Journal articles on the topic 'Apples'
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Bai, Chengwei, and Xiangting Chen. "A Case Study of Apples Success in Marketing Through Big Data Analysis." Advances in Economics, Management and Political Sciences 33, no. 1 (November 10, 2023): 128–31. http://dx.doi.org/10.54254/2754-1169/33/20231647.
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Apple Inc. is one of the most successful technology companies in the world and has been at the forefront of the big data analytics and marketing revolution. The use of big data has become a key element in marketing, and Apple's approach is a good case study for companies seeking to use big data to enhance their marketing strategies. This paper will take it as a case study to discuss how to use big data to promote marketing. This paper will briefly introduce Apple and the concept of big data and marketing, then analyze how Apple applies big data to analyze the market, discuss Apples successful cases in marketing, and summarize Apples marketing strategies. A conclusion will be drawn at the end.
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Tang, Chun Xiao, En Bang Li, Chuan Zhen Zhao, and Chao Li. "Quality Detection and Specie Identification of Apples Based on Multi-Spectral Imaging." Advanced Materials Research 301-303 (July 2011): 158–64. http://dx.doi.org/10.4028/www.scientific.net/amr.301-303.158.
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This paper introduced an apple quality detection and specie identification system based on multi-spectral imaging. Under an international mixed light illumining, system can capture red, green and infrared images of apples at the same time. A software programmed based on Matlab 6.5.1 is used for image processing to complete the detection of quality and specie. According to processing results, the subtotals and classification are made into grading standards. These can be quickly and easily applied to the automation of agriculture fruit grading system. In the experiment, some most common apples including Fuji apple, Red delicious apples, Green apples, Gina Apple's were detected for quality and variety . Accuracy rate can be more than 90%.
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Jiao, Yuhua, Rong Luo, Qianwen Li, Xiaobo Deng, Xiang Yin, Chengzhi Ruan, and Weikuan Jia. "Detection and Localization of Overlapped Fruits Application in an Apple Harvesting Robot." Electronics 9, no. 6 (June 21, 2020): 1023. http://dx.doi.org/10.3390/electronics9061023.
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For yield measurement of an apple orchard or the mechanical harvesting of apples, there needs to be accurate identification of the target apple fruit. However, in a natural scene, affected by the apple’s growth posture and camera position, there are many kinds of apple images, such as overlapped apples; mutual shadows or leaves; stems; etc. It is a challenge to accurately locate overlapped apples. They will influence the positioning time and recognition efficiency and then affect the harvesting efficiency of apple-harvesting robots or the accuracy of orchard yield measurement. In response to this problem, an overlapped circle positioning method based on local maxima is proposed. First, the apple image is transformed into the Lab color space and segmented by the K-means algorithm. Second, some morphological processes, like erosion and dilation, are implemented to abstract the outline of the apples. Then image points are divided into central points; edge points; or outer points. Third, a fast algorithm is used to calculate every internal point’s minimum distance from the edge. Then, the centers of the apples are obtained by finding the maxima among these distances. Last, the radii are acquired by figuring out the minimum distance between the center and the edge. Thus, positioning is achieved. Experimental results showed that this method can locate overlapped apples accurately and quickly when the apple contour was complete; and this has certain practicability.
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Relawati, Rahayu, Masyhuri Masyhuri, Lestari Rahayu Waluyati, and Jangkung Handoyo Mulyo. "The Important Attributes of Local and Imported Apple : A Factor Analysis Application." Agro Ekonomi 28, no. 1 (June 28, 2017): 1. http://dx.doi.org/10.22146/jae.22658.
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This study aims to find the important attributes of local and imported apple. A consumer survey was conducted in Java Island representated by four big cities: Malang, Surabaya, Yogyakarta, and Bandung. Three categories of purchasing place at each city are supermarket, fruit stall and traditional market. Accidental sampling was done to choose the samples of consumer. The total respondents interviewed was 240 consumers consisting of 120 for each attribute. The data of apple attributes and purchasing place were analyzed by exploratory factor analysis supported by SPSS software. The result suggests that the important quality attributes of local and imported apples are grouped in each two latent factors namely quality and cultivar. Meanwhile, purchasing place is grouped in one latent factor. All quality attributes of local and imported apples have positive correlation with the apple quality, but there is a different fi nding in which apple flavor of local and imported apples are not the most important attribute that ranked fi rst based on consumer assessment. The factor of apple cultivar always associates with the apple size, both on local and imported apples. Rome Beauty (local apple) and Fuji (imported apple) have greater average size than other cultivars. Thus, these attributes are already attached one another. The factor of purchasing place becomes an important part which accompanies the apple’s quality attributes and is considered by consumers in purchasing apple.
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Ningrum, Tri Widya, and Lagiono Lagiono. "DESKRIPSI FORMALIN PADA APEL DAN ANGGUR IMPORT DI KIOS BUAH DI EX KOTATIF PURWOKERTO KABUPATEN BANYUMAS TAHUN 2014." Buletin Keslingmas 34, no. 1 (March 31, 2015): 54–62. http://dx.doi.org/10.31983/keslingmas.v34i1.3023.
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Food is every biological, animalistic, processed or unprocessed for human drinking and feedingconsumption including food additive feeding material and other material for savingprocess, or drinking. Formalin is chemical efficient substance but, forbid to food additive, generallyformalin used in textile industry to avoid textile tangled. The goal of this research to known fruit quality(organoleptic) fruit peel, fruit color and fruit flavors in general and to know thereis or now formalin incontamination in import apples and grapes sold at ex kotatif Purwokerto market.This Resecearher of observation method description it was mean to descript import appes andgrapes quality(organoleptic) generally and to know containing formalin at apples and grapes sold in exkotatif Purwokerto year of 2014.Labratorium examining in samples from import apples and grapes, the sample containing formalinpositive were 11 sample those are American grape was 0,218 ppm, Apples Red Delicious code B 1,406ppm, American grape, Apple Red Delicious Code C was 2,463 ppm, Australion grape was 0,167 ppm,Apple Fuji was 2,063 ppm, Apple Red Delicious was 2,049ppm ( Code D), Apple Fuji was 4,73 ppm,Australion grape was 0,204 ppm, Apples Red Delicious was 5,011 ppm ( Code E). And others fruit(Apple and Grape) was not formalin containing.Generally in apple import Fuji, RD, and GS and grape import Australion and American for sample 5all of them was good. So it is resecearher recommence to apply from health department safety foodquality and food nutrition come to Purwokerto town is like explained in government regulation number28th 2004.
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Tussaadah, S. K. A., W. Dinarto, and D. Astriani. "Effect of essential oil type and immersion time on Manalagi apple fruit storability." IOP Conference Series: Earth and Environmental Science 1182, no. 1 (June 1, 2023): 012061. http://dx.doi.org/10.1088/1755-1315/1182/1/012061.
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Abstract Manalagi apples are easily damaged fruits, so fruit storability is relatively short and yield loss will be high if not handled properly after harvest. This study aims to determine the essential oil type and immersion time that are best for maintaining the storability of Manalagi apple fruit. This study was a factorial experiment arranged in a completely randomized design with three replications. The first factor, essential oil type, consists of three types: citronella oil, coconut oil, and sesame oil. The second factor, immersion time, consists of three levels: 5, 10, and 15 seconds. The additives used to make the emulsion were 1% Tween 80, 0.5% oleic acid, and 3% alcohol. Control without coating treatment. The results showed that apple coating with citronella oil with an immersion time of 5 seconds was the best treatment to maintain the Manalagi apple’s storability for 31 days of storage. The weight loss of apples dipped in citronella oil was lower, and the preference level of the panelists was higher than that of apples dipped in coconut or sesame oil. Manalagi apples that are coated with essential oil have better storability than apples that are not coated.
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Zheng, Junwen, Yuhui Zhang, and Ying Wang. "Research on apple detection and maturity assessment based on computer vision technology." Highlights in Science, Engineering and Technology 101 (May 20, 2024): 423–31. http://dx.doi.org/10.54097/vysbg371.
