Relevant bibliographies by topics / Fruit quality and grading

Academic literature on the topic 'Fruit quality and grading'

Author: Grafiati
Published: 10 December 2022
Last updated: 19 February 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Fruit quality and grading.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Fruit quality and grading"

1

Sardar, Hassan. "Fruit Quality Estimation by Color for Grading." International Journal of Modeling and Optimization 4, no. 1 (2014): 38–42. http://dx.doi.org/10.7763/ijmo.2014.v4.344.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Patil, Kavita. "Identifying the Quality of Tomatoes in Image Processing." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (January 31, 2022): 780–82. http://dx.doi.org/10.22214/ijraset.2022.39909.

Full text
Abstract:
Abstract: In agricultural and horticulture. Image processing is one of the widely used application. in this paper automated quality identification using some image processing techniques is there that can be done using some image features which help in quality detection of vegetables like shape, color and size. tomatoes are in high demand because the world population consumes them daily. This research is to improve tomato production and fruit quality through fruit measurement methods, which have a low impact factor on fruit and plant during measurements. As there is high demand for quality fruits in the market fruit grading process is considered as very important. Fruit grading by a human may cause inefficient and it may also leads to some error. Researchers have developed numerous algorithms for quality grading and sorting of fruits. color is most important features for indentifying disease and maturity of the fruit. Here a sorting process is introduced where the image of the fruit is captured and analyzed using image processing techniques and the defected fruit is discarding by this process. the main aim of this paper is to do the quality check of the fruits within a short span of time. Keywords: Fruit grading, Tomato quality, image processing, segmentation, classification
APA, Harvard, Vancouver, ISO, and other styles
3

Utpat, V. B., Dr K. J. e. Karand, and Dr A. O. Mulani. "Grading of Pomegranate Using Quality Analysis." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (February 28, 2022): 875–81. http://dx.doi.org/10.22214/ijraset.2022.40409.

Full text
Abstract:
Abstract: Over the world, India is the largest producer of pomegranate. India produces excellent varieties of pomegranate having soft seeds, very less acids and very attractive colours of fruits and grains. There is tremendous potential for exports of pomegranates from India. Quality grading of pomegranate is an important operation in the export of the pomegranate. Generally external appearance of the fruit decides the quality of the fruit. The fruit with bright colour, good texture and shape is quickly chosen by the customer. Though pomegranate can be qualified or graded manually, it is insufficient method which consumes more time also. Automated grading system quickly grades the pomegranate according to quality of the fruit with no errors. This paper discusses the machine vision approach to form a quality grading analysis system. Keywords: Image acquisition, Image Pre-processing, Image segmentation, and feature extraction, ANN (Artificial Neural Network)
APA, Harvard, Vancouver, ISO, and other styles
4

Zhu, Xueyan, Deyu Shen, Ruipeng Wang, Yili Zheng, Shuchai Su, and Fengjun Chen. "Maturity Grading and Identification of Camellia oleifera Fruit Based on Unsupervised Image Clustering." Foods 11, no. 23 (November 25, 2022): 3800. http://dx.doi.org/10.3390/foods11233800.

Full text
Abstract:
Maturity grading and identification of Camellia oleifera are prerequisites to determining proper harvest maturity windows and safeguarding the yield and quality of Camellia oil. One problem in Camellia oleifera production and research is the worldwide confusion regarding the grading and identification of Camellia oleifera fruit maturity. To solve this problem, a Camellia oleifera fruit maturity grading and identification model based on the unsupervised image clustering model DeepCluster has been developed in the current study. The proposed model includes the following two branches: a maturity grading branch and a maturity identification branch. The proposed model jointly learns the parameters of the maturity grading branch and maturity identification branch and used the maturity clustering assigned from the maturity grading branch as pseudo-labels to update the parameters of the maturity identification branch. The maturity grading experiment was conducted using a training set consisting of 160 Camellia oleifera fruit samples and 2628 Camellia oleifera fruit digital images collected using a smartphone. The proposed model for grading Camellia oleifera fruit samples and images in training set into the following three maturity levels: unripe (47 samples and 883 images), ripe (62 samples and 1005 images), and overripe (51 samples and 740 images). Results suggest that there was a significant difference among the maturity stages graded by the proposed method with respect to seed oil content, seed soluble protein content, seed soluble sugar content, seed starch content, dry seed weight, and moisture content. The maturity identification experiment was conducted using a testing set consisting of 160 Camellia oleifera fruit digital images (50 unripe, 60 ripe, and 50 overripe) collected using a smartphone. According to the results, the overall accuracy of maturity identification for Camellia oleifera fruit was 91.25%. Moreover, a Gradient-weighted Class Activation Mapping (Grad-CAM) visualization analysis reveals that the peel regions, crack regions, and seed regions were the critical regions for Camellia oleifera fruit maturity identification. Our results corroborate a maturity grading and identification application of unsupervised image clustering techniques and are supported by additional physical and quality properties of maturity. The current findings may facilitate the harvesting process of Camellia oleifera fruits, which is especially critical for the improvement of Camellia oil production and quality.
APA, Harvard, Vancouver, ISO, and other styles
5

Saputra, Andri, Wahyu Candra, Yan Soerbakti, Romi Fadli Syahputra, Defrianto Defrianto, and Saktioto Saktioto. "STUDI AWAL GRADING BUAH SAWIT DENGAN BANTUAN INJEKSI TEGANGAN LISTRIK SEARAH." Komunikasi Fisika Indonesia 16, no. 2 (October 31, 2019): 103. http://dx.doi.org/10.31258/jkfi.16.2.103-106.

