Academic literature on the topic 'Fruit imaging'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Fruit imaging.'
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 imaging"
Hansen, James D., Donald W. Schlaman, Ron P. Haff, and Wee L. Yee. "Potential Postharvest Use of Radiography to Detect Internal Pests in Deciduous Tree Fruits." Journal of Entomological Science 40, no. 3 (July 1, 2005): 255–62. http://dx.doi.org/10.18474/0749-8004-40.3.255.
Full textMaas, John L., and M. J. Line. "NUCLEAR MAGNETIC RESONANCE IMAGING OF FUNGAL INFECTIONS IN STRAWBERRY FRUIT." HortScience 30, no. 2 (April 1995): 192b—192. http://dx.doi.org/10.21273/hortsci.30.2.192b.
Full textJiang, Ying Lan, Ruo Yu Zhang, Jie Yu, Wan Chao Hu, and Zhang Tao Yin. "Detection of Infected Tephritidae Citrus Fruit Based on Hyperspectral Imaging and Two-Band Ratio Algorithm." Advanced Materials Research 311-313 (August 2011): 1501–4. http://dx.doi.org/10.4028/www.scientific.net/amr.311-313.1501.
Full textGarillos-Manliguez, Cinmayii A., and John Y. Chiang. "Multimodal Deep Learning and Visible-Light and Hyperspectral Imaging for Fruit Maturity Estimation." Sensors 21, no. 4 (February 11, 2021): 1288. http://dx.doi.org/10.3390/s21041288.
Full textCornelissen, Tom, Patrik Verstreken, and Wim Vandenberghe. "Imaging mitophagy in the fruit fly." Autophagy 14, no. 9 (August 2, 2018): 1656–57. http://dx.doi.org/10.1080/15548627.2018.1496720.
Full textG., ANNAPOORANI. "A Survey on Application of Hyperspectral Imaging Techniques in Assessing Fruit Quality." Journal of Research on the Lepidoptera 51, no. 2 (May 15, 2020): 303–18. http://dx.doi.org/10.36872/lepi/v51i2/301098.
Full textSuherly, Tomy, and Minarni Shiddiq. "Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 3 (July 20, 2020): 535. http://dx.doi.org/10.30865/mib.v4i3.2144.
Full textLin, W. C., J. W. Hall, and A. Klieber. "Video Imaging for Quantifying Cucumber Fruit Color." HortTechnology 3, no. 4 (October 1993): 436–39. http://dx.doi.org/10.21273/horttech.3.4.436.
Full textKurita, Keisuke, Yuta Miyoshi, Yuto Nagao, Mitsutaka Yamaguchi, Nobuo Suzui, Yong-Gen Yin, Satomi Ishii, et al. "Fruit PET: 3-D imaging of carbon distribution in fruit using OpenPET." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 954 (February 2020): 161843. http://dx.doi.org/10.1016/j.nima.2019.01.069.
Full textAbbas, Amel H., and Marwa A. Shamel. "Identify and Classify Normal and Defects of Prunus_armeniaca Using Imaging Techniques." Kurdistan Journal of Applied Research 2, no. 3 (August 27, 2017): 1–6. http://dx.doi.org/10.24017/science.2017.3.11.
Full textDissertations / Theses on the topic "Fruit imaging"
Boyer, Jacob, Janos C. Keresztes, Wouter Saeys, and John Koshel. "An automated imaging BRDF polarimeter for fruit quality inspection." SPIE-INT SOC OPTICAL ENGINEERING, 2016. http://hdl.handle.net/10150/622517.
Full textCheng, Xuemei. "Hyperspectral imaging and pattern recognition technologies for real time fruit safety and quality inspection." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/2154.
Full textThesis research directed by: Biological Resources Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Munera, Picazo Sandra María. "Application of hyperspectral imaging combined with chemometrics for the non-destructive evaluation of the quality of fruit in postharvest." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/125954.