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The study is based on computer vision technology for apple detection and maturity assessment. Firstly, the YOLOv7 algorithm is used for target detection of apples, and the number of apples in the image is counted to generate a distribution histogram of the number of apples. Then, the position of each apple is detected by the YOLOv7 algorithm and a 2D scatter plot of the geometric coordinates of the apples is drawn. Next, apple foreground was extracted by interactive ROI tagging and GrabCut algorithms, and a mathematical model was developed to assess the maturity of apples based on the histogram analysis of apple colours in HSV colour space model. In addition, the Faster R-CNN model is used to detect apples and estimate the quality of apples based on the 2D area of apples to generate a distribution histogram of apple quality. Finally, a convolutional neural network is used to build a fruit recognition model and draw a distribution histogram of apple image ID numbers. This study provides computer vision technical support for apple picking robots to improve apple production efficiency.
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Wu, Xiefan. "Research on Apple Inc. Market Winning Case Study." Advances in Economics, Management and Political Sciences 24, no. 1 (September 13, 2023): 130–36. http://dx.doi.org/10.54254/2754-1169/24/20230425.
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Apple Inc. is currently a cutting-edge company in the field of technology, and its released products occupy most of the market share in the respective fields. Therefore, aiming at the reasons for Apple's success and its future development direction, this article literature review SWOT analysis to analyze and discuss the reasons for Apples success. Apples success basically lies its innovation, improvement of consumer service, and reform of supply chain management. However, in the future, Apple should consider maintaining its innovation speed and avoiding expanding its service into a large number of irrelevant markets, thereby increasing service and management risk.
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Kierczyńska, Sylwia. "DETERMINANTS OF PURCHASE PRICES OF APPLES FOR PROCESSING IN POLAND." Annals of the Polish Association of Agricultural and Agribusiness Economists XXV, no. 4 (November 20, 2023): 167–80. http://dx.doi.org/10.5604/01.3001.0054.0102.
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The aim of the study was to identify the significant determinants of the level of purchase prices of apples for processing in Poland. The subject of the research is purchase prices of apples for processing published in the semi-annual Fruit and Vegetable Market by the Institute of Agricultural and Food Economics – National Research Institute. The study showed that the purchase prices of apples for processing in Poland were significantly influenced by the export prices of apples, the volume of the export of concentrated apple juice, and the export prices of concentrated apple juice. The increase in the export prices of apples may be caused by the growing demand for Polish apples on foreign markets, which may result in lower availability of apples for processing. Therefore, the increase in the export prices of apples was accompanied by the increase in the purchase prices of these fruits for processing. The volume of export of concentrated apple juice depends on the volume of production of this processed product, which is influenced by the volume of apples harvested in Poland. The volume of apples harvested is negatively correlated with the purchase prices of apples for processing. Therefore, the increase in the export of concentrated apple juice was accompanied by relatively low purchase prices of apples for processing. The level of export prices of concentrated apple juice was strongly related to the level of purchase prices of apples for processing and the increase of purchase prices of apples was accompanied by an increase in export prices of concentrated apple juice.
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Lutfi, Moch, Hasan Syaiful Rizal, Mochammad Hasyim, Muhammad Faishol Amrulloh, and Zulfatun Nikmatus Saadah. "Feature Extraction and Naïve Bayes Algorithm for Defect Classification of Manalagi Apples." Journal of Physics: Conference Series 2394, no. 1 (December 1, 2022): 012014. http://dx.doi.org/10.1088/1742-6596/2394/1/012014.
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Abstract Apple is one of the trees that is widely cultivated and grows in subtropical areas. In Indonesia, there are many areas that cultivate apples, including Malang, Batu, Nongkojajar. One way to increase the economic value of apple farmers is by sorting them before sending them to the market. This is important to do in order to make it easier to determine the quality and selling price of manalagi apples. Most apple sellers will sort the apples manually which results in high costs, difficulty, and inconsistency in the sorting process. So far, the classification of defects in apples has been done using the naked eye. This also requires expertise or experts in distinguishing which apple defects are. However, experts have limitations, not all apple defects can be recognized or classified. In addition, each researcher only uses one image feature, namely the texture feature. In this study, using an image dataset of Manalagi apples totaling 337 images, where there are 184 images of good apples and 153 images of defective apples by extracting features on apples, it can be concluded that the nave Bayes method can be used to classify defects of manalagi apples based on texture.
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Wang, Ya Liang, Shi Ming Ji, Li Zhang, Yong Chen, and Y. Zhang. "Research on the Apple Non-Destructive Selection Technology Based on the Fuzzy Arithmetic." Advanced Materials Research 69-70 (May 2009): 705–9. http://dx.doi.org/10.4028/www.scientific.net/amr.69-70.705.
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This paper studies mainly apples non-destructive selection technology, and presents the principle and implementation of non-destructive selection system for apple quality based on the theory of the fuzzy and neural network. Firstly, we can differentiate the kinds of apples by neural network theory. Then, the apple’s quality greatly depends on its size, shape, and color, which are considered as three input parameters in selection system. The pick-up of three character parameters is handled by computer image processing. Only one output parameter is apple rating, which is fall into three grades: A, B and C. Regarding three character parameters as input, we obtain the apple grade based on fuzzy arithmetic. Finally, we set forth the archetypal non-destructive selection system, which includes robot, AGV, conveyor, sensors and etc. Results of experiments show that this method can distinguish the apple’s quality as well as we set before the experiments, and the non-destructive system is feasible.
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Isenberg, Steven F., and Michael G. Stewart. "Practice Management Committee: Benchmarking Apples to Apples in the Big Apple." Otolaryngology–Head and Neck Surgery 131, no. 2 (August 2004): P133. http://dx.doi.org/10.1016/j.otohns.2004.06.224.
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Saikia, Deepanka, Radhakrishnan Kesavan, Baskaran Stephen Inbaraj, Praveen Kumar Dikkala, Prakash Kumar Nayak, and Kandi Sridhar. "Bioactive Compounds and Health-Promoting Properties of Elephant Apple (Dillenia indica L.): A Comprehensive Review." Foods 12, no. 16 (August 8, 2023): 2993. http://dx.doi.org/10.3390/foods12162993.
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Elephant apple (Dillenia indica L.) grows wild in Southeast Asia’s forests, including in China, India, Nepal, Bangladesh, and Sri Lanka. Elephant apples are considered essential fruit crops because of their high nutritional value, which includes high levels of vitamin C, carbohydrates, fats, fibre, protein, minerals, and fatty acids. It is important to understand the nutritional value and health benefits of elephant apples in order to increase fruit intake in people’s daily diets. The present review paper focuses on elephant apple’s phytochemistry, bioactive compounds, therapeutic value, and medicinal capabilities for designing and developing a wide range of food formulations. Proteins, minerals, fats, crude fibre, carbohydrates, vitamin C, tannins, malic acid, and glucose are abundant in the leaves, bark, and fruit of the elephant apple. In addition to nutritional components, many phytochemicals found in elephant apples have been identified as bioactive compounds with a broad range of biological activities, the most prominent of which are antioxidant, anticancer, antidiabetic, and anti-inflammatory properties. Overall, elephant apple is a rich, natural source of bioactive compounds with potential applications in the production of value-added foods and nutraceuticals for disease prevention and management.
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SALAZAR, JOELLE K., CHRISTINA K. CARSTENS, VRIDDI M. BATHIJA, SARTAJ S. NARULA, MICKEY PARISH, and MARY LOU TORTORELLO. "Fate of Listeria monocytogenes in Fresh Apples and Caramel Apples." Journal of Food Protection 79, no. 5 (May 1, 2016): 696–702. http://dx.doi.org/10.4315/0362-028x.jfp-15-442.