Full text
Abstract:
Maturity progress of palm fruit is greatly depending on the availability of nutrients and environments. Determining maturity level of palm fruit is important to evaluate the quality of palm oil fruits. The younger or too mature fruits will produce poor quality of crude palm oil (CPO). An appropriate devices are needed that can measure the level of fruit maturity so that uniformity of maturity grade can be carried out to obtain high quality CPO. This research provides a preliminary study of voltage change on the surface of oil palm seeds which subjected by electric potential. The low directional voltage (DC) injection treatment, ~ 10V, was applied to investigate the impact of applied voltage on palm oil seeds with three different levels of maturity, i.e. immature (young), ripe and over ripe . The results shown that oil palm fruit quite quickly responds to injection of DC applied voltage with different responding voltage. This responding voltage tends to increase with increasing maturity levels, but decreases for over ripe fruit which has falling down and starting to dry out.
APA, Harvard, Vancouver, ISO, and other styles
6

Qiao, J., A. Sasao, S. Shibusawa, N. Kondo, and E. Morimoto. "Mobile fruit grading robot : Mapping yield and quality of sweet pepper in real-time." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 205. http://dx.doi.org/10.1299/jsmermd.2004.205_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Kondo, Naoshi. "Robotization in fruit grading system." Sensing and Instrumentation for Food Quality and Safety 3, no. 1 (December 23, 2008): 81–87. http://dx.doi.org/10.1007/s11694-008-9065-x.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

P., Navitha, Sujatha K., and Beaulah A. "Effect Effect of fruit size on physiological seed quality parameters of Cucumber (Cucumis sativus)." Journal of Applied and Natural Science 11, no. 2 (June 10, 2019): 394–97. http://dx.doi.org/10.31018/jans.v11i2.2046.

Full text
Abstract:
An experiment was carried out at the Department of Seed Science and Technology, Agricultural College and Research Institute, Madurai during 2018 to find out the effect of fruit size on physiological seed quality of cucumber. Variation in fruit size of cucumber results in poor quality seeds. In order to overcome this obstacle fruit grading was done based on weight of fruit to obtain good quality seeds. Harvested fruits of cucumber (Cucumis sativus) were categorized based on the weight into three different groups viz., Big (2.41kg), medium (1.66kg) and small (1.28kg). Observations on fruit and seed quality parameters were recorded. The results revealed that medium sized fruits recorded higher values compared to big and small sized fruits. The number of seeds/fruit recorded higher in medium sized fruit (935 numbers) followed by small (896 numbers) and big (876 numbers) sized fruits. The big, medium and small fruits were recovered to 1.52 %, 1.06% and 0.58% seeds respectively. The physiological quality characters measured in terms of seed germination revealed that seeds of medium sized fruits were recorded higher (80%) followed by seeds of big (82%) and small (65%). The seedling vigour measured through root (17.08cm) and shoot length (14.45cm), dry matter production (0.85g 10 seedlings-1) and vigour index (2522) also proved the superiority in medium sized fruits.
APA, Harvard, Vancouver, ISO, and other styles
9

Leemans, V., M. F. Destain, and H. Magein. "QUALITY FRUIT GRADING BY COLOUR MACHINE VISION: DEFECT RECOGNITION." Acta Horticulturae, no. 517 (March 2000): 405–12. http://dx.doi.org/10.17660/actahortic.2000.517.51.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Blasco, J., N. Aleixos, and E. Moltó. "Machine Vision System for Automatic Quality Grading of Fruit." Biosystems Engineering 85, no. 4 (August 2003): 415–23. http://dx.doi.org/10.1016/s1537-5110(03)00088-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Fruit quality and grading"

1

Dragulinescu, Stefan. "Grading the quality of evidence of mechanisms." Thesis, University of Kent, 2018. https://kar.kent.ac.uk/68526/.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Misimi, Ekrem. "Computer vision for quality grading in fish processing." Doctoral thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1957.

Full text
Abstract:

High labour costs, due to the existing technology that still involves a high degree of manually based processing, incur overall high production costs in the fish processing industry. Therefore, a higher degree of automation of processing lines is often desirable, and this strategy has been adopted by the Norwegian fish processing industry to cut-down production costs. In fish processing, despite a slower uptake than in other domains of industry, the use of computer vision as a strategy for automation is beginning to gain the necessary maturity for online grading and evaluation of various attributes related to fish quality. This can enable lower production costs and simultaneously increase quality through more consistent and non-destructive evaluation of the fish products.

This thesis investigates the possibility for automation of fish processing operations by the application of computer vision. The thesis summarises research conducted towards the development of computer vision-based methods for evaluation of various attributes related to whole fish and flesh quality. A brief summary of the main findings is presented here.

By application of computer vision, a method for the inspection of the presence of residual blood in the body cavity of whole Atlantic salmon was developed to determine the adequacy of washing. Inadequate washing of fish after bleeding is quite common in commercial processing plants. By segmenting the body cavity and performing a colour analysis, it was shown that the degree of bleeding correlated well with colour parameters, resulting in correct classification of the fish with residual blood. The developed computer vision-based classifier showed a good agreement with the manual classification of the fish that needed re-washing. The proposed method has potential to automate this type of inspection in fish processing lines.

In addition, a computer vision-based classifier for quality grading of whole Atlantic salmon in different grading classes, as specified by the industrial standard, was developed. In the proposed solution, after segmentation of the salmon from the image scene, with the use of the computer vision techniques, it was possible to extract non-redundant geometrical features describing the size and shape of fish. Based on these features, a classifier was developed for classification of fish into respective grading classes. The average correct rate of classification was in good agreement with the manual labelling, and the method has a potential for grading of Atlantic salmon in fish processing lines.

Regarding fillet grading, a computer vision-based sorting method for Atlantic salmon fillets according to their colour score was developed. The method and classifier/matching algorithm was based on the present industrial standard NS 9402 for evaluation of fillets by colour according to Roche Cards. As a result, fillets or parts of fillets, could be classified into different colour grades. This is important for the industry since different markets tend to have different preferences for fillet colour. This classification method is suitable for online industrial purposes. In addition, the method gives colour evaluation of fresh and smoked fillets in the CIELab space, similar to the L, a, and b values generated by a Minolta Chromameter, for different parts of fillets as well as for the entire fillet. The advantage of the computer vision-based method derives from the flexibility in the choice of the size of the region of interest of the fillet for colour measurement, as opposed to the Chromameter, where the Minolta generated values are obtained by interrogating a very small area of the fillet (8 mm). The method can also be used for detection of colour non-uniformities (discoloration) in both fresh and smoked fillets.

