commercial harvest window. FWSI Est calculated with air temperature plus 5 °C appeared as diel hysteresis. Such diurnal changes of FWSI Est and those throughout fruit development provide a new ecophysiological tool aimed at 3D spatiotemporal fruit analysis and particularly more efficient, capturing more samples, insight in the specific requests of crop management.

Phenotyping 172 strawberry genotypes for water soaking reveals a close relationship with skin water permeance.

Water soaking is a commercially important disorder of field-grown strawberries that is exacerbated by surface wetness and high humidity. The objective was to establish the effect of genotype on susceptibility to water soaking. Three greenhouse-grown model 'collections' were used comprising a total of 172 different genotypes: (1) a segregating F2 population, (2) a collection of strawberry cultivars and breeding clones, and (3) a collection of wild Fragaria species. A standardized immersion assay was used to induce water soaking. Potential relationships between water soaking and water uptake characteristics, depth of the achene depressions, fruit firmness, cuticle mass and strain relaxation and microcracking were investigated. Further, the effect of downregulating the polygalacturonase genes (FaPG1 and FaPG2) on the susceptibility to water soaking was investigated. The collection of wild species was most susceptible to water soaking. This was followed by the collection of cultivars and breeding clones, and by the F2 population. Susceptibility to water soaking was strongly correlated with water uptake rate (mass of water, per fruit, per time). For the pooled dataset of 172 genotypes, 46% of the variability in water soaking was accounted for by the permeance of the skin to osmotic water uptake. Susceptibility to water soaking was not, or was only poorly correlated with measurements of fruit surface area or of the osmotic potential of the expressed fruit juice. The only exceptions were the wild Fragaria species which were highly variable in fruit size and also in fruit osmotic potential. For genotypes from the F2 and the wild species collections, firmer fruit were less susceptible to water soaking than softer fruit. There were no relationships between fruit firmness and susceptibility to water soaking in transgenic plants in which FaPG1 and FaPG2 were down-regulated. Susceptibility to water soaking was not related to cuticle mass per unit fruit surface area, nor to strain relaxation of the cuticle upon isolation, nor to achene position. In summary, strawberry's susceptibility to water soaking has a significant genetic component and is closely and consistently related to the skin's permeance to osmotic water uptake.

Field observations of clear summer day fruit surface temperatures in apple and satsuma mandarin

Field observations of clear summer day fruit surface temperatures in apple and satsuma mandarin

Chemical compositions and cryo-adhesive probing of the epicuticular wax crystals on fruit surface of wax gourd (Benincasa hispida)

Surface wax crystals play important roles in protecting plants from pest and disease invasions, and UV irradiation. The wax crystals are less probed individually from the fruit surfaces. Herein the morphologies, chemicals and an efficient method to sample the wax blooms of white wax gourd were addressed. Various crystalloids such as rodlets, platelets, fragments, and granules were observed, which stacked as fine wax film covering on wax gourd fruit surface. The wax blooms were effectively removed by cryo-adhesive after consecutive manipulating set by a high-end device with cylinders. Wax crystals were dominated by triterpenols and triterpenol acetates over 61 % of total crystals, followed by vey-long-chain aliphatics. Accordingly, the high-end device with cryo-adhesive provides an efficient approach to selectively probe the wax crystals from those fruits covering wax blooms. The elucidation of morphologies and chemical compositions of wax crystals may help to better understand their regulations on fruit quality traits.

Exogenous application of ALA enhanced sugar, acid and aroma qualities in tomato fruit.

The content and proportion of sugars and acids in tomato fruit directly affect its flavor quality. Previous studies have shown that 5-aminolevulinic acid (ALA) could promote fruit ripening and improve its aroma quality. In order to explore the effect of ALA on sugar and acid quality during tomato fruit development, 0, 100, and 200 mg L-1 ALA solutions were sprayed on the fruit surface 10 days after pollination of the fourth inflorescence, and the regulation of ALA on sugar, acid metabolism and flavor quality of tomato fruit was analyzed. The results showed that ALA treatment could enhance the activities of acid invertase (AI), neutral invertase (NI), and sucrose synthase (SS), reduce the activity of sucrose phosphate synthase (SPS), up-regulate the expression of SlAI, SlNI and SlSS, change the composition and content of sugar in tomato fruit at three stages, significantly increase the content of sugars in fruit, and promote the accumulation of sugars into flesh. Secondly, ALA treatments increased the activities of phosphoenolpyruvate carboxykinase (PEPC), malic enzyme (ME), and citrate synthase (CS), up-regulated the expression of SlPPC2, SlME1, and SlCS, and reduced the citric acid content at maturity stage, thereby reducing the total organic acid content. In addition, ALA could also increase the number and mass fraction of volatile components in mature tomato fruits. These results indicated that exogenous application of ALA during tomato fruit development could promote the formation of fruit aroma quality and were also conducive to the formation of fruit sugar and acid quality.