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ABSTRACT An outbreak of listeriosis in late 2014 and early 2015 associated with caramel apples led to questions about how this product became a vector for Listeria monocytogenes. This investigation aimed to determine information about the survival and growth of L. monocytogenes in both fresh apples and caramel apples, specifically examining the effects of site and level of inoculation, inoculum drying conditions, and storage temperature. At a high inoculation level (7 log CFU per apple), L. monocytogenes inoculated at the stem end proliferated on Gala caramel apples at both 5 and 25°C and on Granny Smith caramel apples at 25°C by as much as 3 to 5 log CFU per apple. Fresh apples and caramel apples inoculated at the equatorial surface supported survival but not growth of the pathogen. Growth rates (μmax) for apples inoculated at the stem end, as determined using the Baranyi and Roberts growth model, were 1.64 ± 0.27 and 1.38 ± 0.20 log CFU per apple per day for Gala and Granny Smith caramel apples, respectively, stored at 25°C. At a low inoculation level (3 log CFU per apple), L. monocytogenes inoculated at the stem end and the equatorial surface survived but did not grow on fresh Gala and Granny Smith apples stored at 25°C for 49 days; however, on caramel apples inoculated at the stem end, L. monocytogenes had significant growth under the same conditions. Although certain conditions did not support growth, the pathogen was always detectable by enrichment culture. The inoculation procedure had a significant effect on results; when the inoculum was allowed to dry for 24 h at 5°C, growth was significantly slowed compared with inoculum allowed to dry for 2 h at 25°C. Variation in stick materials did affect L. monocytogenes survival, but these differences were diminished once sticks were placed into caramel apples.
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Cliff, Margaret, Katherine Sanford, Wendy Wismer, and Cheryl Hampson. "Use of Digital Images for Evaluation of Factors Responsible for Visual Preference of Apples by Consumers." HortScience 37, no. 7 (December 2002): 1127–31. http://dx.doi.org/10.21273/hortsci.37.7.1127.
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This research used digital images to explore some of the factors responsible for consumer preference of visual characteristics of apples (Malus ×domestica Borkh.). The images systematically varied in color and shape (Expt. A: 9 images) and type, shape, and background color (Expt. B: 10 images), while keeping apple size constant. Visual assessments of the apple images were collected from 144 consumers (Expt. A) and 165 consumers (Expt. B) in British Columbia (BC), Nova Scotia (NS), and New Zealand (NZ) using balanced incomplete block designs. Canadian consumers (BC and NS) preferred red apples over green or yellow. NZ consumers liked equally red and green apples, and preferred both to yellow apples. At all locations, consumers in Expt. A significantly preferred round and conical shaped apples to oblong apples. When the combined effects of type, shape, and background color were evaluated, NZ consumers rated the striped, round apples the highest, and least preferred both round and oblong, blush-type apples with yellow backgrounds. NS consumers tended to prefer blush apples regardless of type and background color, and BC consumers were more accepting of a range of apple types, shapes, and background colors.
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Guo, Zhiming, Xuan Chen, Yiyin Zhang, Chanjun Sun, Heera Jayan, Usman Majeed, Nicholas J. Watson, and Xiaobo Zou. "Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms." Foods 13, no. 11 (May 28, 2024): 1698. http://dx.doi.org/10.3390/foods13111698.
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Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.
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Liu, Weihui, Yanan Han, Na Wang, Zhen Zhang, Qingguo Wang, and Yongping Miao. "Apple sugar content non-destructive detection device based on near-infrared multi-characteristic wavelength." Journal of Physics: Conference Series 2221, no. 1 (May 1, 2022): 012012. http://dx.doi.org/10.1088/1742-6596/2221/1/012012.
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Abstract Knowing the sugar content of apples in time and grading the internal quality of apples can meet the requirements of different consumers for apples. In this paper, Yantai Red Fuji apples are used as the research object, a low-cost and portable non-destructive testing device for apple sugar content is designed based on near-infrared detection technology. To realize the quantitative detection of apple sugar content, The relationship between the voltage value of diffuse reflection light and the sugar content of apples at multiple characteristic wavelengths is studied, and the multiple linear regression method is used to establish the apple sugar content prediction model. The correlation coefficient predicted by the model is 0.7708, and the minimum relative error is 0.89%. The experimental results show that within a certain error range, the device can realize fast and non-destructive detection of the sugar content of apples. This article provides a reference for the realization of a low-cost, portable non-destructive testing device for Apple.
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Dolgor, Z., and D. Undarmaa. "Fruit brown rot disease of apples imported to Mongolia." Mongolian Journal of Agricultural Sciences 11, no. 2 (November 24, 2014): 68–72. http://dx.doi.org/10.5564/mjas.v11i2.220.
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Mongolia has imported 3094.8 tones apple from China, 318 tones apple from Russia and 140.8 tones from USA for in average for 2010-2011 and regarding to imported apples, 25% brown rot disease infection, 9.8% apple scab, 1.8% mixed infection of brown rot and scab, 1,8% bacterial spotted disease infection and 10% non-infectious disease symptoms were described within study period.The brown rot of apple fruit is occupied 37-41% in the imported apples from China, 12-19% in the imported apples from USA and 11-29% in the imported apples from Russia, hereof the imported apples from China, the main importer country for apples, has the highest indication on the fruit brown rot disease.According to pathogen identification of apple brown rot disease, which are described as Monilinia fructicola- species that was a cause of the fruit brown rot was widely spread on imported apples. M. fructicola species’s cultural characters are described as follows: tan colourred, dry, course and ringed colony on prune extract agar medium (upper surface of plate), its colony growth 9.9-17mm. Colony shape is margin entire and sporulation was abundant. Its conidial diamensions 6.06-12.29 μm x 4.85-8.2 μm were measured. DOI: http://dx.doi.org/10.5564/mjas.v11i2.220 Mongolian Journal of Agricultural Sciences Vol.11(2) 2013 pp.68-72
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Bianzino, Aruna Prem, Anand Kishore Raju, and Dario Rossi. "Apples-to-apples." ACM SIGMETRICS Performance Evaluation Review 38, no. 3 (January 3, 2011): 81–85. http://dx.doi.org/10.1145/1925019.1925036.
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Dunton, Nancy, Megan Twait, Jan Davidson, Angela Christopher, and Neha Sharma. "Apples to apples." Nursing Management (Springhouse) 39, no. 8 (August 2008): 16–20. http://dx.doi.org/10.1097/01.numa.0000333718.65486.5a.
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Potters, Louis. "Apples to apples." Brachytherapy 10, no. 1 (January 2011): 15. http://dx.doi.org/10.1016/j.brachy.2010.02.009.
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Rupasinghe*, H. P. Vasantha, Dennis P. Murr, Jennifer R. DeEll, and Joseph Odumeru. "Effect of 1-MCP and NatureSeal™ on Fresh-cut Apple." HortScience 39, no. 4 (July 2004): 829C—829. http://dx.doi.org/10.21273/hortsci.39.4.829c.
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Wounding during processing triggers physiological reactions that limits shelf-life of fresh-cut apples. Exposure of `Empire' and `Crispin' apples at harvest to the ethylene antagonist 1-methylcyclopropene (1-MCP, SmartFresh™) on the maintenance of fresh-cut apple quality was evaluated in combination with post-cut dipping of NatureSeal™. Efficacy of 1-MCP on fresh-cut physiology and quality depended on the storage duration and apple cultivar. Ethylene production and respiration of apple slices were inhibited by 1-MCP but not by NatureSeal. Total volatiles produced by fresh-cut apples was not affected by the treatments. 1-MCP influenced the quality attributes of fresh-cut apple slices prepared from apples stored either 4 months in cold storage or 6 months in controlled atmosphere. Enzymatic browning and softening of the cut-surface, total soluble solids, and total microbial growth were suppressed by 1-MCP in `Empire' apples. Overall, the influence of 1-MCP on quality attributes in `Crispin' apple slices was marginal. NatureSeal consistently maintained the firmness of fresh-cut apple slices held at 4 °C for up to 21 days. The additive effect of 1-MCP in the maintenance of apple quality is an advantage for processing and marketing of fresh-cut apples.