A method for computer vision-based measurements and monitoring of transient 2D and 3D changes in the size and shape of fillets during the rigor process and ice storage was developed. The method successfully measured the size (length, width, area) and shape (roundness) of Atlantic salmon and cod fillets, and monitored changes to these during ice storage with high precision. This was demonstrated by comparison of the exhausted and anesthetized fillets. By laser scanning of the fillet, it was possible to obtain size changes in the height (mm) and area of the fillet in cross-section. The method can be used not only for size and shape analysis of fillets but also for other fish products, both in on-line, as well as off-line conditions as a tool for monitoring 2D/3D size and shape changes. The method can also be used for determination of fillet yield measured in thickness, which is an important parameter for the industry. Together with the colour grading ability, this method can also be used for full feature evaluation and classification of any fish or food product from a single image (colour, size and shape in 2D/3D).

If filleting of fish is done pre-rigor, care should be exercised during colour grading since transient colour changes occur in the post-mortem period. As these changes are more pronounced than those that occur during ice storage, incorrect colour grading can occur. The computer vision method developed for evaluation of colour changes in fillets during rigor, ice storage, and due to effects of perimortem handling stress was considered as the most suitable method for industrial purposes when compared to both the Minolta Chromamater and sensory analysis by a panel.

A computer vision-based method for evaluation of fresh and smoked fillets with respect to bleeding was developed. This form of evaluation is important for the industry as residual blood in fillets may lead to reduced visual acceptance of the product. The method was considered suitable for the purpose of this type of evaluation.

The developed computer vision methods have potential for automation of the mentioned grading operations in the commercial fish processing lines. Application of the proposed solutions would lower the production costs, while simultaneously increasing the quality of the products through a more consistent and non-destructive evaluation of these products.

APA, Harvard, Vancouver, ISO, and other styles
3

Wendel, Charlotta. "Multivariate modeling improves quality grading of sawn timber." Thesis, Umeå universitet, Institutionen för fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160765.

Full text
Abstract:
The quality grades are what determines the value of sawn timber. Therefore the grading process is essential for the profitability of a sawmill. At a modern sawmill in northern Sweden, a CT Log Computed Tomography is used in the saw line to optimize the cutting solutions by virtual 3D reconstruction of the log features. By adjusting the position of the log according to the optimal solution before cutting, the aim is to increase the quality and final resale value of the sawn timber. However, measurement errors in the virtual and final grading systems cause inconsistencies that decrease the agreement in grading. The grading process uses a rule-based system based on the Nordic Timber Grading Rules, which depends strongly on the size and shape of knots. If knots are measured incorrectly they could falsely exceed the allowed value for a certain quality, resulting in an inaccurate quality grade. The results from this initial project, show that using multivariate modeling instead of the traditional rule-based grading system improves the agreement between the virtual and final grading. The accuracy in grading increases with up to 19%, resulting in an agreement of 73%. A better agreement between the two systems would allow the process to take advantage of the full potential of the CT, increasing the profitability of the sawmill. The results are promising, but before implementing the method in the sawmill further testing and development have to be done to ensure optimal improvement.
APA, Harvard, Vancouver, ISO, and other styles
4

Marques, José Roberto. "'Hass' avocado fruit quality : the role of fruit minerals and rootstocks /." St. Lucia, Qld, 2002. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16748.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Capewell, Adam Daniel. "Novel grading of silicon germanium for high quality virtual substrates." Thesis, University of Warwick, 2002. http://wrap.warwick.ac.uk/90799/.

Full text
Abstract:
The growth of SiGe virtual substrates, by solid-source molecular beam epitaxy (SS-MBE), using a new germanium grading technique has been studied. It is proposed that the grading of germanium using a series of linearly graded/uniform layers (terrace grading) prevents the dislocation pile-ups, associated with strain relief, from penetrating the entire epilayer. Since the dislocation pile-ups cause threading dislocations to become trapped and increase the roughness of the surface, the control of these pile-ups reduces both the threading dislocation density and the RMS surface roughness. Si0.50Ge0.50 virtual substrates of 2 µm thickness using the terrace grading technique have been studied and compared to conventional linear graded and step graded virtual substrates of the same thickness. Substantial reductions in both the RMS roughness and threading dislocation densities are found in the terrace graded structure, compared with the conventional techniques. Electrical properties have been measured in layers grown on virtual substrates using the terrace grading and show promisingly high hole mobilities. The mechanism by which the terrace graded virtual substrates relax has been examined in order to optimise the growth conditions. It is found that the lowest layers of the virtual substrates do not relax until sufficient strain energy is accumulated by the growth of the following layers, leading to dislocation pile-ups that extend through several layers. The use of in-situ anneals has been shown to greatly improve the relaxation of the lower layers, with a corresponding decrease in the size of the pile-ups, and consequently lower threading dislocation densities have been found.
APA, Harvard, Vancouver, ISO, and other styles
6

Thor, Nandan G. "Using Computer Vision to Build a Predictive Model of Fruit Shelf-life." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1721.

