published_or_final_version / Geography and Geology / Master / Master of Philosophy

Depuis quelques années, l’évolution des techniques d’acquisition a entraîné une généralisation de l’utilisation d’objets 3D très dense, représentés par des nuages de points de plusieurs millions de sommets. Au vu de la complexité de ces données, il est souvent nécessaire de les analyser pour en extraire les structures les plus pertinentes, potentiellement définies à plusieurs échelles. Parmi les nombreuses méthodes traditionnellement utilisées pour analyser des signaux numériques, l’analyse dite scale-space est aujourd’hui un standard pour l’étude des courbes et des images. Cependant, son adaptation aux données 3D pose des problèmes d’instabilité et nécessite une information de connectivité, qui n’est pas directement définie dans les cas des nuages de points. Dans cette thèse, nous présentons une suite d’outils mathématiques pour l’analyse des objets 3D, sous le nom de Growing Least Squares (GLS). Nous proposons de représenter la géométrie décrite par un nuage de points via une primitive du second ordre ajustée par une minimisation aux moindres carrés, et cela à pour plusieurs échelles. Cette description est ensuite derivée analytiquement pour extraire de manière continue les structures les plus pertinentes à la fois en espace et en échelle. Nous montrons par plusieurs exemples et comparaisons que cette représentation et les outils associés définissent une solution efficace pour l’analyse des nuages de points à plusieurs échelles. Un défi intéressant est l’analyse d’objets 3D acquis dans le cadre de l’étude du patrimoine culturel. Dans cette thèse, nous nous étudions les données générées par l’acquisition des fragments des statues entourant par le passé le Phare d’Alexandrie, Septième Merveille du Monde. Plus précisément, nous nous intéressons au réassemblage d’objets fracturés en peu de fragments (une dizaine), mais avec de nombreuses parties manquantes ou fortement dégradées par l’action du temps. Nous proposons un formalisme pour la conception de systèmes d’assemblage virtuel semi-automatiques, permettant de combiner à la fois les connaissances des archéologues et la précision des algorithmes d’assemblage. Nous présentons deux systèmes basés sur cette conception, et nous montrons leur efficacité dans des cas concrets. / Over the last decades, the evolution of acquisition techniques yields the generalization of detailed 3D objects, represented as huge point sets composed of millions of vertices. The complexity of the involved data often requires to analyze them for the extraction and characterization of pertinent structures, which are potentially defined at multiple scales. Amongthe wide variety of methods proposed to analyze digital signals, the scale-space analysis istoday a standard for the study of 2D curves and images. However, its adaptation to 3D dataleads to instabilities and requires connectivity information, which is not directly availablewhen dealing with point sets.In this thesis, we present a new multi-scale analysis framework that we call the GrowingLeast Squares (GLS). It consists of a robust local geometric descriptor that can be evaluatedon point sets at multiple scales using an efficient second-order fitting procedure. We proposeto analytically differentiate this descriptor to extract continuously the pertinent structuresin scale-space. We show that this representation and the associated toolbox define an effi-cient way to analyze 3D objects represented as point sets at multiple scales. To this end, we demonstrate its relevance in various application scenarios.A challenging application is the analysis of acquired 3D objects coming from the CulturalHeritage field. In this thesis, we study a real-world dataset composed of the fragments ofthe statues that were surrounding the legendary Alexandria Lighthouse. In particular, wefocus on the problem of fractured object reassembly, consisting of few fragments (up to aboutten), but with missing parts due to erosion or deterioration. We propose a semi-automaticformalism to combine both the archaeologist’s knowledge and the accuracy of geometricmatching algorithms during the reassembly process. We use it to design two systems, andwe show their efficiency in concrete cases.

No description available.

Thesis (M.S.)--University of Wisconsin, 1959. / Extension Repository Collection. Typescript (carbon copy). Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 176-178).

The need for energy is constantly increasing, and fossil fuels are both harmful and neither everlasting. This puts higher demand on the production of renewable energy. In Sweden the production of renewable energy is relatively good, however the solar power is not utilized enough. The planning phase for the purpose of solar installation is a lengthy process, and will over the coming years need to be more efficient. Several different methods are used for planning today, with the help of geographic data in the form of ortophotos. Multiple studies today have successfully achieved the segmentation of roofs, which then is used in this process. The studies that have achieved this, has used software that is not widely available to private individuals and thus the information regarding precise solar potential assesments are unavailable to them. This study has not found a similar implementation which operates in a semi-automatic manner as a webservice, on the Internet which is the most used platform. Therefore this study will investigate how roofs can be segmented and drawn on a map in a web application, in an automated manner with image processing. This is accomplished using the region growing algorithm. The result is produced by a number of tests on a variation of roof designs and colors. Validation of the results are done visually, when the segmentation is drawn onto the map. In most cases the algorithm has not been able to correctly identify and segment parts of the roof, and in no case has been successful to segment an entire roof. This was largely because of lack of data, and shadow disturbance in the images used. The result shows the method could work in a better way, using more data and developing the image processing further. It also shows how easily this type of method can be integrated with a webmap. / Behovet av energi ökar konstant, och de fossila bränslena är både skadliga för miljön och inte heller föreviga. Detta ställer större krav på produktionen av förnybar energi. I Sverige produceras förnybar energi relativt bra, men solkraften är inte utnyttjad tillräckligt. Planeringsfasen i detta är väldigt stor, och kommer med stor sannolikhet behöva effektiviseras de närmaste åren. Flera olika metoder används idag, man utgår oftast från geografiska data i form av ortofoton. Flertalet arbeten har tidigare lyckats att korrekt segmentera takytor, för att sedan användas som underlag. De arbeten som lyckats med detta, har ofta gjort det i sådana program att det blir svårt för privatpersoner att ta del av informationen. Informationen innefattar en utförlig utvärdering av ett taks potential för solkraft. Detta arbete har inte hittat någon liknande implementation i form av webbtjänst där denna process är semi-automatisk, det vill saga på Internet, vilket är den mest använda plattformen. I detta arbete undersöks därför hur takytor kan segmenteras och ritas ut i en webbapplikation med tillhörande karta, på ett nästan helt automatiserat sätt med bildbehandling. Detta med hjälp av algoritmen region growing på ortofoton. Resultatet produceras av flertalet tester på varierande konstruktioner och färger på tak. Validering av testresultaten sker helt visuellt, efter utritning i karta. I de flesta testfallen har algoritmen på ett korrekt sätt lyckats identifiera och segmentera delar av taket, men inte i något fall ansetts ha lyckats segmentera ett helt tak på ett korrekt vis. Detta berodde till stor del på att inte fler typer av data än ortofoton var tillgängliga, samt störningar i de bilder som användes i form av skuggning. Resultatet visar att metoden kan fungera på ett bättre sätt, med tillgång till mer data och vidare utveckling av bildbehandlingen. Samt visar hur denna typ av operation enkelt kan integreras i en webbkarta.