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Kravchuk, O. P., V. I. Medvedev, A. P. Hrynko, O. M. Bahatska, L. P. Ivanova, H. V. Zvarych, and V. I. Lyshavsky. "Study of residual amounts of flonicamide in apples and justification of medical and sanitary standards for the safe use of insecticide based on it." One Health and Nutrition Problems of Ukraine 59, no. 2 (December 29, 2023): 15–24. http://dx.doi.org/10.33273/2663-9726-2023-59-2-15-24.
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Flonicamid is a new systemic pyridine carboxamide insecticide with selective activity against a wide range of insects on various agricultural crops. In Ukraine, field tests were conducted to justify the possibility of its safe use for the protection of apple trees. Materials and Methods. The content dynamics of flonicamid residual amounts in apples and apple juice was studied in the steppe zone of Ukraine during two growing seasons of 2019-2020 with three times of insecticide use with a consumption rate of 0.07 kg/ha. The residual amounts of flonicamid in apples and apple juice were determined by high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection. The limits of quantitative determination (LQ) by HPLC in apples and apple juice are 0.01 mg/kg. Results. During the research period 2019-2020, the amount of flonicamid in the yield of apples and juice from them (as the sum of flonicamid and TFNA and TFNG metabolites in terms of flonicamid) was 0.019-0.071 mg/kg and 0.017-0.032 mg/kg, respectively. After applying the insecticide, the recommended waiting period before harvesting apples is 35 days. The decrease in the flonicamid content in apples occurs on an exponential curve in accordance with the first-order kinetic equation. The calculated half-life (T50) for apples is 23 days for flonicamid, and 27 days for flonicamid (as the sum of flonicamid and TFNA and TFNG metabolites in terms of flonicamid). The possible daily intake of flonicamid in the human body with apples and apple juice is 9.5% of the level of safe intake with the diet (6.6% of its permissible daily intake). The maximum permissible levels of flonicamid content are justified: apples – 0.3 (the sum of flonicamid and TFNA and TFNG metabolites in terms of flonicamid, (LQ by HPLC – 0.01 mg/kg for each compound); apple juice – 0.03 mg / kg (the sum of flonicamid and TFNA and TFNG metabolites in terms of flonicamid. Conclusions. Flonicamid belongs to the hazard class 2 pesticides in terms of degradation in apple trees. The MPL-approved safe content of the active substance in apples and apple juice and the waiting period before harvesting ensure the safety of using a flonicamid-based insecticide. Keywords: flonicamid, residual amounts, chromatography, field tests.
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Li, Wenfeng, Yulin Yuan, Shikang Hu, Mei Li, Wenxiu Feng, and Jiaxin Zheng. "Positioning of Apple’s Growth Cycle Based on Pattern Recognition." Mobile Information Systems 2021 (May 18, 2021): 1–11. http://dx.doi.org/10.1155/2021/9687950.
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The positioning of the apple growth cycle plays a very important role in predicting the development of apples and guiding fruit farmers in agricultural operations. The traditional method of manually positioning the apple growth cycle has problems such as low efficiency and poor accuracy. Pattern recognition provides support for continuous and rapid positioning during the apple growth process. Under the natural conditions of the orchard, due to the large differences in the individual colors of the apples during the growth process and the influence of factors such as light changes, the photographed apple images are more complex, which brings certain difficulties to the segmentation and recognition of the apples. In this paper, pattern recognition is used to automatically identify and extract the growth stages of apples, a hue intensity (HI) color segmentation algorithm based on a Gaussian distribution model based on prior knowledge is studied, and then an active shape model (ASM) is used to identify each period of apple growth based on pattern recognition. After a series of experimental verifications, the ASM-based automatic identification method proposed in this paper is feasible and can identify the various growth periods of apples, thereby serving the mechanized production of apples.
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Luo, Tongyun, Jianguo Zhou, Shuo Zhang, Jun Chen, Guangrui Hu, and Adilet Sugirbay. "Theoretical Analysis and Experimental Research on the Apple Auto-Orientation Based on Flexible Roller." Horticulturae 9, no. 11 (November 16, 2023): 1235. http://dx.doi.org/10.3390/horticulturae9111235.
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After automatic in-field picking, apple stem shortening requires fixing the apple position and maintaining a relatively stable posture, which puts high demands on the automatic apple-orienting structure. In this paper, a novel dual roller compact apple field orientation structure with dual rollers rotating in the same direction is proposed. It can realize the uniform orientation of apples after automatic picking in any attitude, and the apple auto-orientation phenomenon is theoretically analyzed based on the accurately established apple model, then the apple orientation test platform was set up and a monocular camera combined with YOLOv5m was used to determine the time of apple orientation. The results showed that 70.21% and 96.81% of the apples were respectively oriented within 7 s and 28 s with only two flexible rollers rotating in the corresponding direction. All the apples were oriented, and 95.24% of them moved along the axis toward the calyx end. The generalizability of the apple orientation device for different shapes of apples was then verified, and the relationship between the shape characteristics of apples and orientation speed was later illustrated. A structural basis was finally presented for automatic stem shortening and surface damage detection in the apple field.
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Catana, Monica, Luminita Catana, Enuta Iorga, Alina Culetu, Valentin Ionescu, and Nastasia Belc. "Assessment of the Thermal Stability of Patulin in Apple Puree and of Possibilities for Reduction of Patulin Contamination Level Through Apple Processing." Revista de Chimie 69, no. 4 (May 15, 2018): 809–14. http://dx.doi.org/10.37358/rc.18.4.6206.
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Apples are an important raw material for the production of puree, nectar, jam, and a widely used ingredient in composition of pastry products. Patulin is a mycotoxin that appears in moldy apples, especially, attacked by Penicillium, Aspergillus and Byssochlamys. This study aimed to evaluate the thermal stability of patulin in apple puree and the possibilities to reduce the patulin contamination level through processing apples to apple puree and nectar. Within the experiments, samples of apple puree from Jonathan apple cultivar, spiked with patulin at four concentration levels (10 mg/kg, 20 mg/kg 40 mg/kg and 80 mg/kg) were heat treated at 100 �C for 10, 15, 20 and 25 min, respectively. It was found a reduction of the patulin level, due to the thermal degradation of this mycotoxin. Apples from Golden Delicious cultivar, attacked by Penicillium expansum and contaminated with native patulin were processed to puree and nectar. Through processing of apples contaminated with patulin it was registered an important decrease of it.
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Authoria, Nila, Lilik Wijayanti, and Ratih Puspita Febrinasari. "Differences of Quercetin Content in Fresh and Extracts Local Apples using High Performance Liquid Chromatography Method." Journal of Healthcare and Biomedical Science 1, no. 1 (February 20, 2023): 24–35. http://dx.doi.org/10.31098/jhbs.v1i1.1369.
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Background : Oxidative stress is an imbalance between pro-oxidants and endogenous antioxidants resulting in cell damage and degenerative diseases. As horticultural commodities, apples have superior varieties of Manalagi and Romebeauty. Apples contain exogenous antioxidants, namely quercetin that effectively contributes to the management of oxidative stress. Purpose : The study used laboratory experimental methods to determine differences in quercetin content in fresh apples and apple extracts of Manalagi and Romebeauty. Research methodology : Determination of quercetin content of fresh apples and apple extract used the High Performance Liquid Chromatograph (HPLC) method. The samples used were fresh apples and apple viscous extract of Manalagi and Romebeauty obtained respectively from UPT Medika Material Laboratory of Batu City and Food Engineering Laboratory of Soegijapranata Catholic University Semarang using maceration process with ethanol solvent.Findings : The results showed that the average levels of quercetin in fresh apples of Manalagi and Romebeauty varieties were 13,685 ppm and 15,544 ppm respectively. Extraction of 70% ethanol from 100 grams of Manalagi and Romebeaty varieties resulted in 38.123 grams and 52.699 grams of thick extract. The average levels of quercetin in Manalagi and Romebeauty extracts were 422.235 ppm and 243.454 ppm. It can be concluded that the extract can optimize the quercetin content. Research limitations : The quercetin content in local apple extracts of Manalagi and Romebeauty can be used as an alternative to antioxidant therapy due to oxidative stress. Originality/value : Analyzing differences in quercetin content in fresh apples and apple extracts.