Full text
Abstract:
Computer vision is becoming a ubiquitous technology in many industries on account of its speed, accuracy, and long-term cost efficacy. The ability of a computer vision system to quickly and efficiently make quality decisions has made computer vision a popular technology on inspection lines. However, few companies in the agriculture industry use computer vision because of the non-uniformity of sellable produce. The small number of agriculture companies that do utilize computer vision use it to extract features for size sorting or for a binary grading system: if the piece of fruit has a certain color, certain shape, and certain size, then it passes and is sold. If any of the above criteria are not met, then the fruit is discarded. This is a highly wasteful and relatively subjective process. This thesis proposes a process to undergo to use computer vision techniques to extract features of fruit and build a model to predict shelf-life based on the extracted features. Fundamentally, the existing agricultural processes that do use computer vision base their distribution decisions on current produce characteristics. The process proposed in this thesis uses current characteristics to predict future characteristics, which leads to more informed distribution decisions. By modeling future characteristics, the process proposed will allow fruit characterized as “unfit to sell” by existing standards to still be utilized (i.e. if the fruit is too ripe to ship across the country, it can still be sold locally) which decreases food waste and increases profit. The process described also removes the subjectivity present in current fruit grading systems. Further, better informed distribution decisions will save money in storage costs and excess inventory. The proposed process consists of discrete steps to follow. The first step is to choose a fruit of interest to model. Then, the first of two experiments is performed. Sugar content of a large sample of fruit are destructively measured (using a refractometer) to correlate sugar content to a color range. This step is necessary to determine the end-point of data collection because stages of ripeness are fundamentally subjective. The literature is consulted to determine “ripe” sugar content of the fruit and the first experiment is undertaken to correlate a color range that corresponds to the “ripe” sugar content. This feature range serves as the end-point of the second experiment. The second experiment is large-scale data collection of the fruit of interest, with features being recorded every day, until the fruit reaches end-of-life as determined by the first experiment. Then, computer vision is used to perform feature extraction and features are recorded over each sample fruit’s lifetime. The recorded data is then analyzed with regression and other techniques to build a model of the fruit’s shelf-life. The model is finally validated. This thesis uses bananas as a proof of concept of the proposed process.
APA, Harvard, Vancouver, ISO, and other styles
7

Luwes, Nicolaas Johannes. "Artificial intelligence machine vision grading system." Thesis, Bloemfontein : Central University of Technology, Free State, 2014. http://hdl.handle.net/11462/35.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Su, Qinghua. "Potato Shape Grading Using Depth Imaging." Kyoto University, 2018. http://hdl.handle.net/2433/232491.

Full text
Abstract:
Kyoto University (京都大学)
0048
新制・課程博士
博士(農学)
甲第21278号
農博第2294号
新制||農||1062(附属図書館)
学位論文||H30||N5142(農学部図書室)
京都大学大学院農学研究科地域環境科学専攻
(主査)教授 近藤 直, 教授 清水 浩, 教授 飯田 訓久
学位規則第4条第1項該当
APA, Harvard, Vancouver, ISO, and other styles
9

Stander, Ockert Petrus Jacobus. "Fruit split and fruit size studies on Citrus." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79933.

Full text
Abstract:
Thesis (MScAgric)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: Fruit size and the integrity of the rind are key components that determine the value of a citrus fruit. The application of 2,4-dichlorophenoxy acetic acid (2,4-D) to reduce splitting, a physiological disorder which entails cracking of the rind as well as to increase fruit size was conducted on three different split-susceptible mandarin and two split-susceptible orange cultivars. Treatments were applied directly after the physiological fruit drop period, as well as in January and February at 10 mg·L-1, alone or in combination with calcium (Ca), potassium (K) or gibberellic acid (GA3). Application of 2,4-D directly after physiological fruit drop, either alone or in a tank-mix with K, consistently reduced the number of split mandarin fruit, with later applications in January and February generally being ineffective. Post physiological fruit drop application of 10 mg·L-1 2,4-D significantly increased growth rate (mm.day-1) of all the mandarin cultivars, resulting in increased fruit size. Differences in sensitivity of cultivars to 2,4-D were evident, with the January application reducing the splitting in ‘Midknight’ Valencia. However, all the 2,4-D treatments reduced the fruit growth rate of the orange cultivars. The 2,4-D treatments, in terms of splitting, increased rind thickness, -strength and -coarseness of ‘Marisol’ Clementine, throughout fruit development. In addition fruit diameter and –length increased to such an extent that the fruit shape was altered (reduced d/l-ratio), reducing the potential of the rind to crack and the fruit to split, however rind coarseness of treated fruit was also increased. There were no major negative side effects on internal and external fruit quality, except for a possible reduction in juice content (%). Therefore, 10 mg·L-1 2,4-D can be applied directly after physiological fruit drop on ‘Marisol’ Clementine and ‘Mor’ mandarin to reduce fruit splitting.
AFRIKAANSE OPSOMMING: Vruggrootte asook die integriteit van die skil is belangrike aspekte in die bepaling van ʼn sitrusvrug se waarde. Die toediening van 2,4-dichlorofenoksie asynsuur (2,4-D) om vrugsplit, 'n fisiologiese defek wat tot die kraak van die sitrusskil lei, te verminder is getoets op drie mandaryn- en twee lemoenkultivars. Hiermee saam is die potensiaal van 2,4-D om vruggrootte te verbeter ook geëvalueer. Die 2,4-D behandelings is direk na die fisiologiese vrugval periode toegedien, asook in Januarie en Februarie, teen 10 mg·L-1, alleen of in kombinasie met kalsium (Ca), kalium (K) of gibberelliensuur (GS3). Al die mandarynkultivars het ʼn vermindering in die totale aantal gesplete vrugte getoon indien die 2,4-D (enkel of in kombinasie met K) toegedien was direk na fisiologiese vrugval. Suksesvolle behandelings het ook 'n toename in vruggrootte tot gevolg gehad. Toediening van behandelings in Januarie en Februarie was oor die algemeen oneffektief. Verskille in kultivar sensitiwiteit teenoor 2,4-D is gevind, met vrugsplit in ‘Midknight’ Valencia wat verminder was deur die Januarie toediening van 2,4-D. Al die 2,4-D behandelings het vruggrootte van die lemoenkultivars verlaag. Daar is bevind dat die 10 mg.L-1 2,4-D, enkel of in kombinasie met K, ‘n toename in beide skildikte en –sterkte van ‘Marisol’ Clementine teweeg bring asook ʼn growwer skil. Behandelings met 2,4-D het vrugdeursnee en –lengte laat toeneem, wat ʼn verandering in vrugvorm tot gevolg gehad het, tot so ʼn mate dat vrugte minder geneig was om gesplete te wees. Behalwe vir ʼn moontlike verlaging in die sapinhoud (%) van vrugte, was daar geen noemenswaardige negatiewe effekte op interne en eksterne vrugkwaliteit nie. Die toediening van 10 mg.L-1 2,4-D direk na fisiologiese vrugval kan dus aanbeveel word op mandaryn kultivars wat geneig is tot vrugsplit.
The Citrus Academy
APA, Harvard, Vancouver, ISO, and other styles
10

Boukouvalas, Constantinos R. "Colour shade grading and its applications to visual inspection." Thesis, University of Surrey, 1996. http://epubs.surrey.ac.uk/843494/.