Text in English with abstracts in English, Tsonga and Sepedi and keywords in English / This study was carried out to investigate the performance and quality of Cucumis metuliferus E. Mey. Ex Naudin (African horned cucumber) under protected and open environment with the aim of comparing yield and quality for the purpose of commercialisation of the crop. Therefore, the overall objective was to determine a suitable growing environment for C. metuliferus between greenhouse, shade net and open field, so that a comparative yield and quality analysis could be done for the purpose of commercialisation of the crop. Cucumis metuliferus seeds are difficult to germinate under the normal suitable environmental conditions in which most farmers operate. Germination was evaluated with respect to growth medium, scarification and seed certification. These factors ultimately control yield and fruit quality. The main aim of the study was to investigate the effect or impact of seed certification, growth medium (sand and vermiculite, peat TS1 and seedling mix) and scarification on germination success of C. metuliferus seeds. The seeds were classified under four different categories viz. treated certified, non-treated certified, treated uncertified, and non-treated uncertified. Of the 540 certified and uncertified seeds sown in the three-growth media, 80% germinated, significantly more that those that failed. The treatment combination of treated certified seeds (TC) and peat demonstrated high germination success rate of 93.6%, followed by the treatment combination of treated certified seeds (TC) and sand+ vermiculite with germination success rate of 91.3%. The treatment combination of uncertified untreated (UTU) seeds and potting mix illustrated low germination success rate at 37.2%. In general, the study results revealed that certified seeds scarified with warm water combined had a higher germination rate that unscarified seeds, irrespective of the growth media. Since the seedling root-ball integrity is essential for transplant survival, this study suggests peat and certified seeds as the best combination for propagation and good quality plants. Water scarcity, population growth and climate change are the major factors affecting agricultural productivity in the 20th century. Cucumis metuliferus grows naturally in the wild; however, its yield response to water stress, different cultivation environment and soil types, has not been assessed. A study was carried out to determine water use efficiency of the C. metuliferus grown the greenhouse, shade net and open field under varying soil types and irrigation water levels, so that a comparative analysis could be done on productivity levels. The research was conducted at the University of South Africa (Unisa) Science Campus, in Florida, Gauteng (-26.157831 S, 27.903364 E) during the 2017/2018 and 2018/2019 growing seasons. A factorial experiment with two factors – soil (loamy soil and sandy loam soil) and water stress levels (no water stress, moderate water stress and severe water stress). The pot experiments were a completely randomised design with nine (9) replicates per treatment. Data collected included total biomass, aboveground biomass, harvest index and water use efficiency. Results illustrated that treatment of moderate water stress combined with loamy soil and shade net decreased WUE from 6.2 to 1.4 kg m-3, whereas treatment combination of no water stress combined with sandy loam and open field environment demonstrated increase in WUE from 1.4 to 6.2 kg m-3. Nutritional concentration of most crops depends on factors such as amount of water, growing environment, light intensity and soil types. However, factors influencing nutritional concentration of C. metuliferus fruits is not yet known. Another objective of the study was to determine the effect of different water stress levels, soil types and growing environment (greenhouse, shade net and open field) on the concentration of nutrients in C. metuliferus fruit. Freeze-dried fruit samples were used in the quantification of ꞵ-carotene, vitamin C, vitamin E, total soluble sugars, crude proteins, total flavonoids, total phenols, macro-nutrients (Ca, Mg, P, K, Na and S), and micro-nutrients (Cu, Fe, Mn and Zn). Results demonstrated that plants grown under shade net, combined with severe water stress level and loamy soil, had increased total soluble sugars (15.8 ˚Brix) compared to other treatments. Plants under shade net environment, combined with moderate water level and loamy soil, resulted in increased crude protein content (6.31 ˚Brix). The severe water stress treatment combined with loamy soil under greenhouse conditions resulted in increased ꞵ-carotene content (1.65 mg 100 g-1 DW) when compared to other treatments. Regarding vitamin C, the treatment of no water stress combined with loamy soil under shade net environment showed higher content of (33.1 mg 100 g-1 DW). The severe water stress treatment combined with sandy loam soil under greenhouse environment, increased vitamin E content (35.1 mg 100 g-1 DW) when compared to other treatments. The treatment of open field under severe water stress level and loamy soil increased total flavonoids content (0.85 mg CE/g-1 DW) in the fruit when compared to other treatments. The results thus imply that this plant bears better-quality fruit in terms of concentration of nutrients and biochemical constituents when grown under no to moderate water stress treatment on the loamy or sandy loam substrate in the shade net and open field environment. Primary metabolites are biological compounds that are essential to the growth and development of a plant during its life cycle. They have a direct impact on the yield and biochemical constituents in plants. Quantities of the primary metabolites were determined using the LC-MS-8040 triple quadrupole mass spectrometer (Shimadzu) from fruits harvested from treatments mentioned above. The results showed