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Howill, Angus J., and Alan R. Hays. "Apples, White Apple Leafhopper Test, 1985." Insecticide and Acaricide Tests 11, no. 1 (January 1, 1986): 38. http://dx.doi.org/10.1093/iat/11.1.38.
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Abstract Treatments consisted of single trees replicated 4 times. Materials were applied by handgun dilute on 14 Aug 1985. Evaluations involved a single precount in which nymphs were counted on 25 leaves for each replication. After treatment counts were made at 2 intervals using the same procedure.
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Liang, Xiaoting, Xueying Jia, Wenqian Huang, Xin He, Lianjie Li, Shuxiang Fan, Jiangbo Li, Chunjiang Zhao, and Chi Zhang. "Real-Time Grading of Defect Apples Using Semantic Segmentation Combination with a Pruned YOLO V4 Network." Foods 11, no. 19 (October 10, 2022): 3150. http://dx.doi.org/10.3390/foods11193150.
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At present, the apple grading system usually conveys apples by a belt or rollers. This usually leads to low hardness or expensive fruits being bruised, resulting in economic losses. In order to realize real-time detection and classification of high-quality apples, separate fruit trays were designed to convey apples and used to prevent apples from being bruised during image acquisition. A semantic segmentation method based on the BiSeNet V2 deep learning network was proposed to segment the defective parts of defective apples. BiSeNet V2 for apple defect detection obtained a slightly better result in MPA with a value of 99.66%, which was 0.14 and 0.19 percentage points higher than DAnet and Unet, respectively. A model pruning method was used to optimize the structure of the YOLO V4 network. The detection accuracy of defect regions in apple images was further improved by the pruned YOLO V4 network. Then, a surface mapping method between the defect area in apple images and the actual defect area was proposed to accurately calculate the defect area. Finally, apples on separate fruit trays were sorted according to the number and area of defects in the apple images. The experimental results showed that the average accuracy of apple classification was 92.42%, and the F1 score was 94.31. In commercial separate fruit tray grading and sorting machines, it has great application potential.
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Huang, Shiyuan, and Rubal Mistry. "A Study of the Causes of Price Fluctuation in Apple Commodity and Consumer Shopping Behavior Based on Taste, Preferences, and Willingness to Pay." Financial Forum 9, no. 4 (January 28, 2021): 209. http://dx.doi.org/10.18282/ff.v9i4.1538.
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<p>The profit margin on the retailer’s side is thin, so increasing the consumer’s willingness to pay is crucial for the supply side to earn more profit. In this paper, the authors develop a taste test to see if consumers’ preference for organic and local apples can alter their taste perception for the same apple. The result showed consumer’s preference does change his/her taste preference on the same apple. Besides the experiment, the authors also design a survey to know the consumer’s shopping preferences and the exact willingness to pay. The survey results show that consumers are in support of Local Apples as compared to Organic Apples but are willing to pay more for Organic Apples than Local Apples. Another conclusion that can be drawn is that this survey indicates that there is a huge profit margin for retailers as consumers are willing to pay more for organic apples than the average market price for the apples.</p>
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Hasan, Moh Arie. "Classification of Apple Types Using Principal Component Analysis and K-Nearest Neighbor." International Journal of Information System Technology and Data Science 1, no. 1 (June 9, 2023): 15–22. http://dx.doi.org/10.61398/ijist-das.v1i1.11.
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Apple is a fruit that is quite popular in Indonesia and is widely consumed by people. This fruit has various types of shapes and colors. Types of apples can be distinguished by their color, size, and shape, but it is still difficult for ordinary people to type apples that are more similar in color and size, such as the examples of Braeburn and Crimson Snow apples. This gave rise to the idea of researching image processing to classify the types of apples. This is to help determine the differences between the two types of apples. The classification process of apples is done by testing the image of an apple based on existing training data. The research method consisted of preprocessing image segmentation with morphological operations and feature extraction into Principal Component Analysis (PCA). The classification algorithm used is a K-Nearest Neighbor (KNN). Using adequate training data will further improve the classification of types of apples. The final results of this study amounted to 91,67%.
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Juozas, Lanauskas, Kviklys Darius, Liaudanskas Mindaugas, Janulis Valdimaras, Uselis Nobertas, Viškelis Jonas, and Viškelis Pranas. "Lower nitrogen nutrition determines higher phenolic content of organic apples." Horticultural Science 44, No. 3 (September 7, 2017): 113–19. http://dx.doi.org/10.17221/50/2016-hortsci.
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Phenolic content of apples from an integrated and organic apple tree orchard was analysed at the Institute of Horticulture of Lithuanian Research Centre for Agriculture and Forestry in 2012–2013. Apples of ‘Lodel’ and ‘Aldas’ cultivars on rootstock B.396 in 8–9<sup>th</sup> leaf were tested. Nitrogen and potassium fertilizers were applied annually at the rates of 50 kg/ha N and 66.4 kg/ha K in an integrated fruit orchard. A mixture of perennial grasses with 25% of white clover was sown in interrows in the second year after tree establishment in the organic production system. Every two years sward in alternate interrows was tilled for natural organic matter mineralization. Fertilizers were not used in the organic apple orchard. Organic apples of both cultivars had a higher content of procyanidins B1 and B2, phloridzin, chlorogenic acid, (+)-catechin, and (–)-epicatechin. Organic ‘Aldas’ apples also contained more hyperoside, avicularin and quercitrin than non-organic apples. On average, the total phenolic content of organic apples of both cultivars was 43% higher than that of apples from the integrated orchard. These differences could be explained by nitrogen nutrition: the N content in organically grown apple leaves was significantly lower than that in leaves from the integrated production system. Tree trunk diameter and yield of organic apple were less, and fruits were better coloured.
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Saputra, Arif. "KLASIFIKASI PENGENALAN BUAH MENGGUNAKAN ALGORITMA NAIVE BAIYES." Jurnal RESISTOR (Rekayasa Sistem Komputer) 2, no. 2 (October 28, 2019): 83–88. http://dx.doi.org/10.31598/jurnalresistor.v2i2.434.
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Manually sorting varieties of apples result in high costs, subjectivity, boredom, and inconsistencies associated with humans. A means is needed to distinguish between types of apples and, therefore, some reliable techniques are necessary to identify varieties quickly and without damage. The purpose of conducting research is to investigate the application and performance for Naive Bayes algorithm for apple varieties. This software methodology involves image acquisition, preprocessing, segmentation and analysis classification varieties for apple. The prototype of Apple's classification system was built using the MATLAB R2017 development platform environment. The results in this study indicate that the estimated average accuracy, sensitivity, precision, and specificity are 81%, 73%, 100%, and 70%, respectively. MLP-Neural shows that performance of the Naive Bayes technique is consistent with Principal, Fuzzy Logic, and Neural analysis with 89%, 91%, 87%, and 82% respectively in terms of accuracy. This study shows that Naif Bayes has excellent potential for identifying nondestructive and accurate apple varieties.
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Liu, Xiaopeng, Zhentao Cao, Liu Yang, Huan Chen, and Yonglin Zhang. "Research on Damage Properties of Apples Based on Static Compression Combined with the Finite Element Method." Foods 11, no. 13 (June 23, 2022): 1851. http://dx.doi.org/10.3390/foods11131851.
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Apples are easily damaged during transportation due to extrusion and collision, resulting in structural damage and deterioration. To better understand apples’ mechanical–structural damage behavior, a texture analyzer platform combined with in situ observation was established. The effects of extrusion distance, speed, working temperature, and typical kinds of apple were considered for damage mechanisms. Apple damage was analyzed via the finite element method (FEM). The results indicated that the apple extrusion behavior can be divided into elastic interaction and plastic damage. Compression displacement effects were obviously significant in terms of structural damage, and apple samples were in an elastic stage with displacement of less than 2.3 mm, and no structural damage. The peak force energy-displacement mathematical model was established, showing an “s” shape and upward parabolic shape. The critical compression energy was around 100N·mm during elastic interaction. The damaged area was positively correlated with the compression energy. The FEM simulation results were consistent with the damage distribution of apples. The effects of speed on the three apple types were different. Red Fuji apples with a bruised area were not sensitive to pressure speed. The effect on the crack forming of Ralls apples was significant. Golden Delicious apples with a bruised area and crack formation showed an intermediate effect. The peak force–temperature fitting curve showed a downward parabolic shape and an R2 determination factor of 0.99982. Apple squeeze damage mechanisms provide theoretical guidance for apple damage control.