Full text[CAT] L'objectiu de la present tesi doctoral se centra en avaluar la capacitat de la imatge hiperespectral en el rang visible i infraroig pròxim, en combinació amb mètodes quimiomètrics, per a l'avaluació de la qualitat de la fruita en post collita de manera eficaç i sostenible. A aquest efecte, es presenten diferents estudis en els quals s'avalua la qualitat d'algunes fruites que pel seu valor econòmic, estratègic o social, són d'especial importància a la Comunitat Valenciana com són el caqui 'Rojo Brillante', la magrana 'Mollar de Elche', el nispro 'Algerie' o diferents cultivares de nectarina. En primer lloc es va dur a terme la monitorització de la qualitat post collita de nectarines 'Big Top' i 'Magique' per mitjà d'imatge hiperespectral en reflectància i trasnmitancia. Així mateix es va avaluar la transmitància per a la detecció d'ossos oberts. Es va dur a terme també un estudi per distingir els cultivares 'Big Top' i 'Diamond Ray', els quals posseeixen un aspecte molt semblant però sabor diferent. Pel que fa al caqui 'Rojo Brillante', la imatge hiperespectral va ser estudiada d'una banda per a monitoritzar la seua maduresa, i per un altre costat per avaluar l'astringència, que ha de ser completament eliminada abans de la seua comercialització. Les propietats fisicoquímiques de la magrana 'Mollar de Elche' van ser avaluades per la imatge de color i hiperespectral durant la seua maduresa usant la informació de la fruita intacta i els arils. Finalment, aquesta tècnica es va fer servir per caracteritzar i identificar els defectes interns i externs del nispro 'Algerie'. En la predicció dels índexs de qualitat IQI i RPI usant imatge en reflectància com en trasnmitancia es van obtindre valors de R2 al voltant de 0,90 i en la discriminació per fermesa una precisió entorn del 95,0 % utilitzant longituds d'ona seleccionades. Pel que fa a la detecció d'ossos oberts, l'ús de la imatge hiperespectral en transmitància va obtindre un 93,5 % classificació correcta de fruites amb os normal i 100 % amb os obert usant models PLS-DA i 7 longituds d'ona. Els resultats obtinguts en la classificació dels cultivares 'Big Top' i 'Diamond Ray' van mostrar una fiabilitat superior al 96,0 % per mitjà de l'ús de models PLS-DA i 14 longituds d'ona, superant a la imatge de color (56,9 %) i a un panell sensorial entrenat (54,5 %). Quant al caqui, els resultats obtinguts van indicar que és possible distingir entre tres estats de maduresa amb una precisió del 96,0 % usant models QDA i es va predir la seua fermesa obtenint un valor de R2 de 0,80 usant PLS-R. Pel que fa a l'astringència, es van dur a terme dos estudis similars en què el primer es va discriminar la fruita d'acord al temps de tractament amb altes concentracions de CO2 amb una precisió al voltant del 95,0 % usant QDA. En el segon, es va discriminar la fruita d'acord a un valor de contingut en tanins (0,04 %) i es va determinar quina part de la fruita era millor per a realitzar aquesta discriminació. Així es va obtindre una precisió del 86,9 % usant la zona mitjana i 23 longituds d'ona. Els resultats obtinguts per la magrana van indicar que la imatge de color i hiperespectral posseïxen una precisió semblant a la predicció de les propietats fisicoquímiques usant PLS-R i la informació de la fruita intacta. No obstant això, quan es va usar la informació dels arils, la imatge hiperespectral va ser més precisa. Quant a la discriminació de l'estat de maduresa usant PLS-DA, la imatge hiperespectral va oferir major precisió (95,0 %) usant la informació de la fruita intacta i del 100 % usant la dels arils. Finalment, els resultats obtinguts pel nispro indiquen que la imatge hiperespectral juntament amb el mètode de classificació XGBOOST va poder discriminar entre mostres amb i sense defectes amb una precisió del 97,5 % i entre mostres sense defectes o amb defectes interns o externs amb una precisió del 96,7 %. A més, va ser possible distingir entre