that the no water stress treatment combined with sandy loam under shade net environment significantly (P≤0.05) increased asparagine content from 10×106 to 80x106 peak intensity when compared to other treatments. The severe water stress treatment combined with sandy loam soil under open field environment during the 2017/2018 season, significantly increased dopa content from 12,030 to 324,240 peak intensity, while during the 2018/2019 season, 4-hydroxyproline from 10×106 to 90x106 peak intensity the was significantly increased. The study suggests that the treatment combination of water stress levels (no water stress and severe water stress) and soil substrates (loamy soil and sandy loam) under greenhouse and shade net significantly affected the shift of primary metabolites profile of C. metuliferus fruit as opposed to individual factors, respectively. There is therefore great potential to commercialise this crop; however, there is still a great deal that is not well understood of its growth habits and biological/biochemical constituents as a future alternative crop. / Ndzavisiso lowu wu endliwe ku lavisisa hi matirhelo na khwaliti ya Cucumis metuliferus E. Mey. Ex Naudin (African horned cucumber) eka mimbangu na mavala lama sirheleriweke na hi xikongomelo xa ku kotlanisa ntshovelo na vuxopaxopi bya khwaliti hi xikongomelo xa ku endla minxaviso ya ximila. Xikongomelonkulu xa ku vona ku faneleka ku kula ka C. metuliferus exikarhi ka ti-greenhouse, nete ya ndzhuti na mimbangu ya le rivaleni ku endlela ku pfuneta nxopaxopo. Timbewu ta C. metuliferus ta nonon'hwa ku tihlukisa ehansi ka swiyimo swa mbangu leswi faneleke laha varimi va tirhaku eka tona. Ku hlukisa swi kamberiwe hi ku langutana na midiyamu ya ku kula, skarifikhexini na switifiketi swa timbewu. Swilo leswi swi lawula ntshovelo na khwaliti ya muhandzu. Xikongomelonkulu xa ndzavisiso lowu a ku ri ku lavisa hi vuyelo bya ku nyikiwa ka switifiketi, midiyamu ya ku kula (sand + vermiculite, peat TS1 and seedling mix) na skarifikhexini eka ku humelela ku hlukisa timbewu ta C. metuliferus E. Mey. ex naudin. Timbewu ti klasifayiwile ehansi ka tikhathegori ta mune to hambana, ku nga, treated certified, non-treated certified, treated uncertified, na non-treated uncertified.Hi vunharhu ka timediya leti ti ve na nhlukiso wa xiyenge hi 80%. Vuyelo byi kombise leswo treated certified na non-treated certified ti ve na ku humelela ka le henhla ka nhlukiso hi 93.6% na 91.3% hi ku landzelelana. Vuhumeleri bya nhlukiso wa le hansi ku ve timbewu ta treated uncertified hi vuyelo bya 37%. Vulehi bya 12 cm byi voniwe eka certified seedlings tanihi bya le henhla swinene. Swimilani swa unscarified na swa uncertified swi ve na timbewu ta le hansi, ta vulehi bya 3.44 cm eka vhiki ra vumune. Hikokwalaho, seed certification swi ve na vuyelo ngopfu ku tlula scarification hi majini ya le henhla swinene. Ku khomaniseka ka ximila eka bolo ya misava i swa nkoka eka ku pona no ya emahlweni ka ximila loko xi transplantiwa, kasi ndzavisiso lowu wu tlakusa leswo ku va na peat na timbewu leti nga na switifiketi tanihi ndlela yo antswa swinene ya ku kurisa swimila na ku va na swimila swa khwaliti. Ku pfumaleka ka mati, nkulo wa swilo hinkwaswo na ku cinca ka tlayimete i swa nkoka leswi khumbaka ku tirheka ka vurimi eka malembexidzana ya 20. Cucumis metuliferus yi kula hi ntumbuluko enhoveni; kambe ntshovelo wa yona wu angula eka ku kala ka mati, tindhawu to hambana ta ku rimiwa na mixaka ya misava, a swi si kamberiwa. Ku endliwe ndzavisiso ku vona ku faneleka ka mafambiselo ya ku kurisa ximila eka greenhouse, nete ya ndzhuti eka swiyimo swa mavala lama pfulekeke, leswo nxopaxopo wu ta kotlanisiwa eka tilevhele ta vuyelo bya ntshovelo loku nga endliwaka. Ndzavisiso wu endliwe eka greenhouse, nete ya ndzhuti na swiyimo swa mavala lama pfulekeke eKhempasi ya Sayense eUniversity of South Africa (Unisa) eFlorida, eGauteng (26.157831 S, 27.903364 E) hi nkarhi wa 2017/2018 na 2018/2019 hi tisizini ta ku byala. Ekspirimente leyi nga na swilo swimbirhi – ku nga misava ya loamy na misava ya misava ya sava ya loam) na levhele ya ncheleto wa mati (laha ku nga ri ku na mati kahle, laha ku nga na matinyana na laha ku kalaka mati). Xipirimente xa le mapotweni xi endliwe hi ndlela yo ka yi nga kunguhatiwangi hi ku tirhisa ku phindaphinda ka nkaye (9), na dizayini ya kona leyi nga kombisiwa laha henhla. Tipharamita ta ku pimiwa ti katsa chlorophyll content, stomatal conductance na xiyenge xa ntshovelo, xo fana na ku tirhisa mati, vuheleri bya biomass, biomass ehenhla ka bayomasi ya misava, indeksi ya ntshovelo, vulehi bya muhandzu, nhlayo ya mihandzu, na ku tirhisiwa ka mati hi ndlela yo hlayisa. Vuyelo byi kombise leswo tirhelo ra mavala lama pfulekeke swi pfanganisiwa na ndhawu yo kala mati na misava ya sava ya loam, swi ngetela nhlayo ya mihandzu. Ku tirhiwa ka swiyimo swa mavala lama nga pfuleka, swi hlanganisiwa na ndhawu yo kalanyana mati na misava ya sava ya loam, swi kombise ku tirhisiwa kahle ka mati ka le henhla hi (6. 2 kg m-3) loko swi kotlanisiwa na ku tirhiwa ku n'wana. I swa nkoka ku lemuka leswaku a ku va ngi na ku hambana ku kulu exikarhi ka misava ya sava ya loam na misava ya loam eka ntirhiso wa mati lowu ku nga water use efficiency (WUE). Kambe, misava ya sava ya loam yi kombise xiyenge xa le henhla xa WUE loko swi kotlangisiwa na misava ya loam. Hikokwalaho ku nga fikeleriwa eka mhaka ya leswo ku pfanganisa ku tirhana na mavala yo pfuleka, tilevhele ta ncheleto wa mati (kahle na le xikarhi) na misava ya sava ya loam swa bumabumeriwa eka varimi leswo ku ta fikelekeleriwa xiyenge xa le henhla xa WUE na ku humelela ka ntshovelo wa C. metuliferus. Ku hlengeletana ka tinutriyente eka ndhawu yin'we (nutritional concentration) ka swimila swi titshege hi swilo swo fana na leswi kumekaka eka mati, mbangu wa ku kula, masana ya dyambu na mixaka ya misava. Kambe, swilo swo fana na ku hlengeletana ka tinutriyente ta mihandu ya C. metuliferus a swi si tiveka. Xikongomelo xa ndzhavisiso a ku ri ku vona vuyelo bya tilevhele to hambana ta ku kala ka mati (ku pfumaleka ka mati, ku pfumalekanyana, na ku pfumaleka swinene ka mati), mixaka ya misava (misava ya loam na misava ya sava) mbangu wa ku kula (greenhouse, nete ya ndzhuti na mavala yo pfuleka) hi ku pfangana na tinutriyente eka mihandzu ya C. metuliferus E. Mey. ex naudin. Tisampuli ta mihandzu leyi nga omisiwa yi friziwa ti tirhisiwe eka ku endla vunyingi bya ꞵ-carotene, Vhitamini C, Vhitamini E, na total soluble sugars, ti-crude protein na ti-total flavonoids, total phenols, na micro-nutrients (Cu, Fe, Mn na Zn). Vuyelo bya ndzavisiso byi kombise leswo swimila leswi nga kurisiwa eka nete ya ndzhuti, swi pfanganisiwa na levhele ya nkalo wa mati swinene na misava ya loam, swi ngetele ti-soluble sugars hi (15.8 ˚Brix) loko ku kotlanisiwa na ku tirhiwa kun'wana. Swimila leswi nga hansi ka mbangu wa nete ya ndzhuti, swi pfanganisiwa na nkayivelonyana wa mati hi vuxikarhi na misava ya loam, swi ve na vuyelo bya ku ngetela crude protein content hi (6.31˚Brix). Ku tirhiwa ka nkayivelo wa mati swinene swi pfanganisiwa na misava ya loam ehansi ka swiyimo swa greenhouse swi ngetelele ꞵ-carotene content (1.65 mg/100 g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Ku tirhiwa ka ku kayivela ka mati swi pfanganisiwa na misava ya loam ehansi ka mbangu wa nete ya ndzhuti swi kombise ku ngeteleleka ka vhitamini C hi (33.1 mg 100 g-1 DW). Ku tirhiwa ka nkayivelo wa mati swinene swi pfanganisiwa na misava ya loam ehansi ka swiyimo swa mbangu wa greenhouse swi ngetelele vhitamin E hi (35.1 mg 100 g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Ku tirhiwa ka mavala lama nga rivaleni eha CE g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Ku tirhana na nkayivela mati ka levhela ya le xikarhi na misava ya sava ya loam ehansi ka mbangu wa nete ya ndzhuti swi kombise ku ngeteleleka ka Zn content (12.7 μg g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Vuyelo byi kombisa leswaku ximila lexi xi na mihandzu ya khwaliti yo antswa hi ku landza ku hlengeletana ka tinutriyeente na tikhonstituwenti ta bayokhemikali, loko xi kurisiwa ehansi na ku ka ku nga ri na nkayivela mati kumbe ku kayivelanyana ka mati, hi ku tirhisa misava ya loam kumbe misava ya sava eka nete ya ndzhuti na le ka mavala ya le rivaleni.Ti-primary betabolites ti tlhela titiviwa tanihi biological compounds leti ti faneleke eka ku kula na ku hluvuka ka ximila hi nkarhi wa vutomi bya xona. Ti na vuyelo byo kongoma eka ntshovelo na tikhonsticuwenti ta bayokhemikala eka swimila. Vunyingi bya primary metabolites swi vekiwe hi ku tirhisa LC-MS-8040 triple quadrupole mass spectrometer (Shimadzu) eka mihandzu leyi nga ntshovelo wa ku tirhiwa kun'wana loku ku nga vuriwa laha henhla. Vuyelo byi kombe leswo ku tirhana na nkala nkayivelo wa mati, swi pfanganisiwa na misava ya loam ehansi ka mbangu wa nete ya ndzhuti, swi ngetelele swinene asparagine content from 10×106 to 80x106 nsi ka nkayivelo swinene wa mati na misava ya loam, swi ngetelele ti-total mz loko swi kotlangisiwa na ku tirhiwa kun'wana. Ku tirhana na nkayivelo wa mati swinene, swi pfanganisiwa na misava ya sava ya loam ehansi ka mbangu wa mavala lama pfulekeke hi nkarhi wa sizini ya 2017/2018, swi ngetelele swinene dopa content ku suka eka 12,030 to 324,240 peak intensity, kasi hi nkarhi wa sizini ya 2018/2019 season, 4-hydroxyproline ku 10×106 to 90x106 peak intensity swi ngeteleleke swinene. Ku tirhana ko fanana ehansi ka mbangu wa greenhouse, swi ngetelele swinene acetylcarnitine content ku suka eka 3,761 to 82,841 area under the curve hi nkarhi wa sizini ya 2018/2019. Ku tirhiwa ka ku nga ri na ku kayivela ka mati ka le xikarhi swi pfanganisiwa na misava ya loam ehansi ka mbangu wa mavala lama nga rivaleni swi ngetelele swinene norepinephrine content from 71,577 to 256,1045 peak intensity. Ndzavisiso wu pimanyete leswo mpfanganyiso wa ku tirhana na tilevhele ta ncheleteo wa mati (laha ku nga ri ku na ku kayivela ka mati na le ku nga na nkayivelo wa mati) na misava ya loam na misava ya sava ya loam) ehansi ka greenhouse na nete ya ndzhuti swi khumbe swinene ku xifta ka mihandzu ya primary metabolites profile of C. metuliferus E. Mey. ex naudin loko ku langutaniwa na tifekthara ha yin'we yin'we hi ku landzelelana.flavonoids content (0.85 mg CE g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Ku tirhana na nkayivela mati ka levhela ya le xikarhi na misava ya sava ya loam ehansi ka mbangu wa nete ya ndzhuti swi kombise ku ngeteleleka ka Zn content (12.7 μg g-1 DW) loko swi kotlanisiwa na ku tirhiwa kun'wana. Vuyelo byi kombisa leswaku ximila lexi xi na mihandzu ya khwaliti yo antswa hi ku landza ku hlengeletana ka tinutriyeente na tikhonstituwenti ta bayokhemikali, loko xi kurisiwa ehansi na ku ka ku nga ri na nkayivela mati kumbe ku kayivelanyana ka mati, hi ku tirhisa misava ya loam kumbe misava ya sava eka nete ya ndzhuti na le ka mavala ya le rivaleni.Ti-primary betabolites ti tlhela titiviwa tanihi biological compounds leti ti faneleke eka ku kula na ku hluvuka ka ximila hi nkarhi wa vutomi bya xona. Ti na vuyelo byo kongoma eka ntshovelo na tikhonsticuwenti ta bayokhemikala eka swimila. Vunyingi bya primary metabolites swi vekiwe hi ku tirhisa LC-MS-8040 triple quadrupole mass spectrometer (Shimadzu) eka mihandzu leyi nga ntshovelo wa ku tirhiwa kun'wana loku ku nga vuriwa laha henhla. Vuyelo byi kombe leswo ku tirhana na nkala nkayivelo wa mati, swi pfanganisiwa na misava ya loam ehansi ka mbangu wa nete ya ndzhuti, swi ngetelele swinene asparagine content from 10×106 to 80x106 mz loko swi kotlangisiwa na ku tirhiwa kun'wana. Ku tirhana na nkayivelo wa mati swinene, swi pfanganisiwa na misava ya sava ya loam ehansi ka mbangu wa mavala lama pfulekeke hi nkarhi wa sizini ya 2017/2018, swi ngetelele swinene dopa content ku suka eka 12,030 to 324,240 peak intensity, kasi hi nkarhi wa sizini ya 2018/2019 season, 4-hydroxyproline ku 10×106 to 90x106 peak intensity swi ngeteleleke swinene. Ku tirhana ko fanana ehansi ka mbangu wa greenhouse, swi ngetelele swinene acetylcarnitine content ku suka eka 3,761 to 82,841 area under the curve hi nkarhi wa sizini ya 2018/2019. Ku tirhiwa ka ku nga ri na ku kayivela ka mati ka le xikarhi swi pfanganisiwa na misava ya loam ehansi ka mbangu wa mavala lama nga rivaleni swi ngetelele swinene norepinephrine content from 71,577 to 256,1045 peak intensity. Ndzavisiso wu pimanyete leswo mpfanganyiso wa ku tirhana na tilevhele ta ncheleteo wa mati (laha ku nga ri ku na ku kayivela ka mati na le ku nga na nkayivelo wa mati) na misava ya loam na misava ya sava ya loam) ehansi ka greenhouse na nete ya ndzhuti swi khumbe swinene ku xifta ka mihandzu ya primary metabolites profile of C. metuliferus E. Mey. ex naudin loko ku langutaniwa na tifekthara ha yin'we yin'we hi ku landzelelana. / Thuto ye e dirilwe ka maikemišetšo a go nyakišiša tiragatšo le boleng bja Cucumis metuliferus E. Mey. Ex Naudin (phara ya seAfrika) mo tikologong yeo e šireleditšwego le ya mo lebaleng e le nepo ya go bapetša tshekatsheko ya kotollu le boleng go hola thekišo ya mabele. Maikemišetšo kakaretšo e le go humana tsela ya maleba ya go mediša C. Metuliferus dipakeng tša mokhukhutšhireletšo, nnete ya moriti le mo ditikologong tša mabala ao a bulegilego gore go nolofatšwe tshekatsheko. Go boima go mediša dipeu tša C. Metuliferus ka tlase ga maemo a tikologo ya maleba ya go tlwaelega yeo e šomišwago ke bontši bja balemi. Medišo ya dipeu e lekanyeditšwe go ya le ka sedirišwa sa go mediša dimela, go fala dipeu le go hlahlobo ya boleng bja dipeu. Dikokwana tše ke tšona di laolago kotollu le boleng bja dienywa. Nepokgolo ya thuto ye e be e le go nyakišiša khuetšo ya tlhahlobo ya polokego ya dipeu tše, sedirišwa sa go mediša dimela (mohlaba+vermiculite, peat TS1 le motswako wa dipeu) le phalo ya dipeu go kgonthišiša katlego ya go mela ga dipeu tša C. Metuliferus. Dipeu di ile tša arolwa go ya le ka magoro a mane, bjalo ka peu ya go okobatšwa ka dikhemikhale yeo e hlahlobilwego, peu yeo e sa okobatšwago gomme e hlahlobilwe, peu ya go okobatšwa e sa hlahlobjwago le peu yeo e sa okobatšwago gomme e se ya hlahlobjwa. Boraro bja didirišwa tše di laeditše katlego ya go mediša yeo e ka balelwago go 80%. Dipoelo di šupa gore dipeu tšeo di okobaditšwego di se a hlahlobjwa le tšeo di sa okobatšwago di hlahlobilwe di bile le katlego ya tlhogo yeo e ka balelwago go 93.6% le 91.3%. Tlhogo ya fase e bile go dipeu tšeo di okobaditšwego di sa hlahlobjwago ka poelo ya 37%. Dipeu tše di hlahlobilwego di laeditše botelele bja 12cm gomme e le bjona bja go di feta ka moka. Dipeu tšeo di sa falwago le go hlahlobjwa di bile le botelele bja fase bja go balelwa go 3.44 cm ka dibeke tše nne. Bjalo, tlhahlobo ya dipeu e tlišitše katlego go fetiša phalo. Ka ge mudu wa dipeu o le bohlokwa go tšhutišetšo ya maphelo a dimela, thuto ye e thekga mmutedi le tlhahlobo ya dipeu bjalo ka tlhakanyo ya go mediša dimela tša boleng bja maleba. Tlhokego ya meetse, go oketšega ga baagi, le diphetogo tša klaemete ke tšona dikokwana tše di amago tšwelelo go tša temo nakong ya bjale. C. Metuliferus E. Mey. ex naudin e mela ka lešokeng tlhagong ya yona; efela, kotullo ya yona go tlhokego ya meetse, go mehuta ya mašemo le mehuta ya mabu ga se e ahlaahlwe. Thuto e ile ya dirwa go humana mokgwa wa go bjala/mediša dimela dipakeng tša mokhukhutšhireletšo, nnete ya moriti le boemo bja lebala le le bulegilego, gore go tle go tšweletšwe tshekatsheko yeo e laetšago diphapano tša mabato a puno. Nyakišišo ye e diritšwe ka fase ga maemo a mokhukhutšhireletšo, nnete ya moriti le lebaleng le le bulegilego Yunibesithing ya Afrika Borwa (UNISA) Khamphasing ya tša Saense, go la Florida, Gauteng (-26.157831 S, 27.903364 E) ka nako ya sehla sa 2017/2018 le 2018/2019 ka dinako tša go mela. Teko ye e ithekgile godimo ga dikokwana tše pedi – mabu (monola le mohlaba) le mabato a taolo ya go nošetša (tlhokego ya meetse ya lebato la fase, tlhokego ya meetse ye e lekanetšego le tlhokego ya meetse ya lebato la godimo). Diteko di be di beilwe ka mokgwa wo o sa rulaganywago gomme teko ye nngwe le ye nngwe e boeleditšwe ga senyane (9) bjalo ka ge e laeditšwe godimo. Dipharametha tšeo di lekantšwego di akaretša dikagare tša chlorophyll, stomatal conductance le bjalo ka tšhomišo ya meetse, palomoka ya dimela, dimela tše di bonagalago ka godimo, lenaneo la puno, botelele bja enywa, palo ya enywa le tšhomišo ya meetse ke dimela. Dipoelo di tšweletša gore teko ya mo lebaleng le le bulegilego le meetse a a lekanetšego gammogo le monola di oketša palo ya dienywa. Teko ya mo lebaleng le le bulegilego go kopantšhwa le meetse ao a lekanetšego le monola, di laeditše tšhomišo ya meetse yeo e balelwago go (6.2 kg m-3) ge go bapetšwa le diteko tše di ngwe. Go bohlokwa go lemoga gore ga ga go na diphapano magareng ga mohlaba le monola tšhomišong ya meetse (WUE). Efela, mohlaba o laeditše (WUE) ya godimo ge go bapetšwa le monola. Se se bolela gore, go ka tšewa sephetho sa gore teko ya dipeu lebaleng le le bulegilego, taolo ya go nošetša dimela (ye gabotse le ye e lekanetšego) le mohlaba ke didirišwa tšeo go eletšwago balemi gore ba di šomiše go humana (WUE) ya godimo le tšweletšo ye e atlegilego ya C. metuliferus. Bontši bja phepo mo mabeleng bo hlohleletšwa ke dikokwana tša go swana le meetse, tikologo ya mo a melago gona, dihlase tša letšatši le mehuta ya mabu. Efela, dikokwana tše di huetšago bontši bja diphepo go dienywa tša C. metuliferus ga dišo di tsebjwa. Nepo ya thuto ye e be e le go nyakolla khuetšo yeo dikokwana tše di latelago; di nago le yona go bontši bja diphepo go enywa ya C. Metuliferus: mabato a meetse (tlhokego ya meetse ya lebato la fase, tlhokego ya meetse ye e lekanetšego le tlhokego ya godimo ya meetse), mehuta ya mabu (monola le mohlaba) le tikologo ya go mediša (mokhukhutšhireletšo, nnete ya moriti le lebala le le bulegilego). Diteko tša enywa yeo