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Kotova, Viktoriya, Volodymyr Shapkin, and Kateryna Tertyshna. "Chemical and Pharmaceutical Features of Obtaining Pectins from Apple Pomace and Prospects for Use in Medicine and Pharmacy." SSP Modern Pharmacy and Medicine 4, no. 1 (January 9, 2024): 1–12. http://dx.doi.org/10.53933/sspmpm.v4i1.126.
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The COVID-19 pandemic has shown the need to increase the level of providing patients with medicines. The development of new drugs using natural biomaterials remains relevant. The chemical and pharmaceutical features of obtaining apple pectin have been studied. The influence of technological factors during the extraction of apple pulp from different varieties of apples on the yield of pectin substances was studied. A chemical analysis of pectin content and output was carried out. The fractional composition of pectin substances was analyzed. Prospects for the use of pectins in medicine and pharmacy are outlined. The effect of the technological conditions of extraction of pectin extract from apple pomace on the content and yield of pectin in apple pulp from different varieties of apples was investigated. The technology for obtaining pectins from apple pulp in the presence of various acidic agents is presented, and it is established that the conditions for obtaining apple pectins are optimal for obtaining the highest yield of pectin compounds when choosing the technological parameters of the first stage of hydrolysis for summer and autumn varieties of apples using citric acid with a concentration of 0.10-0.15%, at a temperature of 80-85°C, lasting 2 hours for autumn varieties of apples, and 2.5 hours for summer varieties of apples. Under the conditions of the proposed technology, highly esterified apple pectin (degree of esterification on average 75%) was obtained from apple pulp of autumn and summer varieties of apples, which can be used in medicine and pharmacy.
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LANG, MEGAN M., STEVEN C. INGHAM, and BARBARA H. INGHAM. "Verifying Apple Cider Plant Sanitation and Hazard Analysis Critical Control Point Programs: Choice of Indicator Bacteria and Testing Methods." Journal of Food Protection 62, no. 8 (August 1, 1999): 887–93. http://dx.doi.org/10.4315/0362-028x-62.8.887.
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The objectives of this study were (i) to evaluate the survival of coliforms, Escherichia coli, and enterococci in refrigerated apple cider; (ii) to develop simple and inexpensive presumptive methods for detection of these bacteria; (iii) to perform a field survey to determine the prevalence of these bacteria on apples and in apple cider; and (iv) based on our results, to recommend the most useful of these three indicator groups for use in verifying apple cider processing plant sanitation and hazard analysis critical control point (HACCP) programs. Eight of 10 coliform strains (5 E. coli, 1 Enterobacter aerogenes, and 2 Klebsiella spp.) inoculated into preservative-free apple cider (pH 3.4, 13.3° Brix) survived well at 4°C for 6 days (≤3.0 log10 CFU/ml decrease). Of 21 enterococci strains (Enterococcus faecalis, E. faecium, and E. durans), only 2 E. durans and 3 E. faecium strains survived well. Simple broth-based colorimetric methods were developed that detected the presence of ∼10 cells of coliforms or enterococci. In three field studies, samples of unwashed apples (drops and picked), washed apples, and freshly pressed cider were presumptively analyzed for total coliforms, E. coli, and enterococci using qualitative and/or quantitative methods. Drop apples were more likely than picked apples to be contaminated with E. coli (26.7% vs. 0%) and enterococci (20% vs. 0%). Washing had little effect on coliform populations and in one field study was associated with increased numbers. Total coliform populations in cider ranged from <1 CFU/ml to >738 most probable number/ml, depending on the enumeration method used and the sample origin. E. coli was not recovered from washed apples or cider, but enterococci were present on 13% of washed apple samples. The qualitative coliform method successfully detected these bacteria on apples and in cider. Based on its exclusively fecal origin, good survival in apple cider, and association with drop apples, we conclude that E. coli is the most useful organism for verifying apple cider sanitation and HACCP programs.
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Sekharamantry, Praveen Kumar, Farid Melgani, Jonni Malacarne, Riccardo Ricci, Rodrigo de Almeida Silva, and Jose Marcato Junior. "A Seamless Deep Learning Approach for Apple Detection, Depth Estimation, and Tracking Using YOLO Models Enhanced by Multi-Head Attention Mechanism." Computers 13, no. 3 (March 21, 2024): 83. http://dx.doi.org/10.3390/computers13030083.
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Considering precision agriculture, recent technological developments have sparked the emergence of several new tools that can help to automate the agricultural process. For instance, accurately detecting and counting apples in orchards is essential for maximizing harvests and ensuring effective resource management. However, there are several intrinsic difficulties with traditional techniques for identifying and counting apples in orchards. To identify, recognize, and detect apples, apple target detection algorithms, such as YOLOv7, have shown a great deal of reflection and accuracy. But occlusions, electrical wiring, branches, and overlapping pose severe issues for precisely detecting apples. Thus, to overcome these issues and accurately recognize apples and find the depth of apples from drone-based videos in complicated backdrops, our proposed model combines a multi-head attention system with the YOLOv7 object identification framework. Furthermore, we provide the ByteTrack method for apple counting in real time, which guarantees effective monitoring of apples. To verify the efficacy of our suggested model, a thorough comparison assessment is performed with several current apple detection and counting techniques. The outcomes adequately proved the effectiveness of our strategy, which continuously surpassed competing methods to achieve exceptional accuracies of 0.92, 0.96, and 0.95 with respect to precision, recall, and F1 score, and a low MAPE of 0.027, respectively.
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Riekstina-Dolge, Rita, Zanda Kruma, Fredijs Dimins, Evita Straumite, and Daina Karklina. "Phenolic Composition and Sensory Properties of Ciders Produced from Latvian Apples." Proceedings of the Latvia University of Agriculture 31, no. 1 (July 29, 2014): 39–45. http://dx.doi.org/10.2478/plua-2014-0005.
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Abstract Polyphenol compounds are very important components of cider – they are responsible for the colour and the bitterness and astringency balance of cider. The polyphenolic profile of apples and apple drinks is influenced by several factors: apple variety, climate, maturity, and technological processes applied. This research paper concerns the influence of apple variety on the phenolic compounds and sensory properties of cider. Fermentation of 12 varieties of apple juice with Saccharomyces cerevisiae yeast ‘71B-1122’ (Lalvin, Canada) was performed in a laboratory of the Faculty of Food Technology of the Latvia University of Agriculture. The total phenol content (TPC) was determined according to the Folin-Ciocalteu spectrophotometric method. Individual phenolic compounds were analysed using HPLC. Sensory properties (clarity, the apple, fruit and yeast aroma, the apple and yeast taste, sourness, astringency, and bitterness) were evaluated by trained panelists using a line scale. Special attention was paid to the use of dessert apples for the production of cider. The most important sensory properties of cider are the aroma and taste of apples and fruit. All cider samples showed the intensity of apple aroma ranging from 5.3 to 7.6 points, and higher results were obtained for cider from the bvariety ‘Auksis’ apples. The TPC in cider samples varied from 792.68 to 3399.78 mg L-1: Among crab apples, the highest TPC was detected in ciders made from the ‘Hyslop’ and ’Riku’ varieties, whereas among dessert apples, the highest TPC was detected in ciders made from the ‘Antonovka’ variety. Among the twelve phenols identified in cider samples, chlorogenic acid and caffeic acid were the dominating ones. Variation in the sensory properties of ciders was dependent on the physicochemical composition of the apples used.