[EN] The objective of this doctoral thesis is to evaluate the potential of the hyperspectral imaging in the visible and near infrared range in combination with chemometrics for the assessment of the postharvest quality of fruit in a non-destructive, efficient and sustainable manner. To this end, different studies are presented in which the quality of some fruits is evaluated. Due to their economic, strategic or social value, the selected fruits are of special importance in the Valencian Community, such as Persimmon 'Rojo Brillante', the pomegranate 'Mollar de Elche', the loquat 'Algerie' or different nectarine cultivars. First, the quality monitoring of 'Big Top' and 'Magique' nectarines was carried out using reflectance and transmittance images. At the same time, transmittance was evaluated for the detection of split pit. In addition, a classification was performed to distinguish the 'Big Top' and 'Diamond Ray' cultivars, which look very similar but have different flavour. Whereas that for the 'Rojo Brillante' persimmon, the hyperspectral imaging was studied on the one hand to monitor its maturity, and on the other hand to evaluate the astringency of this fruit, which must be completely eliminated before its commercialization. The physicochemical properties of the 'Mollar de Elche' pomegranate were evaluated by means of hyperspectral and colour imaging during its maturity using the information from the intact fruit and arils. Finally, this technique was used to characterise and identify the internal and external defects of the 'Algerie' loquat. In the prediction of the IQI and RPI quality indexes using reflectance and transmittance images, R2 values around 0.90 were obtained and in the discrimination according to firmness, accuracy around 95.0 % using selected wavelengths was obtained. Regarding the split pit detection, the use of the hyperspectral image in transmittance mode obtained a 93.5 % of fruits with normal bone correctly classified and 100% with split pit using PLS-DA models and 7 wavelengths. The results obtained in the classification of 'Big Top' and 'Diamond Ray' fruits show accuracy higher than 96.0 % by using PLS-DA models and 14 selected wavelengths, higher than the obtained with colour image (56.9 %) and a trained panel (54.5 %). According to persimmon, the results obtained indicated that it is possible to distinguish between three states of maturity with an accuracy of 96.0 % using QDA models and its firmness was predicted obtaining a R2 value of 0.80 using PLS-R. Regarding astringency, two similar studies were carried out. In the first study, the fruit was classified according to the time of treatment with high concentrations of CO2 with a precision of around 95.0 % using QDA. In the second, the fruit was discriminated according to a threshold value of soluble tannins (0.04 %) and was determined what fruit area was better to perform this discrimination. Thus, an accuracy of 86.9 % was obtained using the middle area and 23 wavelengths. The results obtained for the pomegranate indicated that the use of colour and hyperspectral images have a similar precision in the prediction of physicochemical properties using PLS-R and the intact fruit information. However, when the information from the arils was used, the hyperspectral image was more accurate. Regarding the discrimination by the state of maturity using PLS-DA, the hyperspectral image offered greater precision, of 95.0 % using the information from the intact fruit and 100 % using that from the arils. Finally, the results obtained for the 'Algerie' loquat indicated that the hyperspectral image with the XGBOOST classification method could discriminate between sound samples and samples with defects with accuracy of 97.5 % and between sound samples or samples with internal or external defects with an accuracy of 96.7 %. It was also possible to distinguish between the different defects with an accuracy of 95.9 %.
Munera Picazo, SM. (2019). Application of hyperspectral imaging combined with chemometrics for the non-destructive evaluation of the quality of fruit in postharvest [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/125954
TESIS
Long, Robert Llewellyn, and bizarrealong@hotmail com. "Improving fruit soluble solids content in melon (Cucumis melo L.) (reticulatus group) in the Australian production system." Central Queensland University. Biological and Environmental Science, 2005. http://library-resources.cqu.edu.au./thesis/adt-QCQU/public/adt-QCQU20051019.144749.
Full textKalaj, Yousef Rezaei. "Effects of preharvest factors and postharvest treatments on fruit quality of Prunus domestica L." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17458.