Full text
Abstract:
This thesis is concerned with the problem of colour shade grading for Industrial Inspection and attempts to find accurate and robust solutions to this problem. The application we are interested in, is the automation of the ceramic tiles manufacturing process so as to replace the human inspectors responsible for the quality control of the product. Therefore our aim is to perform the colour grading in a way which is consistent with what the human experts and subsequently the clients would perceive. First an overview of colour vision, colour measurement and colour constancy is given. Then a method that tackles the problem of colour grading of uniform and patterned surfaces is proposed. This method is the first step towards colour grading since it involves various corrections of the data, so as to provide the necessary precision for any further attempt. The problem of colour grading of random textures is then addressed. A method based on the comparison between colour histograms is proposed, and various statistical aspects involved in the comparison of distributions such as the colour histograms are discussed. Since the real-time implementation of any industrial inspection method should be taken into account, we use a space-effective method of storing colour histograms. Having solved the problem of colour grading for the majority of uniform and textured surfaces, we then try to optimise the performance of the proposed techniques, for cases where it fails. We attribute that to the fact that every electronic sensor captures colour and patterns in a way which only approximates what the human vision system would perceive. First we propose a method of perceptual colour grading of uniform surfaces, which transforms the camera data to data as they would have been recorded by the human eye. This method makes use of metameric data, to determine the relation between the human and the electronic sensors. We use various methods of generating metamers, and we show how the need of a spectrophotometer can be overcome. In a similar way, we propose a method of perceptual colour grading of random textures, which involves the restoration of the electronically acquired data and then their transformation to a colour space which expresses the way we perceive colour texture. We test both methods with real data, and we compare them with the non-perceptual ones. All the methods proposed in this thesis have been tested with real data, from the ceramic tiles manufacturing industry, previously colour graded by human inspectors. The consistency of the methods has been tested by using various sets of all sorts of tiles, and by repeating the acquisition and grading processes many times for every set of tiles. Further, these experiments have been carried out using different apparatuses, thus allowing us to draw conclusions about their quality and to make our methods as hardware independent as possible.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Fruit quality and grading"

1

P, Nichols John. Quality in U.S. fruit and vegetable marketing. College Station, TX: Dept. of Agricultural Economics, Texas Agricultural Experiment Station, Texas Agricultural Extension Service, Texas A&M University, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Jenks, Matthew A., and Penelope J. Bebeli. Breeding for fruit quality. Ames, Iowa: Wiley-Blackwell, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Jenks, Matthew A., and Penelope J. Bebeli, eds. Breeding for Fruit Quality. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470959350.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Jenks, Matthew A., and Penelope J. Bebeli. Breeding for fruit quality. Ames, Iowa: Wiley-Blackwell, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Wilson, Diana. Quality and the grading systems of Great Britain. [s.l: The author], 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Morgan, Jones Stephen David, ed. Quality and grading of carcases of meat animals. Boca Raton: CRC, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Tytgat, Stefaan H.A.J., ed. Grading and staging in gastroenterology. Stuttgart: Thieme, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Dale, Martin E. Butt log quality of trees in Pennsylvania oak stands. [Broomall, Pa.]: U.S. Dept. of Agriculture, Forest Service, Northeastern Station, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Dale, Martin E. Butt log quality of trees in Pennsylvania oak stands. [Broomall, Pa.]: U.S. Dept. of Agriculture, Forest Service, Northeastern Station, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Dale, Martin E. Butt log quality of trees in Pennsylvania oak stands. [Broomall, Pa.]: U.S. Dept. of Agriculture, Forest Service, Northeastern Forest Experiment Station, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Fruit quality and grading"

1

Sharif, Nadia, Burera Sajid, Neelma Munir, and Shagufta Naz. "Sensors for Sorting and Grading of Fruits and Vegetables." In Sensor-Based Quality Assessment Systems for Fruits and Vegetables, 57–77. Series statement: Postharvest biology and technology series: Apple Academic Press, 2020. http://dx.doi.org/10.1201/9781003084174-3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Prem Kumar, M. K., and A. Parkavi. "Quality Grading of the Fruits and Vegetables Using Image Processing Techniques and Machine Learning: A Review." In Lecture Notes in Electrical Engineering, 477–86. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3992-3_40.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Rahul Ganesh, P., R. Priyatharshini, M. Sarath Kumar, and A. Raj Kumar. "Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN." In Lecture Notes in Electrical Engineering, 49–57. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7169-3_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ligon, Ethan. "Quality and Grading Risk." In A Comprehensive Assessment of the Role of Risk in U.S. Agriculture, 353–69. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3583-3_16.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Issaoui, Manel, and Amélia M. Delgado. "Grading, Labeling and Standardization of Edible Oils." In Fruit Oils: Chemistry and Functionality, 9–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12473-1_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Johnson, Norman L., Samuel Kotz, and Xizhi Wu. "Stratified populations: grading." In Inspection Errors for Attributes in Quality Control, 181–91. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-3196-2_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Wardowski, Wilfred F., William Grierson, and Maurice Johnson. "Separation and Grading of Freeze-Damaged Fruit." In Fresh Citrus Fruits, 275–86. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-8792-3_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Holloway, Joseph William, and Jianping Wu. "Intrinsic Quality Factors: Carcass Quality Grading Systems." In Red Meat Science and Production, 3–14. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7860-7_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Àlvarez-Fernàndez, Ana, Javier Abadía, and Anunciación Abadía. "Iron Deficiency, Fruit Yield and Fruit Quality." In Iron Nutrition in Plants and Rhizospheric Microorganisms, 85–101. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-4743-6_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Dorais, M., A. P. Papadopoulos, and A. Gosselin. "Greenhouse Tomato Fruit Quality." In Horticultural Reviews, 239–319. Oxford, UK: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470650806.ch5.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Fruit quality and grading"