Evidence That Field Muskmelon (Cucumis melo L. var. agrestis Naud.) Fruits Are Solids of Revolution.

In nature, the fruit shapes of many plants resemble avian eggs, a form extensively studied as solids of revolution. Despite this, the hypothesis that egg-shaped fruits are themselves solids of revolution remains unvalidated. To address this, 751 Cucumis melo L. var. agrestis Naud. fruits were photographed, and the two-dimensional (2D) boundary coordinates of each fruit profile were digitized. Then, the explicit Preston equation (EPE), a universal egg-shape model, was used to fit the 2D boundary coordinates to obtain the estimates of the EPE's parameters of each fruit. Under the hypothesis that egg-shaped fruits are solids of revolution, the fruit volumes were estimated using the solid of revolution formula based on the estimated EPE's parameters. To test whether the fruits are solids of revolution, the fruit volumes were measured by using a graduated cylinder and compared with the estimated volumes using the solid of revolution formula. The EPE was demonstrated to be valid in describing the 2D profiles of C. melo var. agrestis fruits. There was a significant correlation between the measured fruit volumes using the graduated cylinder and the estimated fruit volumes using the solid of revolution formula based on the estimated EPE's parameters. Acknowledging potential measurement errors, particularly fruit fuzz causing air bubbles during volume measurements, we recognize slight deviations between measured volumes and estimated values. Despite this, our findings strongly suggest that C. melo var. agrestis fruits are solids of revolution. This study contributes insights into the evolutionary aspects of fruit geometries in plants with egg-shaped fruits and introduces a practical tool for non-destructively calculating fruit volume and surface area based on photographed 2D fruit profiles.

Effect of wax chain length on the adhesion dynamics and interfacial rigidity of Salmonella Typhimurium LT2

The wax layer on the surface of fruits and vegetables is the first line of defense against a range of environmental stresses. The initial stage in the etiology of bacterial foodborne illnesses involves the bacterial adhesion and colonization on the wax layer of food commodities. Herein, we report a systematic study that provides new insights into dynamics of interfacial nanoscale processes associated with the transition of bacteria from a planktonic state to a sessile state at the early stages. To achieve this, we coated a piezoelectric sensor with model waxes containing linear alkyl carbon chains of varying lengths (from 6 to 18 carbons) via chemisorption. The process of bacterial adhesion to these wax-coated sensors was monitored using the Quartz Crystal Microbalance with Dissipation (QCM-D) technique, which offers nanogram-level gravimetric accuracy and millisecond time resolution. Our findings revealed that surfaces with higher hydrophobicity are more susceptible to Salmonella adhesion. Furthermore, we conduct a comparative analysis of the viscoelastic properties of the adhered layer, revealing distinct behaviors: Salmonella adhered to C6-wax exhibited solid-like characteristics, while adherence to C18-wax rendered a more liquid-like response. This observation underscores the role of interfacial energy in governing bacterial adhesion, as interpreted through the thermodynamic and surface science model, ultimately influencing rigidity. This investigation offers valuable insights into the initial adhesion to surfaces and has potential implications for surface design and modification within the food industry and other relevant applications, while also contributing to our understanding of bacterial contamination in food commodities.

Efficacy evaluation of apple sunburn mitigation techniques in WA 38 cultivar using crop physiology sensing system

This study evaluated the efficacy of two heat stress mitigation techniques, i.e., modified evaporative cooling (EC), and drape/shade net (SN) against untreated control (UC) in terms of fruit surface temperature (FST) suppression and internal fruit quality for cv. WA 38. The EC treatment used foggers (flow rate: 4.1 L s−1 ha−1) spaced at 3.3 m along the row to create mist within the canopy. The experiment was conducted in a 0.2 acre block planted on two randomly distributed rootstocks [Geneva 41 (G41) and Malling 9-Nic 29 (M9)], trained in a bi-axis vertical wall architecture. Treatments were divided into three sub-blocks. Alternate wet and dry zones were observed in the sub-block treated with fogger-based EC and was therefore subdivided into EC-Wet and EC-Dry treatments. The proximal thermal-RGB imaging and in-field weather sensing integrated crop physiology sensing system (CPS2.0) was upgraded with edge computing capability to monitor real-time apple FST, an indicator of heat stress. Deployed nodes monitored imagery and weather data based FST in each treatment at an interval of 5-min throughout the growing season (i.e., during fruit maturation). Aerial imagery-based canopy temperature mapping with ground sampling distance of 4 cm/pixel was also utilized to monitor the canopy heat stress at key growth stages. CPS2.0 imagery derived apple FST was effectively reduced by EC-Wet (G41: 27.1 ± 0.4 and M9: 28.8 ± 0.4 °C) (mean ± std. error) and SN (G41: 29.8 ± 0.2 and M9: 30.5 ± 0.1 °C) treatments compared to the UC (G41: 33.1 ± 0.2 and M9: 31.4 ± 0.4 °C) throughout the production season. However, convective cooling from EC-Dry (G41: 33.1 ± 0.2 and M9: 32.5 ± 0.2 °C) treatment failed to mitigate heat stress. Results suggest that fogger spacing, and orientation need adjustments along tree-rows for effective sunburn management. Overall, canopy temperature quantified by aerial imagery was significantly lower under modified EC (30.3 ± 1.3 °C) than UC (34.2 ± 1.3 °C) treatment. Compared to UC, EC-Wet and SN protection enhanced fruit quality with higher or similar crop load, fruit firmness, and quality.