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Abdelhalim, Aya, Yasser S. A. Mazrou, Nabila Shahin, Gabr A. El-Kot, Abdelnaser A. Elzaawely, Hanafey F. Maswada, Abeer H. Makhlouf, and Yasser Nehela. "Enhancing the Storage Longevity of Apples: The Potential of Bacillus subtilis and Streptomyces endus as Preventative Bioagents against Post-Harvest Gray Mold Disease, Caused by Botrytis cinerea." Plants 13, no. 13 (July 4, 2024): 1844. http://dx.doi.org/10.3390/plants13131844.
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Gray mold, caused by Botrytis cinerea Pers. Fr., is one of the most vital plant diseases, causing extensive pre- and post-harvest losses in apple fruits. In the current study, we isolated and identified two potential endophytic bioagents, Bacillus subtilis and Streptomyces endus. Both bioagents exhibited a potent fungistatic effect against B. cinerea under both in vitro and in planta conditions. Moreover, two experiments were carried out; (i) the first experiment was conducted at room temperature after artificial inoculation with B. cinerea to monitor the progression of the infection and the corresponding biochemical responses of the apples. Our in vivo findings showed that the treated B. cinerea-infected apple fruits with the cell-free bacterial filtrate of B. subtilis and S. endus (dipping or wrapping) significantly reduced the rotten area of the treated apple at room temperature. Additionally, B. subtilis and S. endus enhanced the enzymatic (POX and PPO) and non-enzymatic (phenolics and flavonoids) antioxidant defense machinery in treated apples. (ii) The second experiment focused on the preventive effects of both bioagents over a 90-day storage period at 1 °C of healthy apples (no artificial inoculation). The application of both bacterial filtrates prolonged the storage period, reduced the relative weight loss, and maintained high-quality parameters including titratable acidity, firmness, and total soluble solids of apple fruits under cold storage at 1 °C. The Kaplan–Meier analysis of rotten apples over 90 days during cold storage showed that the treated apples lasted longer than the non-treated apples. Moreover, the lifespan of apple fruits dipped in the culture filtrate of B. subtilis, or a fungicide, was increased, with no significant differences, compared with the non-treated apples. The current results showed the possibility of using both bioagents as a safe and eco-friendly alternative to chemical fungicides to control gray mold disease in apples.
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Jiang, Xiaogang, Mingwang Zhu, Jinliang Yao, Yuxiang Zhang, and Yande Liu. "Calibration of Near Infrared Spectroscopy of Apples with Different Fruit Sizes to Improve Soluble Solids Content Model Performance." Foods 11, no. 13 (June 28, 2022): 1923. http://dx.doi.org/10.3390/foods11131923.
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The transmission spectrum of apples is affected by the fruit’s size, which leads to poor prediction performance of the soluble solids content (SSC) models built for their different apple sizes. In this paper, three sets of near infrared (NIR) spectra of apples with various apple diameters were collected by applying NIR spectroscopy detection equipment to compare the spectra differences among various apple diameter groups. The NIR spectra of apples were corrected by studying the extinction rates within different apples. The corrected spectra were used to develop a partial least squares prediction model for their soluble solids content. Compared with the prediction model of the soluble solids content of apples without size correction, the Rp of PLSR improved from 0.769 to 0.869 and RMSEP declined from 0.990 to 0.721 in the small fruit diameter group; the Rp of PLSR improved from 0.787 to 0.932 and RMSEP declined from 0.878 to 0.531 in the large fruit diameter group. The proposed apple spectra correction method is effective and can be used to reduce the influence of sample diameter on NIR spectra.
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Zhong, Lei, Jason Carere, Zhaoxin Lu, Fengxia Lu, and Ting Zhou. "Patulin in Apples and Apple-Based Food Products: The Burdens and the Mitigation Strategies." Toxins 10, no. 11 (November 15, 2018): 475. http://dx.doi.org/10.3390/toxins10110475.
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Apples and apple-based products are among the most popular foods around the world for their delightful flavors and health benefits. However, the commonly found mold, Penicillium expansum invades wounded apples, causing the blue mold decay and ensuing the production of patulin, a mycotoxin that negatively affects human health. Patulin contamination in apple products has been a worldwide problem without a satisfactory solution yet. A comprehensive understanding of the factors and challenges associated with patulin accumulation in apples is essential for finding such a solution. This review will discuss the effects of the pathogenicity of Penicillium species, quality traits of apple cultivars, and environmental conditions on the severity of apple blue mold and patulin contamination. Moreover, beyond the complicated interactions of the three aforementioned factors, patulin control is also challenged by the lack of reliable detection methods in food matrices, as well as unclear degradation mechanisms and limited knowledge about the toxicities of the metabolites resulting from the degradations. As apple-based products are mainly produced with stored apples, pre- and post-harvest strategies are equally important for patulin mitigation. Before storage, disease-resistance breeding, orchard-management, and elicitor(s) application help control the patulin level by improving the storage qualities of apples and lowering fruit rot severity. From storage to processing, patulin mitigation strategies could benefit from the optimization of apple storage conditions, the elimination of rotten apples, and the safe and effective detoxification or biodegradation of patulin.
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Shi, Caiyun, Li Liu, Zhifeng Wei, Junwei Liu, Ming Li, Zhenli Yan, and Dengtao Gao. "Anthocyanin Accumulation and Molecular Analysis of Correlated Genes by Metabolomics and Transcriptomics in Sister Line Apple Cultivars." Life 12, no. 8 (August 16, 2022): 1246. http://dx.doi.org/10.3390/life12081246.
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Red coloration in apples, an important quality trait, is primarily attributed to the accumulation of anthocyanins. Centuries of breeding have produced a wide variety of apples with different levels of anthocyanins in response to genetic and environmental stimuli. The Huashuo apple shows a much darker red color than its sister line, Huarui. Thirteen different anthocyanins were detected in Huashuo and Huarui apples, of which ten were significantly more abundant in Huashuo apples, confirming that the color difference is indeed attributed to high anthocyanins accumulation rather than the types of anthocyanins. In particular, the contents of cyanidin 3-O-galactoside levels were highest among anthocyanins in both cultivars, reaching >5000 μg·g−1 at the last color transition stage in Huashuo apples, while only >3000 μg·g−1 in Huarui apples. Moreover, the expression of most structural genes, especially DFR, CHI, and 4CL associated with anthocyanin synthesis, were higher in Huashuo apples than in Huarui apples. Combined transcriptomics, metabolomics, and qRT-PCR analysis revealed that six transcription factors from the MYB and bZIP transcription factor families likely play key roles in the dark coloring of Huashuo apples. These results provide deeper insights into apple coloring and suggest a series of candidate genes for breeding anthocyanin-rich cultivars.
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Lyons, Sean T., Linda Schweitzer, Eddy S. W. Ng, and Lisa K. J. Kuron. "Comparing apples to apples." Career Development International 17, no. 4 (August 10, 2012): 333–57. http://dx.doi.org/10.1108/13620431211255824.
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KORETZ, R. "Comparing apples with apples." Gastroenterology 115, no. 5 (November 1998): 1299–300. http://dx.doi.org/10.1016/s0016-5085(98)70110-6.
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Regula, Jaroslaw, and Michal F. Kaminski. "Comparing apples to apples." Endoscopy 51, no. 08 (July 25, 2019): 713–14. http://dx.doi.org/10.1055/a-0958-2366.
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Li, Jianxin, Yibing Zhou, and Zimo Gao. "Image Recognition for Fruit-Picking Robots." Academic Journal of Science and Technology 9, no. 1 (January 20, 2024): 226–31. http://dx.doi.org/10.54097/m3tfqr59.