Full textPlum consumption does not meet its potential, most probably because of a non-uniform fruit quality and lack of fully-mature fruit. It is necessary to manage preharvest conditions such as crop load and soil properties optimally in order to obtain high quality plums and to harvest the fruit in ripe stage. In this study, (1) the effects of soil ECa, crop load and maximum daily trunk shrinkage (MDS) on various fruit quality parameters of two European plum cultivars ''Jojo'' und ''Tophit plus'') (2) the internal and external fruit quality as it relates to harvest time were investigated. The investigation of plums was carried out in an experimental orchard in 2011, 2012 and 2013. Fruit of selected trees were sampled and subjected to laboratory measurements three times before and at the commercial harvest. At the commercial harvest, plums were stored at 2 °C and 90% RH for up to 28 days plus 2 days at 20 °C. During storage, fruit of each treatment were sampled after 0, 7, 14, 21, 28 and 30 days in order to analyse the physicochemical quality. In addition, the optical properties of samples were non-destructively evaluated through laser light backscattering imaging (LLBI). Fruit from low crop load trees grown under low ECa had the highest SSC and dry matter content, while those from low crop load trees under high ECa showed the highest fresh mass in 2013. Moreover, low MDS trees had lower total fruit yield, and fruit had higher transpiration, lower SSC, and dry matter content than those grown on trees with high MDS. Fruit quality was best when plums had been harvested late, preferably at the 3rd harvest date (137 DAFB) in this study. These fruit had the highest fresh mass and lowest transpiration. Furthermore, the results of LLBI measured at 532 nm and 785 nm showed an encouraging potential to predict quality parameters of plums such as anthocyanin content and fruit firmness.
Momin, Md Abdul. "Fluorescence Imaging for Defect Inspection of Citrus Fruits." Kyoto University, 2013. http://hdl.handle.net/2433/175068.
Full text0048
新制・課程博士
博士(農学)
甲第17639号
農博第2001号
新制||農||1012(附属図書館)
学位論文||H25||N4760(農学部図書室)
30405
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, 准教授 小川 雄一, 教授 清水 浩
学位規則第4条第1項該当
Matsimbe, Sofrimento Fenias Savanto. "Utilização de características ópticas para estimar o teor de óleo e volume do mesocarpo nos frutos de macaúba." Universidade Federal de Viçosa, 2012. http://locus.ufv.br/handle/123456789/4571.
Full textConselho Nacional de Desenvolvimento Científico e Tecnológico
The macaúba [Acrocomia aculeata (Jacq.) Lodd. Ex Mart.] is a rustic oilseed, with high productivity and multiple potential, which is strongly demanded in the food, cosmetic, and especially the energy industries, due of its suitability for biodiesel production. However, despite the enormous potential, the exploitation of macaw palm still boils down to foraging. Studies aiming at their sustainable use and the resulting domestication of the species are ignorant, because of the lack of practical and efficient methods to support breeding programs on genotypes selections. The main objective of this study was to develop and propose methods to estimate the oil content and volume of the mesocarp in macaw palm fruit using optical characteristics. For methodologies evaluation two assays were carried out. In the first, 420 samples were used to develop calibration model to predict oil content of mesocarp using visible and near infrared spectrometry. The soxhlet method was used as reference. In the second, consisted of 20 samples, were developed imaging algorithms to estimate the mesocarp volume, and as a reference was used water displacement method. In the first assay the developed model showed consistent results in the calibration and validation sets, and it s potentially feasible for preliminary selections and characterization of genotypes intended macaw palm improvement. In the second, were developed two algorithms, one considering each fruit as sphere and another one using ellipsoid approximation. The results show that the algorithms can be used in the pre and post-harvest sector and to make genotypes selection in macaw palm breeding programs.
A macaúba [Acrocomia aculeata (Jacq.) Lodd. Ex Mart.] é uma oleaginosa rústica, de alta produtividade e múltiplas potencialidades, com grande demanda nas indústrias alimentícia, cosmética e, principalmente, a energética, em função da adequação para produção do biodiesel. Contudo, apesar do enorme potencial, a exploração da macaúba ainda resume-se ao extrativismo. Os estudos visando a sua domesticação e o consequente uso sustentável da espécie são insipientes, em função da falta de métodos práticos e eficientes que possam subsidiar os programas de melhoramento na seleção de genótipos de interesse. Assim, o objetivo deste trabalho foi desenvolver e propor métodos para estimar o teor de óleo e volume do mesocarpo no fruto da macaúba utilizando características ópticas. Para avaliação das metodologias foram conduzidos dois ensaios. No primeiro foram utilizadas 420 amostras para desenvolver um modelo de predição do teor de óleo do mesocarpo usando a espectrometria do visível e infravermelho próximo. Como referência foi usado o método soxhlet. No segundo, composto por 20 amostras, foram desenvolvidos algoritmos do processamento de imagens digitais para estimar o volume do mesocarpo, e como referência empregou-se o método do deslocamento da coluna da água. No primeiro ensaio, o modelo desenvolvido apresentou resultados consistentes na calibração e validação, sendo potencialmente viável para a caracterização e pré-seleção de genótipos visando o melhoramento da macaúba. No segundo ensaio, foram desenvolvidos dois algoritmos, um considerando cada fruto como uma esfera e outro por aproximação a um elipsóide. Os resultados permitem concluir que os algoritmos podem ser usados nas áreas da pré e pós-colheita e na seleção de genótipos em programas do melhoramento da macaúba.
Perre, Paula. "Caracterização de três espécies do grupo fraterculus (Diptera, Tephritidae, Anastrepha) por meio da análise de imagens e morfometria." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/11/11146/tde-24042012-100427/.
Full textThe fruit flies are pests of quarantine importance, among which stand out the genus Anastrepha. Despite of many study, the taxonomy of some groups of the genus is still not adequately resolved. The correct identification of fraterculus group requires practice/knowledge and the use of a number of techniques. Thus, this study proposes to test the efficiency of two techniques in the identification of three species (A. fraterculus, A. obliqua e A. sororcula) and in the identification of A. fraterculus specimens related to three hosts (guava, loquat and peach). Were tested the techniques of image analysis, for the fists time in fruit flies, and of morphometry (conventional for the aculeus and geometric for the wings). By image analysis, very high accuracies were obtained for species identification, both by the images of the wings and aculeus, with average accuracy of 87,8% and 90,6%, respectively. Regarding the association of A. fraterculus with the hosts, also were obtained positive results with image analysis (means of 85,3% of accuracy on images of wings and 88,3% on images of aculeus). The geometric morphometric of wings, using 17 landmarks, indicated differences in the wings shape of the individuals of each species, separating them into distinct groups successfully. Regarding the association of A. fraterculus with the hosts, the groups obtained were not very distinct, specially in relation to individuals from peach. The multivariate morphometric of seven measures of the aculeus tip, by linear discriminant analysis (LDA), also indicated differences in the species, separating them in three groups. By cluster analysis (UPGMA), was noted that A, fraterculus and A. obliqua form a group and A. soroscula is isolated, suggesting that the measures that most influenced the grouping of the species were the length of the serrate part (L3 and L7). In the host association, were obtained positives results with LDA, however, was not possible separate the populations of the same host by UPGMA. Both techniques were effectives in separating the species and in the association of A. fraterculus with their hosts, showing that the host fruit can influence in the color and shape of the wing and in the shape of the aculeus in the three species of the group fraterculus.
Maldonado, Júnior Walter [UNESP]. "Estimativa do número de frutos verdes em laranjeiras com o uso de imagens digitais." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/136455.
Full textApproved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-03-30T11:37:55Z (GMT) No. of bitstreams: 1 maldonadojunior_w_dr_jabo.pdf: 75187969 bytes, checksum: ed5b4271338552ed5f58e72f73d7073d (MD5)
Made available in DSpace on 2016-03-30T11:37:55Z (GMT). No. of bitstreams: 1 maldonadojunior_w_dr_jabo.pdf: 75187969 bytes, checksum: ed5b4271338552ed5f58e72f73d7073d (MD5) Previous issue date: 2016-02-22
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
A estimativa da produtividade é um fator importante no planejamento de um processo produtivo. No caso dos citros, pode colaborar com o gerenciamento do processo industrial e servir como orientação para os produtores, apresentando papel decisivo no mercado do produto e no manejo de tratos culturais. Vários estudos de técnicas para estimativa da produção da cultura vêm sendo realizados mas ainda apresentando limitações. Devido à correlação entre o número de frutos visíveis na imagem de uma planta e o número real de frutos na mesma já apontada em estudos anteriores, foi desenvolvido um método de amostragem automático e não-destrutivo, por meio da extração das características de frutos verdes em imagens digitais. Utilizou-se uma combinação das técnicas de conversão do modelo de cores, limiarização, equalização do histograma de níveis de cinza, filtragem espacial com os operadores de Laplace e Sobel e suavização gaussiana. Além disso, foi desenvolvido e testado um algoritmo para o reconhecimento e contagem dos frutos nessas imagens, com taxas de detecção de falso-positivos de 3\% em imagens de boa qualidade. É possível se estimar a média do número de frutos visíveis por planta com um erro tolerado de 5\% com até 46 imagens e em aproximadamente 8 minutos, sem nenhuma interação humana. A ausência de flash e a incidência de luz solar direta sobre a planta podem prejudicar consideravelmente o desempenho do algoritmo.