e omišitšwego ka setšidifatšing e ile ya šomišwa go tšweletša boleng bja ꞵ-carotene, vitamin C, vitamin E, total soluble sugars, crude proteins, total flavonoids, total phenols, le micro-nutrients (Cu, Fe, Mn le Zn). Dipoelo di šupa gore dimela tše di godišitšwego ka fase ga nnete ya moriti, go akaretša le tlhokego ya meetse ya godimo le monola di nyološitše diswikiri tše di humanegago mo dimeleng (15.8 ˚Brix) ge go bapetšwa le diteko tše dingwe. Dimela tikologong ya nnete ya moriti go akaretša le tlhokego ya meetse ye e lekanetšego le monola di ile tša nyološa phroteine (6.31 ˚Brix). Teko go tlhokego ya meetse ya godimo go akaretša le monola ka tlase ga boemo bja mokhukhutšhireletšo go nyološitše diteng tša ꞵ-carotene (1.65 mg 100 g-1 DW) ge e bapetšwa le diteko tše dingwe. Teko go tlhokego ya meetse go akaretša monola ka fase ga nnete ya moriti go nyološitše Vitamin C (33.1 mg100 g-1 DW). Teko go hlokego ya meetse ya godimo go akaretša mohlaba tikologong ya mokhukhutšhireletši go nyološitše diteng tša vitamin E (35.1 mg/100 g-1 DW) ge e bapetšwa le diteko tše dingwe. Teko ya go se hlokege ga meetse, go akaretša le monola tikologong ya lebala le le bulegilego e nyološitše palomoka ya diteng tša phenolic (6.4 mg GAE/g-1 DW) ge e bapetšwa le diteko tše dingwe. Teko lebala le le bulegilego ka fase ga hlokego ya meetse ye godimo go akaretša monola go okeditše diteng tša flavonoids (0.85 mg CE g-1 DW) mo dienyweng tša gona ge e bapetšwa le diteko tše dingwe. Teko go hlokego ya meetse ye e lekanetšego le mohlaba ka fase ga nnete ya moriti di laeditše go oketšega ga diteng tša Zn (12.7 μg g-1 DW) ge e bapetšwa le diteko tše dingwe. Dipoelo di laetša gore semela se se thunya boleng bjo bo kgodišago bja dienywa ge go lebeletšwe bontši bja diphepo le dikokwana tša dikhemikhale ge di medišwa mo go sa hlokegago meetse go yela go mo go hlokegago meetse ka go lekanela, go šomišitšwe monola goba mohlaba mo nneteng ya moriti le mo lebaleng le le bulegilego. Dimetabolite tša motheo di tsebjwa bjalo ka motswako wa tlhago wo o lego bohlokwa go kgolo le tlhabollo ya dimela maphelong a tšona. Di na le khuetšothwii go dikokwana tša puno le khemikhale ya hlago ya dimela. Bontši bja dimetabolites tša motheo di humanwe ka go šomiša LC-MS-8040 triple quadrupole mass spectrometer (Shimadzu) ya go tšwa dienyweng tšeo di bunnwego ditekong tše di šetšego di boletšwe. Dipoelo di laeditše gore teko ya hlokego ya meetse ya lebato la fase go akaretša le mohlaba tikologong ya nnete ya moriti; e nyološitše asparagine content go tloga go 10×106 go ya go 80x106 peak intensity ge e bapetšwa le diteko tše dingwe. Tlhokego ya meetse ya lebato la fase e akaretša le monola tikologong ya lebala le le bulegilego ka nako ya sehla sa 2017/2018, 4-hydroxyproline go tšwa go 10×106 go ya go 90x106 area under curve e ile ya nyušwa. Teko ya go swana le ye tikologong ya mokhukhutšhireletšo e ile ya oketša dikagare tša acetylcarnitine go tšwa go 3,761 go ya go 82, 841 peak intensity ka nako ya sehla sa 2018/2019. Teko go tlhokego ya meetse ye e lekanetšego go akaretšwa le monola tikologong ya lebala le le bulegilego e nyološitše dikagare tša norepinephrine go tloga go 71,577 go ya go 256,1045 peak intensity. Diteko di šupa gore ge go kopantšwe taolo ya mabato a go nušetša (tlhokego ya meetse ya lebato la fase le tlhokego ya meetse ya lebato la godimo) le (monola le mohlaba) ka fase ga boemo bja mokhukhutšhireletšo le nnete ya moriti go ile gwa ama katološo ya dimetabolites tša motheo tša enywa ya C. metuliferus ge di bapetšwa le kokwana ye nngwe le nngwe. / College of Agriculture and Environmental Sciences / Ph. D. (Agriculture)

O presente estudo analisou os efeitos da fratura de côndilo unilateral, no período de crescimento. Para tanto, foram utilizados 50 ratos jovens, linhagem Wistar, com peso até 100g. Sob anestesia geral foi realizada no grupo experimental fratura do processo condilar no lado direito com desvio e no grupo controle-operado, foi feito apenas acesso cirúrgico ao côndilo. O sacrifício dos animais foi feito aos três meses de idade. A mandíbula foi desarticulada sendo obtidas as incidências radiográficas axial do crânio seco e lateral das hemi-mandíbulas. Foram feitas mensurações cefalométricas por meio de um sistema de computador. Foram aplicados os testes estatísticos “t" de Student entre os grupos e teste “t" de Student para dados pareados entre os lados, dentro de cada grupo.Houve diferença significante entre os grupos para o lado direito no comprimento das porções anterior (p=0,001) e posterior (0,017) da maxila e altura do ramo mandibular (p=0,001). Houve diferença significante entre os lados para o comprimento da mandíbula (p<0,001) e altura do ramo mandibular (p<0,001), nos grupos experimental e controle-operado. Houve diferença significante para a altura do corpo mandibular (p=0.001) e para o comprimento das porções anterior (p=0,002) e posterior (p=0,001) da maxila apenas no grupo experimental. Os resultados obtidos permitiram concluir que uma fratura de côndilo mandibular experimental durante o período de crescimento em ratos levou a uma assimetria da mandíbula na altura do corpo mandibular, com conseqüências também para a maxila. / The present study analyzed the effects of the condyle fracture were analyzed in the growing period in this study. Fifty young Wistar rats weighting 100g were used. Under general anestesia fracture of the condilar process on the right side with deviation was performed in the experimental group, while only the made surgical access was performed in the sham-operated group. The animals were sacrifized with three months of age. The mandible was disarticulated, and radiographic projections axial of dried skull and lateral of the hemimandible were obtained. Cephalometric mensurations through a computer system were made. Statistical tests "t" of Student between the groups and paired test "t" of Student among the sides, inside of each group were applied. There was a significant different among the groups to the right side in the length of the anterior portion (p=0,001) and posterior (0,017) of the maxilla and height of the mandibular ramus (p=0,001). There was significant difference among the sides for the length of the mandible (p <0,001) and height of the mandibular ramus (p<0,001), in the height of the body mandibular (p=0.001) and for the length of the anterior portions (p=0,002) and posterior (p=0,001) of the maxilla just in the experimental group. The obtained results allowed to conclude that a experimental fracture of mandibular condyle during the growing period in rats induced an asymmetry of the mandible in the height of the mandibular body, with also consequences to the maxilla.