1

Paolo Gay, Remigio Berruto, and Pietro Piccarolo. "Fruit Color Assessment for Quality Grading Purposes." In 2002 Chicago, IL July 28-31, 2002. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2002. http://dx.doi.org/10.13031/2013.10549.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

S.Deulkar, Shweta, and Sunita S. Barve. "Feature based Fruit Quality Grading System using Support Vector Machine." In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2018. http://dx.doi.org/10.1109/rteict42901.2018.9012384.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Choi, Han Suk, Je Bong Cho, Sang Gyun Kim, and Hong Seok Choi. "A real-time smart fruit quality grading system classifying by external appearance and internal flavor factors." In 2018 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2018. http://dx.doi.org/10.1109/icit.2018.8352510.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Prabhu, V. S., Y. M. Blessy, S. Balasubramani, M. Harshini, J. Jayashree, and Guna Haneesha. "Automatic identification of ripening and quality grading of fruits using deep neural networks." In INTERNATIONAL CONFERENCE ON TRENDS IN CHEMICAL ENGINEERING 2021 (ICoTRiCE2021). AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0114510.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Ali, Mohammed A. H., and Kelvin Wong Thai. "Automated fruit grading system." In 2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation (ROMA). IEEE, 2017. http://dx.doi.org/10.1109/roma.2017.8231734.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Gaikwad, D., K. Karande, and H. Deshpande. "Pomegranate Fruit Diseases Identification and Grading." In International Conference on Communication and Signal Processing 2016 (ICCASP 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/iccasp-16.2017.96.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Deepa, P., and S. N. Geethalakshmi. "Improved Watershed Segmentation for Apple Fruit Grading." In 2011 International Conference on Process Automation, Control and Computing (PACC). IEEE, 2011. http://dx.doi.org/10.1109/pacc.2011.5979003.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Jun Qiao, Akira Sasao, Sakae Shibusawa, and Naoshi Kondo. "Mobile Fruit Grading Robot -Concept and prototype-." In 2004, Ottawa, Canada August 1 - 4, 2004. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2004. http://dx.doi.org/10.13031/2013.16725.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

"Computer Vision Based Mango Fruit Grading System." In International conference on Innovative Engineering Technologies. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e1214004.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Gan, Beiwen Chen, and Yanfen Gan. "Review on related technologies of fruit grading detection." In 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), edited by Ligu Zhu. SPIE, 2022. http://dx.doi.org/10.1117/12.2641497.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Fruit quality and grading"

1

Delwiche, Michael, Yoav Sarig, Antony Dodd, and Uri Peiper. Electronic Sorting and Grading of Fruit for Quality and Maturity. United States Department of Agriculture, March 1990. http://dx.doi.org/10.32747/1990.7695830.bard.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Delwiche, Michael, Yael Edan, and Yoav Sarig. An Inspection System for Sorting Fruit with Machine Vision. United States Department of Agriculture, March 1996. http://dx.doi.org/10.32747/1996.7612831.bard.

Full text
Abstract:
Concepts for real-time grading of fruits and vegetables were developed, including multi-spectral imaging with structured illumination to detect and distinguish surface defects from concavities. Based on these concepts, a single-lane conveyor and inspection system were designed and evaluated. Image processing algorithms were developed to inspect and grade large quasi-spherical fruits (peaches and apples) and smaller dried fruits (dates). Adjusting defect pixel thresholds to achieve a 25% error rate on good apples, classification errors for bruise, crack, and cut classes were 51%, 42%, and 46%, respectively. Comparable results for bruise, scar, and cut peach clases were 48%, 22%, and 58%, respectively. Acquiring more than two images of each fruit and using more than six lines of structured illumination per fruit would reduce sorting errors. Doing so, potential sorting error rates for bruise, crack, and cut apple classes were estimated to be 38%, 38%, and 33%, respectively. Similarly, potential error rates for the bruitse, scar, and cut peach classes were 9%, 3%, and 30%, respectively. Date size classification results were good: 68% within one size class and 98% within two size classes. Date quality classification results were not adequate due to the problem of blistering. Improved features were discussed. The most significant contribution of this research was the on-going collaboration with producers and equipment manufacturers, and the resulting transfer of research ideas to expedite the commercial application of machine vision for postharvest inspection and grading of agricultural products.
APA, Harvard, Vancouver, ISO, and other styles
3

Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

Full text
Abstract:
The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
APA, Harvard, Vancouver, ISO, and other styles
4

Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, October 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