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This summary presents the solutions to the five questions posed in the competition regarding apple image recognition. The objective is to establish a robust apple image recognition model that accurately counts the number of apples, estimates their positions, determines their maturity state, calculates their masses, and recognizes them based on provided image datasets. The specific answers to each question are as follows: Using the image dataset of harvest-ready apples provided in Attachment 1, an image feature extraction method is employed to establish a mathematical model for counting the number of apples in each image. The distribution of all apples in Attachment 1 is then depicted in a histogram. The precise number of apples in each image is determined, enabling a comprehensive understanding of the dataset. Utilizing the image dataset of harvest-ready apples provided in Attachment 1, the positions of the apples in each image are identified. The left bottom corner of the image serves as the coordinate origin, and a two-dimensional scatter diagram is created, illustrating the geometric coordinates of all apples in Attachment 1. This analysis facilitates the visualization of the spatial distribution of apples within the dataset. Based on the image dataset of harvest-ready apples provided in Attachment 1, a mathematical model is developed to assess the maturity state of apples in each image. By applying this model, a histogram is generated, illustrating the distribution of maturity levels across all apples in Attachment 1. This analysis provides insights into the overall maturity status of the dataset.
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Kalashnikov, G. V., and E. V. Litvinov. "Prospects of improving technologies for apple raw materials processing." Proceedings of the Voronezh State University of Engineering Technologies 84, no. 1 (January 18, 2022): 86–92. http://dx.doi.org/10.20914/2310-1202-2022-1-86-92.
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A resource-saving technology for processing apples, including the main production of finished dried products in the form of dried apples, apple chips, apple semi-finished products and additional production based on secondary raw materials recovery from the main production, were proposed in the work. The possibility of using of secondary raw materials from the apples industrial processing to obtain natural products that allows to make the main manufacture of dried apple products as efficient as possible was studied by the authors. The main directions of apples and secondary apple raw materials processing were considered in the work. The technological scheme of the line for apples and their wastes processing based on dehydration and moisture-thermal processing of components, taking into account the specifics of the production of dried fruits, chips and their semi-finished products, was proposed in the course of this study. The main production line for the manufacture of dried apples, apple chips and apple semi-finished products was designed. The resource-saving technological scheme of the dried apple and apple chips production line includes a washing machine, an inspection conveyor, a calibrator, a machine for seeds removing and a device for cutting fruits into chips, a sulfitator, a combined continuous toroidal apparatus for wet-heat treatment, divided into sections for raw materials heating, convective drying , preliminary hydrothermal treatment between sections of microwave drying and dried product cooling and a filling and packaging machine. Taking into account the type of raw materials, a set of equipment from a drum machine with a washing unit and a multifunctional plant with raw materials crushing and seeds separation was provided in the line. The recirculation circuit, the feedstock heating, the steam and condensate used after drying in a closed circuit were used to create an energy-saving technology for the finished product manufacturing. The line consists of modular blocks and is reconfigured depending on the type of dried apples or apple chips obtained based on the developed resource-saving scheme and combined convective microwave drying of raw materials.
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PIETRYSIAK, EWA, JULIANNE M. KUMMER, INES HANRAHAN, and GIRISH M. GANJYAL. "Efficacy of Surfactant Combined with Peracetic Acid in Removing Listeria innocua from Fresh Apples." Journal of Food Protection 82, no. 11 (October 23, 2019): 1965–72. http://dx.doi.org/10.4315/0362-028x.jfp-19-064.
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ABSTRACT Large amounts of water used in the apple packing process, the presence of organic matter, and difficult-to-clean equipment are vectors for contaminating apples with foodborne pathogens, such as Listeria monocytogenes. There is a need to develop new cleaning methods for fresh apples and evaluate their antimicrobial efficacy. A series of surfactants of different chemical properties (cationic lauric arginate [LAE], anionic sodium dodecyl sulfate [SDS], and nonionic Tween 20 [T20]) alone and combined with peracetic acid (PAA) were evaluated for their efficiency in the removal of L. innocua, a surrogate of L. monocytogenes, from fresh apples. Whole fresh apples were inoculated with L. innocua (7 log CFU/mL) by a dipping method, dried, and subjected to wash treatments with selected cleaning solutions (water, PAA, PAA-LAE, PAA-SDS, and PAA-T20). The contact angle between the cleaning solutions and the surface of the apples was measured. The antimicrobial activity of the cleaning solutions and the efficacy of the cleaning treatment were evaluated by enumeration of L. innocua from treated apples and visualized by scanning electron microscopy. Stem bowl and calyx cavities of the apple harbored higher bacteria concentrations (∼4.82 log CFU per apple), compared with the equatorial section (∼2.66 log CFU per apple). Addition of 0.1% of selected surfactants led to a significant decrease in surface tension of cleaning solutions and allowed better spreading on the apple surface. Surfactants combined with PAA solution resulted in higher L. innocua reduction compared with PAA alone; however, their efficacy was limited. The most effective cleaning solution was PAA-T20, with reduction of approximately 2.2 log. Scanning electron microscopy imaging confirmed that most bacteria were harbored inside the surface irregularities. PAA alone and with surfactants caused damage and deformation of bacteria cells. Cleaning apples with PAA combined with surfactants may improve microbial safety in whole apples; however, the efficiency of the decontamination treatment can be reduced because of variations in apple morphology.
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JANES, M. E., T. COBBS, S. KOOSHESH, and M. G. JOHNSON. "Survival Differences of Escherichia coli O157:H7 Strains in Apples of Three Varieties Stored at Various Temperatures." Journal of Food Protection 65, no. 7 (July 1, 2002): 1075–80. http://dx.doi.org/10.4315/0362-028x-65.7.1075.
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Differences in survival and growth among five different Escherichia coli O157:H7 strains in three apple varieties were determined at various temperatures. Jonathan, Golden Delicious, and Red Delicious apples were wounded and inoculated with E. coli O157:H7 strains C7929 (apple cider isolate), 301C (chicken isolate), 204P (pork isolate), 933 (beef isolate), and 43890 (human isolate) at an initial level of 6 to 7 log CFU/g. The inoculated apples were stored at a constant temperature of 37, 25, 8, or 4°C or at 37°C for 24 h and then at 4°C, and bacterial counts were determined every week for 28 days. By day 28, for Jonathan apples at 25°C, the apple isolate counts were significantly higher than the chicken and human isolate counts. At 4°C for 28 days, the human isolate inoculated into Jonathan, Golden Delicious, and Red Delicious apples was present in significantly smaller numbers than the other strains. The apple isolate survived significantly better at 4°C, yielding the highest number of viable cells. By days 21 and 28, for apples stored at 37°C for the first 24 h and then at 4°C, the counts of viable E. coli O157: H7 apple and human isolates were 6.8 and 5.8 log CFU/g at the site of the wound, whereas for apples kept at 4°C for the duration of storage, the respective counts were 5.6 and 1.5 log CFU/g. Our study shows that E. coli O157:H7 strains responded differentially to their ability to survive in these three apple varieties at 25 or 4°C and produced higher viable counts when apples were temperature abused at 37°C for 24 h and then stored at 4°C for 27 days.
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Fan, Xuetong, and James P. Mattheis. "Enhanced Degreening of Apple Fruit by Jasmonates." HortScience 32, no. 3 (June 1997): 457D—457. http://dx.doi.org/10.21273/hortsci.32.3.457d.
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Airborne methyl jasmonate (MJ) can modulate apple fruit ripening, including the degreening process. Degreening of `Fuji' and `Golden Delicious' apples by jasmonates [jasmonic acid (JA) and MJ] in aqueous solution was investigated. JA and MJ applied by dipping apples in solutions of jasmonates for 2 min enhanced degreening during ripening at 20C. MJ was more effective at promoting degreening compared to JA. The minimum concentration of jasmonates required to promote significant degreening during the 2-week ripening period was 1 mM. Degreening of jasmonate-treated apples ripened at 4C progressed slower compared to apples ripened at 20°C. JA stimulated apple fruit ethylene production at concentrations as low as 10 μM. Jasmonates at 1 or 10 mM were more effective at accelerating the degreening process compared to 0.35 or 3.5 mM ethephon. Firmness, soluble solids content, and titratable acidity of `Fuji' apples were not significantly affected by jasmonate treatments. Peel injury occurred on apples treated with 10 mM JA or 3.5 mM ethephon.