Yield estimation is an important factor in a production process planning. In the case of citrus orchards, can be useful for processing plants management and as guidance for farmers, showing a decisive role in the product market strategies and cultivation practices. Several techniques are being studied for estimating citrus crop yield, but still presenting significant limitations. On the basis of the known correlation between the number of visible fruits in a digital image and the total of fruits present in an orange tree, an automatic and non-destructive method for green fruit feature extraction was developed with a combination of the techniques of color model conversion, thresholding, histogram equalization, spatial filtering with Laplace and Sobel operators and gaussian blur. In addition, we built and tested an algorithm to recognize and count the fruits, with detection rates of false-positives of 3\% for images acquired in good conditions. It is possible to estimate the mean number of visible fruits in the trees within a tolerated error of 5\% with up to 46 images and taking approximately 8 minutes without any human interaction. The absence of flash light or the direct incidence of solar light on the plant can significantly detract the algorithm results.
CNPq: 140600/2013-2
Martinsen, Paul. "Quantitative near-infrared imaging spectroscopy of fruit." 1999. http://hdl.handle.net/2292/1945.
Full textBooks on the topic "Fruit imaging"
How to grow more vegetables: (and fruits, nuts, berries, grains, and other crops) than you ever thought possible on less land than you can imagine. 8th ed. Berkeley: Ten Speed Press, 2012.
Find full textKendrick, Robert L. Fruits of the Cross. University of California Press, 2018. http://dx.doi.org/10.1525/california/9780520297579.001.0001.
Full textZaz'Gasy, Editions. Mon Premier Imagier Malgache des FRUITS and LEGUMES / Ny Bokintsariko Voalohany NY VOANKAZO SY NY LEGIOMA / My First Malagasy Picture Book FRUITS and VEGETABLES. Independently Published, 2020.
Find full textJeavons, John. How to Grow More Vegetables: And Fruits, Nuts, Berries, Grains, and Other Crops Than You Ever Thought Possible on Less Land Than You Can Imagine. 6th ed. Ten Speed Press, 2002.
Find full textBook chapters on the topic "Fruit imaging"
Ye, Xujun, and Kenshi Sakai. "Fruit Yield Estimation Through Multispectral Imaging." In Advances in Citrus Nutrition, 453–73. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4171-3_30.
Full textMusse, Maja, and Henk Van As. "NMR Imaging of Air Spaces and Metabolites in Fruit and Vegetables." In Modern Magnetic Resonance, 1–15. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28275-6_130-1.
Full textMusse, Maja, and Henk Van As. "NMR Imaging of Air Spaces and Metabolites in Fruit and Vegetables." In Modern Magnetic Resonance, 1765–79. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-28388-3_130.
Full textLin, Tzu-En. "Multiple SECM Mapping of Tyrosinase in Micro-contact Printed Fruit Samples on Polyvinylidene Fluoride Membrane." In Soft Probes for Bio-electrochemical Imaging, 37–52. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05758-9_3.
Full textKhairy, Khaled, William C. Lemon, Fernando Amat, and Philipp J. Keller. "Light Sheet-Based Imaging and Analysis of Early Embryogenesis in the Fruit Fly." In Methods in Molecular Biology, 79–97. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1164-6_6.
Full textDipt, Shubham, Thomas Riemensperger, and André Fiala. "Optical Calcium Imaging Using DNA-Encoded Fluorescence Sensors in Transgenic Fruit Flies, Drosophila melanogaster." In Methods in Molecular Biology, 195–206. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-622-1_15.