Carotenoid retention during post-harvest storage of Capsicum annuum: the role of the fruit surface structure.

In this study, a chilli pepper (Capsicum annuum) panel for post-harvest carotenoid retention was studied to elucidate underlying mechanisms associated with this commercial trait of interest. Following drying and storage, some lines within the panel had an increase in carotenoids approaching 50% compared with the initial content at the fresh fruit stage. Other lines displayed a 25% loss of carotenoids. The quantitative determination of carotenoid pigments with concurrent cellular analysis indicated that in most cases, pepper fruit with thicker (up to 4-fold) lipid exocarp layers and smooth surfaces exhibit improved carotenoid retention properties. Total cutin monomer content increased in medium/high carotenoid retention fruits and subepidermal cutin deposits were responsible for the difference in exocarp thickness. Cutin biosynthesis and cuticle precursor transport genes were differentially expressed between medium/high and low carotenoid retention genotypes, and this supports the hypothesis that the fruit cuticle can contribute to carotenoid retention. Enzymatic degradation of the cuticle and cell wall suggests that in Capsicum the carotenoids (capsanthin and its esters) are embedded in the lipidic exocarp layer. This was not the case in tomato. Collectively, the data suggest that the fruit cuticle could provide an exploitable resource for the enhancement of fruit quality.

A comprehensive study from the micro- to the nanometric scale: Evaluation of chilling injury in tomato fruit (Solanum lycopersicum)

Tomato fruit is susceptible to chilling injury (CI) during its postharvest handling at low temperature. The symptoms caused by this physiological disorder have been commonly evaluated by visual inspection at a macro-observation scale on fruit surface; however, the structure at deeper scales is also affected by CI. This work aimed to propose a descriptive model of the CI development in tomato tissue under the micro-scale, micro-nano-scale and nano-scale approaches using fractal analysis. For that, quality and fractal parameters were determined. In this sense, light microscopy, Environmental Scanning Electron Microscopy (ESEM) and Atomic Force Microscopy (AFM) were applied to analyse micro-, micro-nano- and nano-scales, respectively. Results showed that the morphology of tomato tissue at the micro-scale level was properly described by the multifractal behaviour. Also, generalised fractal dimension (Dq=0) and texture fractal dimension (FD) of CI-damaged pericarp and cuticle were higher (1.659, 1.601 and 1.746, respectively) in comparison to non-chilled samples (1.606, 1.578 and 1.644, respectively); however, FD was unsuitable to detect morphological changes at the nano-scale. On the other hand, lacunarity represented an appropriate fractal parameter to detect CI symptoms at the nano-scale due to differences observed between damaged and regular ripe tissue (0.044 and 0.025, respectively). The proposed multi-scale approach could improve the understanding of CI as a complex disorder to the development of novel techniques to avoid this postharvest issue at different observation scales.

Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management

Our prior study focused on development of internet of things (IoT) and edge-compute enabled crop physiology sensing system (CPSS) for apple sunburn monitoring. Edge compute algorithm on CPSS estimated sunburn susceptibility as fruit surface temperature (FST) through pixel-by-pixel multiplication of captured thermal infrared images with segmented fruits binary mask. The segmentation was performed using color-based K means clustering approach. This limited CPSS applicability to monitor sunburn of red colored cultivars only and when fruits develop color, typically late growing season. This is a key research gap as recent weather patterns have shown that sunburn can occur during early growing season when fruits are green to yellow. Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. Season long field data were collected in 2021 using eight CPSS nodes (three in cv. WA38 [Cosmic crisp] and five in cv. Honeycrisp). Collected data were used to develop and validate mask R-CNN based fruit segmentation model. Developed mask R-CNN based model was able to segment fruits of two apple cultivars and of varying colors with 91.4 % average precision. In orchard evaluations (2022 season), the resulting algorithm ported on CPSS was able to accurately segment (dice similarity coefficient = 0.89) and estimate apple FST with < 0.5 °C error compared to ground truth data. With compute time of about 37 s, data processing time was reduced by 22 % over previous algorithm. High ambient temperature (>35 °C) on a warmer day resulted in multiple throttling errors caused by excessive CPU temperature; however, the CPSS performance was uncompromised in FST estimation. Ambient air temperature did not affect RAM utilization and CPU clock frequency. Overall, developed FST algorithm can potentially be used as input to actuate water-based cooling system.