Full text
Abstract:
The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the project, to develop and apply the two complementary methods for quality control of agricultural commodities. In Israel: An improved firmness testing system was developed and tested with tropical fruits. The new system included an instrumented fruit-bed of three flexible piezoelectric sensors and miniature electromagnetic hammers, which served as fruit support and low-energy excitation device, respectively. Resonant frequencies were detected for determination of firmness index. Two new acoustic parameters were developed for evaluation of fruit firmness and maturity: a dumping-ratio and a centeroid of the frequency response. Experiments were performed with avocado and mango fruits. The internal damping ratio, which may indicate fruit ripeness, increased monotonically with time, while resonant frequencies and firmness indices decreased with time. Fruit samples were tested daily by destructive penetration test. A fairy high correlation was found in tropical fruits between the penetration force and the new acoustic parameters; a lower correlation was found between this parameter and the conventional firmness index. Improved table-top firmness testing units, Firmalon, with data-logging system and on-line data analysis capacity have been built. The new device was used for the full-scale experiments in the next two years, ahead of the original program and BARD timetable. Close cooperation was initiated with local industry for development of both off-line and on-line sorting and quality control of more agricultural commodities. Firmalon units were produced and operated in major packaging houses in Israel, Belgium and Washington State, on mango and avocado, apples, pears, tomatoes, melons and some other fruits, to gain field experience with the new method. The accumulated experimental data from all these activities is still analyzed, to improve firmness sorting criteria and shelf-life predicting curves for the different fruits. The test program in commercial CA storage facilities in Washington State included seven apple varieties: Fuji, Braeburn, Gala, Granny Smith, Jonagold, Red Delicious, Golden Delicious, and D'Anjou pear variety. FI master-curves could be developed for the Braeburn, Gala, Granny Smith and Jonagold apples. These fruits showed a steady ripening process during the test period. Yet, more work should be conducted to reduce scattering of the data and to determine the confidence limits of the method. Nearly constant FI in Red Delicious and the fluctuations of FI in the Fuji apples should be re-examined. Three sets of experiment were performed with Flandria tomatoes. Despite the complex structure of the tomatoes, the acoustic method could be used for firmness evaluation and to follow the ripening evolution with time. Close agreement was achieved between the auction expert evaluation and that of the nondestructive acoustic test, where firmness index of 4.0 and more indicated grade-A tomatoes. More work is performed to refine the sorting algorithm and to develop a general ripening scale for automatic grading of tomatoes for the fresh fruit market. Galia melons were tested in Israel, in simulated export conditions. It was concluded that the Firmalon is capable of detecting the ripening of melons nondestructively, and sorted out the defective fruits from the export shipment. The cooperation with local industry resulted in development of automatic on-line prototype of the acoustic sensor, that may be incorporated with the export quality control system for melons. More interesting is the development of the remote firmness sensing method for sealed CA cool-rooms, where most of the full-year fruit yield in stored for off-season consumption. Hundreds of ripening monitor systems have been installed in major fruit storage facilities, and being evaluated now by the consumers. If successful, the new method may cause a major change in long-term fruit storage technology. More uses of the acoustic test method have been considered, for monitoring fruit maturity and harvest time, testing fruit samples or each individual fruit when entering the storage facilities, packaging house and auction, and in the supermarket. This approach may result in a full line of equipment for nondestructive quality control of fruits and vegetables, from the orchard or the greenhouse, through the entire sorting, grading and storage process, up to the consumer table. The developed technology offers a tool to determine the maturity of the fruits nondestructively by monitoring their acoustic response to mechanical impulse on the tree. A special device was built and preliminary tested in mango fruit. More development is needed to develop a portable, hand operated sensing method for this purpose. In North Carolina: Analysis method based on an Auto-Regressive (AR) model was developed for detecting the first resonance of fruit from their response to mechanical impulse. The algorithm included a routine that detects the first resonant frequency from as many sensors as possible. Experiments on Red Delicious apples were performed and their firmness was determined. The AR method allowed the detection of the first resonance. The method could be fast enough to be utilized in a real time sorting machine. Yet, further study is needed to look for improvement of the search algorithm of the methods. An impact contact-pressure measurement system and Neural Network (NN) identification method were developed to investigate the relationships between surface pressure distributions on selected fruits and their respective internal textural qualities. A piezoelectric dot-matrix pressure transducer was developed for the purpose of acquiring time-sampled pressure profiles during impact. The acquired data was transferred into a personal computer and accurate visualization of animated data were presented. Preliminary test with 10 apples has been performed. Measurement were made by the contact-pressure transducer in two different positions. Complementary measurements were made on the same apples by using the Firmalon and Magness Taylor (MT) testers. Three-layer neural network was designed. 2/3 of the contact-pressure data were used as training input data and corresponding MT data as training target data. The remaining data were used as NN checking data. Six samples randomly chosen from the ten measured samples and their corresponding Firmalon values were used as the NN training and target data, respectively. The remaining four samples' data were input to the NN. The NN results consistent with the Firmness Tester values. So, if more training data would be obtained, the output should be more accurate. In addition, the Firmness Tester values do not consistent with MT firmness tester values. The NN method developed in this study appears to be a useful tool to emulate the MT Firmness test results without destroying the apple samples. To get more accurate estimation of MT firmness a much larger training data set is required. When the larger sensitive area of the pressure sensor being developed in this project becomes available, the entire contact 'shape' will provide additional information and the neural network results would be more accurate. It has been shown that the impact information can be utilized in the determination of internal quality factors of fruit. Until now,
APA, Harvard, Vancouver, ISO, and other styles
5

Bennett, Alan B., Arthur A. Schaffer, Ilan Levin, Marina Petreikov, and Adi Doron-Faigenboim. Manipulating fruit chloroplasts as a strategy to improve fruit quality. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598148.bard.

Full text
Abstract:
The Original Objectives were modified and two were eliminated to reflect the experimental results: Objective 1 - Identify additional genetic variability in SlGLK2 and IPin wild, traditional and heirloom tomato varieties Objective 2 - Determine carbon balance and horticultural characteristics of isogenic lines expressing functional and non-functional alleles of GLKsand IP Background: The goal of the research was to understand the unique aspects of chloroplasts and photosynthesis in green fruit and the consequences of increasing the chloroplast capacity of green fruit for ripe fruit sugars, yield, flavor and nutrient qualities. By focusing on the regulation of chloroplast formation and development solely in fruit, our integrated knowledge of photosynthetic structures/organs could be broadened and the results of the work could impact the design of manipulations to optimize quality outputs for the agricultural fruit with enhanced sugars, nutrients and flavors. The project was based on the hypothesis that photosynthetic and non-photosynthetic plastid metabolism in green tomato fruit is controlled at a basal level by light for minimal energy requirements but fruit-specific genes regulate further development of robust chloroplasts in this organ. Our BARD project goals were to characterize and quantitate the photosynthesis and chloroplast derived products impacted by expression of a tomato Golden 2- like 2 transcription factor (US activities) in a diverse set of 31 heirloom tomato lines and examine the role of another potential regulator, the product of the Intense Pigment gene (IP activities). Using tomato Golden 2-like 2 and Intense Pigment, which was an undefined locus that leads to enhanced chloroplast development in green fruit, we sought to determine the benefits and costs of extensive chloroplast development in fruit prior to ripening. Major conclusions, solutions, achievements: Single nucleotide polymorphisms in the promoter, coding and intronicSlGLK2 sequences of 20 heirloom tomato lines were identified and three SlGLK2 promoter lineages were identified; two lineages also had striped fruit variants. Lines with striped fruit but no shoulders were not identified. Green fruit chlorophyll and ripe fruit soluble sugar levels were measured in 31 heirloom varieties and fruit size correlates with ripe fruit sugars but dark shoulders does not. A combination of fine mapping, recombinant generation, RNAseq expression and SNP calling all indicated that the proposed localization of a single locus IP on chr 10 was incorrect. Rather, the IP line harbored 11 separate introgressions from the S. chmielewskiparent, scattered throughout the genome. These introgressions harbored ~3% of the wild species genome and no recombinant consistently recovered the IP parental phenotype. The 11 introgressions were dissected into small combinations in segregating recombinant populations. Based on these analyses two QTL for Brix content were identified, accounting for the effect of increased Brix in the IP line. Scientific and agricultural implications: SlGLK2 sequence variation in heirloom tomato varieties has been identified and can be used to breed for differences in SlGLK2 expression and possibly in the green striped fruit phenotype. Two QTL for Brix content have been identified in the S. chmielewskiparental line and these can be used for increasing soluble solids contents in breeding programs.
APA, Harvard, Vancouver, ISO, and other styles
6