Full textNedbal, Ladislav, and John Whitmarsh. "Chlorophyll Fluorescence Imaging of Leaves and Fruits." In Chlorophyll a Fluorescence, 389–407. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-3218-9_14.
Full textSharma, R. R., S. Vijay Rakesh Reddy, and G. Gajanan. "X-Ray Imaging for Quality Detection in Fruits and Vegetables." In Sensor-Based Quality Assessment Systems for Fruits and Vegetables, 231–52. Series statement: Postharvest biology and technology series: Apple Academic Press, 2020. http://dx.doi.org/10.1201/9781003084174-9.
Full textSofia Jennifer, J., T. Sree Sharmila, H. Sairam, and T. S. Kishorkrishna. "Detection of Bruises and Flaws in Fruits Using Thermal Imaging." In Springer Proceedings in Mathematics & Statistics, 529–35. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4646-8_41.
Full textPaloutzian, Raymond F., and Katelyn J. Mukai. "Believing, Remembering, and Imagining: The Roots and Fruits of Meanings Made and Remade." In Processes of Believing: The Acquisition, Maintenance, and Change in Creditions, 39–49. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50924-2_3.
Full textConference papers on the topic "Fruit imaging"
., Swetha, Santhosh Chidangil, Tanvi Karpate, and Anand Asundi. "Fruit ripening using hyper spectral imaging." In Fifth International Conference on Optical and Photonics Engineering, edited by Anand K. Asundi. SPIE, 2017. http://dx.doi.org/10.1117/12.2270888.
Full textGurupatham, Sathish K., and Carson Wiles. "Thermal Imaging Technique to Minimize the Wastage of Fruits." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10034.
Full textZhang, Dong, Dah-Jye Lee, and Alok Desai. "Color back projection for fruit maturity evaluation." In IS&T/SPIE Electronic Imaging, edited by Juha Röning and David Casasent. SPIE, 2014. http://dx.doi.org/10.1117/12.2045374.
Full textGurupatham, Sathish K., Erhan Ilksoy, Nick Jacob, Kevin Van Der Horn, and Fahad Fahad. "Fruit Ripeness Estimation for Avocado Using Thermal Imaging." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86290.
Full textSumriddetchkajorn, Sarun, and Yuttana Intaravanne. "Two-dimensional fruit ripeness estimation using thermal imaging." In International Conference on Photonics Solutions 2013, edited by Prathan Buranasiri and Sarun Sumriddetchkajorn. SPIE, 2013. http://dx.doi.org/10.1117/12.2019654.
Full textZhang, Dong, Dah-Jye Lee, and Alok Desai. "Using short-wave infrared imaging for fruit quality evaluation." In IS&T/SPIE Electronic Imaging, edited by Juha Röning and David Casasent. SPIE, 2014. http://dx.doi.org/10.1117/12.2045406.
Full textXia, Peng, Yasunori Ito, Yasuhiro Awatsuji, Shogo Ura, Kenzo Nishio, and Osamu Matoba. "Spectroscopic measurement for fruit using spectral estimation digital holography." In Digital Holography and Three-Dimensional Imaging. Washington, D.C.: OSA, 2014. http://dx.doi.org/10.1364/dh.2014.dw3b.6.
Full textSinha, Supriyo, Liang Liang, Eric TW Ho, Liqun Luo, Thomas M. Baer, and Mark J. Schnitzer. "Laser microsurgery for two-photon imaging in fruit flies." In Novel Techniques in Microscopy. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/ntm.2011.nmc6.
Full textBoyer, Jacob, Janos C. Keresztes, Wouter Saeys, and John Koshel. "An automated imaging BRDF polarimeter for fruit quality inspection." In SPIE Optical Engineering + Applications, edited by Arthur J. Davis, Cornelius F. Hahlweg, and Joseph R. Mulley. SPIE, 2016. http://dx.doi.org/10.1117/12.2239008.
Full textGhavami, Navid, Ioannis Sotiriou, and Panagiotis Kosmas. "Limited-view Prototype Design for Radar-based Fruit Imaging." In 2020 14th European Conference on Antennas and Propagation (EuCAP). IEEE, 2020. http://dx.doi.org/10.23919/eucap48036.2020.9135213.
Full text