O uso de imagens provenientes de sensores remotos, tal como sistemas acoplados em aviões e satélites, é cada vez mais frequente, uma vez que permite o monitoramento continuo e periódico ao longo do tempo por meio de diversas observações de uma mesma região, por vezes ampla ou de difícil acesso. Essa ferramenta tem se mostrado importante e significativa em aplicações como o mapeamento de solo e fronteiras; acompanhamento de áreas de desmatamento, queimadas e de produção agrícola. Para gerar resultados interpretáveis ao usuário final, essas imagens devem ser processadas. Atualmente, o método de classificação por máxima verossimilhança é o mais empregado para classificação de imagens multiespectrais de sensores remotos, entretanto, por se tratar de uma técnica supervisionada, seus resultados dependem extensivamente da qualidade do conjunto de treinamento, utilizado para definir os parâmetros do método. A seleção de um bom conjunto de treinamento é um processo custoso e inviabiliza a automação da classificação para diversas imagens. O método de classificação por máxima verossimilhança é também paramétrico e portanto exitem algumas suposições quanto a distribuição dos dados que devem ser atendidas, caso contrário a aplicação do método pode gerar resultados ruins. Tendo em vista essas desvantagens do método da máxima verossimilhança, este trabalho propõe um novo método para a classificação de imagens multiespectrais provenientes de sensores remotos de forma que o procedimento seja autônomo, veloz e preciso, minimizando dessa forma os possíveis erros humanos inseridos em etapas intermediárias do processo, tal como a definição de conjuntos de treinamento. O método aqui proposto pertence ao conjunto das redes neurais artificiais (RNAs) e é denominado growing neural gas (GNG). Este método baseia-se no aprendizado não supervisionado de padrões \"naturais\" dentro de um conjunto de dados por meio da criação e adaptação de uma rede mínima de neurônios. Os resultados gerados a partir da classificação pela RNA foram comparados com os métodos mais utilizados na literatura atual, sendo eles o método da máxima verossimilhança e o método k-means. A partir da biblioteca espectral ASTER, mantida e criada parcialmente pela NASA, foram realizadas várias repetições do experimento, que consiste em classificar os dados de acordo com as diferentes classes existentes, e para cada uma destas repetições calculou-se uma medida de acurácia, denominada índice kappa, além do tempo de execução de cada método, de forma que suas médias foram comparadas via intervalo de confiança gerados por bootstrap não paramétrico. Também investigou-se como a análise de componentes principais (ACP), técnica utilizada para reduzir a dimensão dos dados e consequentemente o custo computacional, pode influenciar no desempenho dos métodos, tanto em sua qualidade de classificação quanto em relação ao tempo de execução. Os resultados mostram que o método proposto é superior nos dois aspectos estudados, acurácia e tempo de execução, para a maioria dos fatores aplicados. Mostra-se ainda um exemplo de aplicação prática em que uma imagem multiespectral de satélite não satisfaz as pré-suposições estabelecidas para o uso do método da máxima verossimilhança e verifica-se a diferença entre os métodos com relação a qualidade final da imagem classificada. / The use of images from remote sensors, such as coupled systems in airplanes and satellites, are increasingly being used because they allow continuous and periodic surveillance over time through several observations of some particular area, sometimes large or difficult to access. This sort of image has shown an important and meaningful participation in applications such as soil and borders mapping; surveillance of deforestation, forest fires and agricultural production areas. To generate interpretable results to the end user, these images must be processed. Currently, the maximum likelihood classification method is the most used for multispectral image classification of remote sensing, however, because it is a supervised technique, the results depend extensively on the quality of the training set, used to define the parameters of the method. Selecting a good training set is a costly process and prevents the automation of classification for different images. The maximum likelihood classification method is also parametric, and therefore, some assumptions about the distribution of the data must be met, otherwise the application of the method can generate bad results. In view of these disadvantages of the maximum likelihood method, this dissertation proposes a new, autonomous, fast and accurate method for multispectral remote sensing imagery classification thereby minimizing the possible human errors inserted at intermediate stages of the process, such as the definition of training sets. The method proposed here belongs to the set of artificial neural networks (ANN) and is called growing neural gas (GNG). This method is based on unsupervised learning of \"natural\" patterns in a dataset through the creation and adaptation of a minimum network of neurons. The results generated from the classification by ANN were compared with the most commonly used methods in the literature: the maximum likelihood method and the k-means method. From the spectral library Aster, maintained and made in part by NASA, several replications of the experiment were made, which is to classify the data according to different preestablished classes, and a measure of accuracy called kappa index was calculated for each of the replicates, in addition to the execution time of each method, so that their means were compared via confidence interval generated by nonparametric bootstrap. It was additionally investigated how principal component analysis (PCA), technique which reduces dimension of data and consequently the computational cost, can influence the performance of methods, both in its quality rating and runtime. The results show that the proposed method is superior in both aspects studied, accuracy and runtime, for the majority of applied factors. Furthermore, it is shown an example of a practical application in which a multispectral satellite image does not necessarily meet the established assumptions for using the maximum likelihood method, and there is a difference between the methods, regarding to its final classified image quality.

Made available in DSpace on 2015-03-03T15:07:33Z (GMT). No. of bitstreams: 1 AlexandreGL_DISSERT.pdf: 5013567 bytes, checksum: e16408257f23b984754d0a91e2a173b4 (MD5) Previous issue date: 2011-08-12 / Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results. / O sensoriamento remoto de uma tecnologia de extrema import?ncia na atualidade, permitindo a capta??o de dados da superf?cie terrestre que s?o utilizados com diversas finalidades, entre as quais, fiscaliza??o ambiental, acompanhamento de uso dos recursos naturais, prospec??ao geol?gica e monitoramento de cat?strofes. Uma das aplica??es principais do sensoriamento remoto ? a gera??o de mapas tem?ticos e posterior levantamento de ?reas a partir de imagens geradas por sensores orbitais ou sub-orbitais. M?todos de classica??o de padr?es s?o utilizados na implementa??o de rotinas computacionais que automatizem essa atividade. As redes neurais artificiais apresentam-se como m?todos alternativos vi?veis aos classicadores estat?sticos tradicionais, principalmente em aplica??es cujos dados apresentem alta dimensionalidade como os provenientes de sensores hiperespectrais. Este trabalho tem como objetivo principal desenvolver um classicador baseado nas redes neurais de fun??o de base radial e Growing Neural Gas e que apresenta algumas vantagens em rela??o ? utiliza??o individual de redes neurais. A id?ia principal ? utilizar as caracter?sticas incrementais da rede Growing Neural Gas para determinar a quantidade e a escolha de centros da rede de fun??o de base radial com o intuito de obter um classificador altamente ecaz. Para atestar o desempenho do classicador s?o apresentados tr?s estudos de caso juntamente com os resultados obtidos

O presente estudo analisou os efeitos da fratura de côndilo unilateral, no período de crescimento. Para tanto, foram utilizados 50 ratos jovens, linhagem Wistar, com peso até 100g. Sob anestesia geral foi realizada no grupo experimental fratura do processo condilar no lado direito com desvio e no grupo controle-operado, foi feito apenas acesso cirúrgico ao côndilo. O sacrifício dos animais foi feito aos três meses de idade. A mandíbula foi desarticulada sendo obtidas as incidências radiográficas axial do crânio seco e lateral das hemi-mandíbulas. Foram feitas mensurações cefalométricas por meio de um sistema de computador. Foram aplicados os testes estatísticos “t” de Student entre os grupos e teste “t” de Student para dados pareados entre os lados, dentro de cada grupo.Houve diferença significante entre os grupos para o lado direito no comprimento das porções anterior (p=0,001) e posterior (0,017) da maxila e altura do ramo mandibular (p=0,001). Houve diferença significante entre os lados para o comprimento da mandíbula (p<0,001) e altura do ramo mandibular (p<0,001), nos grupos experimental e controle-operado. Houve diferença significante para a altura do corpo mandibular (p=0.001) e para o comprimento das porções anterior (p=0,002) e posterior (p=0,001) da maxila apenas no grupo experimental. Os resultados obtidos permitiram concluir que uma fratura de côndilo mandibular experimental durante o período de crescimento em ratos levou a uma assimetria da mandíbula na altura do corpo mandibular, com conseqüências também para a maxila. / The present study analyzed the effects of the condyle fracture were analyzed in the growing period in this study. Fifty young Wistar rats weighting 100g were used. Under general anestesia fracture of the condilar process on the right side with deviation was performed in the experimental group, while only the made surgical access was performed in the sham-operated group. The animals were sacrifized with three months of age. The mandible was disarticulated, and radiographic projections axial of dried skull and lateral of the hemimandible were obtained. Cephalometric mensurations through a computer system were made. Statistical tests "t" of Student between the groups and paired test "t" of Student among the sides, inside of each group were applied. There was a significant different among the groups to the right side in the length of the anterior portion (p=0,001) and posterior (0,017) of the maxilla and height of the mandibular ramus (p=0,001). There was significant difference among the sides for the length of the mandible (p <0,001) and height of the mandibular ramus (p<0,001), in the height of the body mandibular (p=0.001) and for the length of the anterior portions (p=0,002) and posterior (p=0,001) of the maxilla just in the experimental group. The obtained results allowed to conclude that a experimental fracture of mandibular condyle during the growing period in rats induced an asymmetry of the mandible in the height of the mandibular body, with also consequences to the maxilla.