Schaffer, Arthur A., D. Mason Pharr, Joseph Burger, James D. Burton, and Eliezer Zamski. Aspects of Sugar Metabolism in Melon Fruit as Determinants of Fruit Quality. United States Department of Agriculture, September 1994. http://dx.doi.org/10.32747/1994.7568770.bard.

Full text
Abstract:
The cucurbit family, including melon, translocates the galactosyl-sucrose oligosaccharides, raffinose and stachyose, in addition to sucrose, from the source leaves to the fruit sink. The metabolism of these photoassimilates in the fruit sink controls fruit growth and development, including the horticulturally important phenomenon of sucrose accumulation, which determines melon fruit sweetness. During this research project we have characterized the complete pathway of galactosyl sucrose metabolism in developing fruit, from before anthesis until maturity. We have also compared the metabolic pathway in scurose accumulating genotypes, as compared to non-accumulating genotypes. Furthermore, we studied the pathway in different fruit tissues, in response to pollination, and also analyzed the response of the individual steps of the pathway to perturbations such as low temperature and leaf removal. The results of our studies have led to the conclusion that generally galactosyl-sucrose metabolism functions as a coordinately controlled pathway. In one case, as an immediate response to the absence of pollination, the activity of a single enzyme, UDPglu pyrophosphorylase, was drastically reduced. However, during young fruit development, sucrose accumulation, and in response to perturbations of the system, groups of enzymes, rather than single enzymes, respond in a concerted manner. Our research has characterized in detail the initial enzymes of galactosyl-sucrose metabolism, including the galactosidases, galactokinase and the UDPgal- and UDPglu pyrophosphorylases. We have discovered a novel alkaline a-galactoside which hydrolyzes both stachyose and reaffinose and thereby may have solved the dilemma of cytosolic-sucrose metabolism, since prior to this research there was no known alkaline a-galactosidase capable of hydrolyzing raffinose.
APA, Harvard, Vancouver, ISO, and other styles
7

Paran, Ilan, and Allen Van Deynze. Regulation of pepper fruit color, chloroplasts development and their importance in fruit quality. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598173.bard.

Full text
Abstract:
Pepper exhibits large natural variation in chlorophyll content in the immature fruit. To dissect the genetic and molecular basis of this variation, we conducted QTL mapping for chlorophyll content in a cross between light and dark green-fruited parents, PI 152225 and 1154. Two major QTLs, pc1 and pc10, that control chlorophyll content by modulation of chloroplast compartment size in a fruit-specific manner were detected in chromosomes 1 and 10, respectively. The pepper homolog of GOLDEN2- LIKE transcription factor (CaGLK2) was found as underlying pc10, similar to its effect on tomato fruit chloroplast development. A candidate gene for pc1was found as controlling chlorophyll content in pepper by the modulation of chloroplast size and number. Fine mapping of pc1 aided by bulked DNA and RNA-seq analyses enabled the identification of a zinc finger transcription factor LOL1 (LSD-One-Like 1) as a candidate gene underlying pc1. LOL1 is a positive regulator of oxidative stress- induced cell death in Arabidopsis. However, over expression of the rice ortholog resulted in an increase of chlorophyll content. Interestingly, CaAPRR2 that is linked to the QTL and was found to affect immature pepper fruit color in a previous study, did not have a significant effect on chlorophyll content in the present study. Verification of the candidate's function was done by generating CRISPR/Cas9 knockout mutants of the orthologues tomato gene, while its knockout experiment in pepper by genome editing is under progress. Phenotypic similarity as a consequence of disrupting the transcription factor in both pepper and tomato indicated its functional conservation in controlling chlorophyll content in the Solanaceae. A limited sequence diversity study indicated that null mutations in CaLOL1 and its putative interactorCaMIP1 are present in C. chinensebut not in C. annuum. Combinations of mutations in CaLOL1, CaMIP1, CaGLK2 and CaAPRR2 are required for the creation of the extreme variation in chlorophyll content in Capsicum.
APA, Harvard, Vancouver, ISO, and other styles
8

Dilley, Craig A., and Gail R. Nonnecke. Soil Quality Interest Survey of Iowa Small Fruit Growers. Ames: Iowa State University, Digital Repository, 2007. http://dx.doi.org/10.31274/farmprogressreports-180814-257.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Baugher, Tara A. Growth, yield and fruit quality of 'delicious' apple strains. West Virginia University Agricultural Experiment Station, January 1990. http://dx.doi.org/10.33915/agnic.596.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Baugher, Tara A. Growth, yield and fruit quality of 'delicious' apple strains. West Virginia University Agricultural Experiment Station, January 1990. http://dx.doi.org/10.33915/agnic.702.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Fruit quality and grading' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography