Fruit Surface Research Articles

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.

A sensitive fluorometric-colorimetric dual-mode intelligent sensing platform for the detection of formaldehyde

Excess formaldehyde (FA) is a strong carcinogen, so the development of a rapid visualized and portable formaldehyde detection platform is of great research importance. A multi-color fluorescence sensing system constituted of model compound (NAHN) and red-emitting InP/ZnS QDs was constructed herein, which can simultaneously realize fluorometric-colorimetric dual-mode sensing when exposed to FA environment. Its preparation process was simplified, the detection process was green, and the limits of detection (LOD) were 0.623 μM and 0.791 μM, respectively. The high recoveries of FA in actual water samples indicated that the sensor had broad application prospects. The prepared fluorescent film can be utilized for rapid visual simulation analysis of FA on the surface of various fruits and vegetables. In addition, a serial logic gate was designed to quickly semi-quantitatively assess FA concentration, which promoted the realization of on-site intelligent evaluation of FA.

Tomato plant extract (Lycopersicon esculentum) obtained from agroindustrial byproducts and its antifungal activity against Fusarium spp.

Phytopathogenic fungi are a constant danger in the production of different crops around the world, especially in melons, since they can cause significant economic losses during the harvest, affecting the quality and shelf life. In recent years, producers have increasingly used chemical pesticides indiscriminately, causing environmental problems and damage to public health. For this reason, phytopathogenic fungi become more resistant. However, it is essential to guarantee the safety, quality, and shelf life of food after harvest, during transportation, storage and marketing. The presence of fungi in food can cause diseases transmitted through the production of toxins. Most producers depend on the discriminated use of chemical pesticides, which is a great challenge to guarantee food safety and sustainable agricultural production. To solve this problem, some extracts derived from tomato plants after harvest containing bioactive compounds have been implemented. These compounds can be natural antifungal agents as they contain phenols, flavonoids, and vitamins. Bioactive compounds emerge as a sustainable and safe opportunity in the search for new antifungal and antimicrobial agents. Therefore, the objective of this study was to determine the in vitro antifungal activity of whole tomato plant extracts on three phytopathogenic fungi. The research findings indicated that a concentration of 74.7 μg/mL of TPE resulted in a complete inhibition of mycelial growth in Fusarium oxysporum, Fusarium graminearum, and Fusarium verticillioides. Additionally, TPE exhibited both fungistatic and fungicidal effects on these Fusarium species, with a MIC50 of 30.7, 31.5, and 29.5, and a MFC of 82.4, 78.6, and 75.8 μg/mL, respectively. As a result, this study suggests that TPE can be considered as an environmentally friendly solution for extracting tomato plants, which can be applied to the surface of whole fruits or incorporated into semi-processed foods.

Novel Feature Extraction for Oil Palm Bunches Classification

This paper presents research on an image processing approach for oil palm fruit brunches classification on automating the process of classifying palm fruit brunches based on their visual characteristics, which can have applications in the agriculture and palm oil industry. The research aims to classify the bunches into four categories which are unripe, under ripe, ripe and over ripe. Additionally, this approach can reduce the manual labour involved in palm oil grading and provide a more objective and consistent method for grading the oil. The proposed approach consists of the process of image acquisition, image pre-processing, colour processing, image segmentation and classification. The ripeness of the oil palm fruit bunches is determined based on the percentage of ripeness areas masked on the fruit surface. The proposed algorithms successfully classified the palm oil bunches and improved the accuracy of grading palm oil, achieving 85% accuracy from the experiment results.

Au-coated quartz fabric by plasma treatment as a flexible SERS substrate for rapid detection of harmful substances

Food safety remains a global concern and there is always demanded to advance methods to ensure that toxic substances and contamination do not pose safety concerns. This study discusses the development of a rapid, low-cost, portable, in situ method for the detection of harmful substances on the surface of fruits and vegetables to ensure safety for human consumption. Gold nanoparticles (Au NPs) are deposited onto quartz fabric by using a magnetron sputtering system. The argon flow rate and sputtering time are both controlled to produce Au NPs of different sizes on the quartz fabric with different gap distances. Scanning electron microscope images, X-ray diffraction spectra, and Raman intensity are used to evaluate the produced substrates. With an average grain size of about 32.35 nm, the Au particles with a thickness of 70 nm deposited onto the quartz fabric (i.e., Qt-70) provide the best surface-enhanced Raman scattering (SERS) performance of 65,639 counts towards a 10−3 M methylene blue (MB) solution. The results show that the Qt-70 SERS substrate is highly sensitive, reproducible, and stable, and demonstrates good reusability. Images of “hotspots” that form between two Au nanoparticles based on electric field distribution are simulated by using the finite-difference time-domain (FDTD) method to explain for the signal enhancement. In addition, Qt-70 can be used for the direct collection of pesticides, such as Rhodamine B (RhB), Rhodamine 6G (R6G), and Malachite green (MG), from food surfaces. This novel flexible SERS (FSERS) substrate has good potential for the rapid detection of harmful substances on food.

Occurrence of Alternaria alternata and A. tenuissima causing black rot in cherry fruits (Prunus avium) in Central Chile.

During the harvest of 2020 and 2021, sweet cherry (Prunus avium) fruit showed a firm rot with irregular pale to dark brown lesions on the fruit surface, with green to light brown fungal growth resembling Alternaria-like infection (Simmons, 2007). Diseased cherries (n= 80 fruit) were collected at harvest in mature (over 10-year-old) commercial orchards of cherry tree varieties Lapins, Regina, Santina, Skeena, and Sweetheart planted in four localities of the regions O´Higgins (33°59´ S, 70°42´W; San Francisco de Mostazal and Graneros) and Maule (35°00'S, 71°23´W; Curicó and Sagrada Familia), Central Chile. The incidence of black rot was 1.9 and 3.2% in O´Higgins and Maule region, respectively, and it was increased to up to 5% during cold storage. The fruit collected previously, were transported to the lab, and surface disinfected in 75% ethanol for 15 s, and rinsed in sterile water. Internal pieces from the junction of diseased and healthy tissues of fruits were placed on potato dextrose agar (PDA, 2%) for 7 days at 20°C. Forty-two isolates of Alternaria-like (Simmons, 2007) were recovered consistently from pure cultures taking hyphal tips from 7 days old cultures. On PDA, 28 isolates (group A) were characterized by cottony, white-gray to green colonies and conidial chains (4 to 10 conidia) with secondary chains (1 to 5 conidia) branching on the conidiophore. Conidia were ovate to obclavate (mean 22.8 ± 5.1 x 8.8 ± 1.5 μm; n=40) with 3 to 7 transepta and 1 longisepta. The remaining 14 isolates (group B) were characterized by cottony, olive-green to olive-brown colonies following a ring pattern of growth and white margins, with conidial chains (4 to 14 conidia) and uncommon secondary chains (1 to 4 conidia). Conidia were obpyriform to ovate, light brown to brown with a cylindrical short beak at the tip (mean 24.7 ± 5.9 × 11.2 ± 1.3 μm; n=40) with 2 to 4 transepta, and 0 to 2 longisepta. Two representative isolates of group A (Sant-02-2020 and Bing-03-2020) and group B (Sant-26-2021 and Skeen-43-2021) were amplified for the Alternaria major allergen (Alt a1), plasma membrane ATPase (ATP), and calmodulin (Cal) loci following the protocols described by Hong et al. (2005) and Lawrence et al. (2013). A MegaBlast search of sequences of group A (GenBank nos. OR267293- OR267294, OR258001- OR258002, and OR267297- OR267298, for Alt a1, ATP, and Cal, respectively) showed 100% similarity to strains UCD10529 and UCD10539 of A. alternata, and group B (GenBank nos. OR267295- OR267296, OR258003- OR258004, and OR258005- OR258006, for Alt a1, ATP, and Cal, respectively) showed 100% similarity to strains EGS 34-015 and A30 of A. tenuissima. Combined phylogenetic analysis using MEGA X clustered isolates Sant-02-2020 and Bing-03-2020, and Sant-26-2021 and Skeen-43-2021 with ex-type of A. alternata and A. tenuissima, respectively. Pathogenicity tests were conducted using isolates of A. alternata (Sant-02-2020; Bing-03-2020) and A. tenuissima (Sant-26-2021; Skeen-43-2021). Detached ripe cherry fruit var. Sweetheart (n=40 fruits/isolate) and Regina (n=40 fruits/isolate) were surfaces disinfested (75% ethanol, 30 s), wounded in the middle with a sterile needle (2 mm in depth), and inoculated with 20 μL of conidial suspension (106 conidia/mL). An equal number of healthy cherries (n=40 fruits) treated with sterile water were used as controls. The experiment was repeated once. All inoculated fruit incubated for 7 days at 22°C, developed between 13 ± 2.7 to 23 ± 2.5 mm and 14.1 ± 1.1 to 19 ± 3.6 mm in lesion diameter for A. alternata and A. tenuissima isolates, respectively. Koch´s postulates were fulfilled by 100% reisolation of the causal pathogen from inoculated fruit, and molecular identification of A. alternata and A. tenuissima isolates. Previously, A. alternata has been described as causing rots on cherries in Chile (Acuña 2010), and China (Zhao and Liu, 2012; Ahmad et al., 2020). To our knowledge, this is the first occurrence of cherry black rot caused by A. alternata and A. tenuissima in Central Chile. Epidemiological studies are necessary to develop integrated management of cherry black rot in Central Chile.