Detection of Disease and Pest of Kenaf Plant Based on Image Recognition with VGGNet19

One of the advantages of Kenaf fiber as an environmental management product that is currently in the center of attention is the use of Kenaf fiber for luxury car interiors with environmentally friendly plastic materials. The opportunity to export Kenaf fiber raw material will provide significant benefits, especially in the agricultural sector in Indonesia. However, there are problems in several areas of Kenaf's garden, namely plants that are attacked by diseases and pests, which cause reduced yields and even death. This problem is caused by the lack of expertise and working hours of extension workers as well as farmers' knowledge about Kenaf plants which have a terrible effect on Kenaf plants. The development of information technology can be overcome by imparting knowledge into machines known as artificial intelligence. In this study, the Convolutional Neural Network method was applied, which aims to identify symptoms and provide information about disease symptoms in Kenaf plants based on images so that early control of plant diseases can be carried out. Data processing trained directly from kenaf plantations obtained an accuracy of 57.56% for the first two classes of introduction to the VGGNet19 architecture and 25.37% for the four classes of the second introduction to the VGGNet19 architecture. The 5×5 block matrix input feature has been added in training to get maximum results

Branching Boogaloo: Botanical Adventures in Multi-Mediated Morphologies

FormaLeaf is a software interface for exploring leaf morphology using parallel string rewriting grammars called L-systems. Scanned images of dicotyledonous angiosperm leaves removed from plants around Bard’s campus are displayed on the left and analyzed using the computer vision library OpenCV. Morphometrical information and terminological labels are reported in a side-panel. “Slider mode” allows the user to control the structural template and growth parameters of the generated L-system leaf displayed on the right. “Vision mode” shows the input and generated leaves as the computer ‘sees’ them. “Search mode” attempts to automatically produce a formally defined graphical representation of the input by evaluating the visual similarity of a generated pool of candidate leaves. The system seeks to derive a possible internal structural configuration for venation based purely off a visual analysis of external shape. The iterations of the generated L-system leaves when viewed in succession appear as a hypothetical development sequence. FormaLeaf was written in Processing

Phylogenetics and biogeography of two clades of Cucurbitaceae

The gourd family, Cucurbitaceae, is among the economically most important families of plants, with many crop species that form the basis of multi-million dollar industries. Knowledge of these species’ geographic origin and their closest wild relatives is fundamental to breeding efforts, genetic improvement, and conservation. Surprisingly, these aspects have been unknown or misunderstood for many widely cultivated species, even though plant material that could have been used for broad phylogenetic studies has long been available in herbaria. For the thesis presented here, I focused on the phylogenetic relationships within two clades of Cucurbitaceae that comprise cultivated species: the genus Cucumis, to which cucumber (Cucumis sativus) and melon (Cucumis melo) belong, and the New World Sicyoeae, which contain vegetable pear or chayote (Sicyos (Sechium) edulis) and tacaco (Frantzia tacaco), locally important in Mexico and Costa Rica, and the former also cultivated worldwide. I used a combination of DNA sequence data from up to 175-year old herbarium specimens and molecular phylogenetic methods as well as traditional morphological and ecological data from my own fieldwork in Asia and Australia to infer the phylogenetic relationships among these clades. I also discovered and described several new species, and reconstructed plausible scenarios for the two clades’ geographical unfolding over time. Until recently, only two species of Cucumis, namely cucumber and its closest relative C. hystrix, were thought to be of Asian origin, and melon was thought to have originated in Africa, from where 30 species were known. Using DNA sequences from plastid and nuclear markers for some 100 Cucumis accessions from Africa, Australia, and Asia, I have shown that cucumber and melon both are of Asian (probably Indian) origin and form a clade with 23 previously overlooked species-level relatives in Asia, Australia, and around the Indian Ocean, at least nine of them new to science and some described as part of this thesis. Fieldwork I carried out in Thailand and Australia contributed new knowledge about the life forms and habitats of some of these species and resulted in fertile material essential for the descriptions. My study furthermore revealed that the sister species of melon is the re-discovered C. picrocarpus from Australia. Future breeding efforts and investigations of wild species related to melon and cucumber should therefore concentrate on Asia and Australia, instead of Africa. In my second study group, the Sicyoeae, my aim was to test long-problematic generic boundaries and to reconstruct the history of the tribe’s name-giving genus, Sicyos, which has an exceptional geographical distribution. Using a densely sampled molecular phylogeny that included type species of 23 currently or formerly accepted genera of Sicyoeae, I showed that morphology-based concepts did not result in monophyletic genera, and that species from numerous smaller genera, including chayote, need to be part of Sicyos if monophyly is to be established. Sicyos, in its new circumscription, has a center of distribution in the Neotropics, where c. 50 species occur, but long-distance dispersal has resulted in the group’s presence on Hawaii (where it radiated into 14 species), at least two arrivals on the Galápagos archipelago (but no radiations), and one arrival in Australia and New Zealand, now with three species, two of them new to science. Using molecular clock models, I dated these four trans-Pacific dispersal events, all from the American mainland, to the last 4.5 to 1 million years. The mode of dispersal may have been adherence of the small, spiny fruits to birds, which would fit with the documented occurrence of Sicyos plants near seabird nesting colonies. The rapid diversification on Hawaii may have followed the loss of the fruit spines in the ancestor of the 14 Hawaiian species, leading to lower dispersal ability and faster allopatric speciation in the diverse habitats of the archipelago

Contributions from the United States National Herbarium

v.38(1974

Bioassay-Guided Metabolomic Fingerprinting Analysis of Mediterranean plants using GC-MS and NMR spectroscopy

In our study, the metabolomic fingerprinting analysis of leaves and roots of eight Mediterranean plants was made by an integrated approach of GC-MS and NMR spectroscopic techniques targeted on apolar and polar metabolites respectively, following bioassay test focused on antifungal activity against two phytopathogenic fungi, Trichoderma harzianum and Aspergillus niger. The eight plant species included two perennial forbs (Dittrichia viscosa, Acanthus mollis), two grasses (Typha latifolia, Festuca drymeia), one vine (Hedera helix), one evergreen tree (Quercus ilex), and two deciduous trees (Fraxinus ornus, Fagus sylvatica), which have been used as traditional folk remedy. The research aimed at evaluating the chemical compositions of the different species both from a qualitative and a quantitative point of view, to identify the major classes of apolar and polar compounds and to integrate the spectra followed by chemometrics. The highlights of the undertaken work were: i) using an integrated approach of GC-MS and NMR spectroscopic techniques to make an intensive investigation of apolar and polar metabolites of leaves and roots of each species; ii) comparing the variation of metabolite contents in leaves and roots of eight plants simultaneously; iii) correlating internal physiologic properties (chemical profile) with the external bioactivity (antifungal activity) on some degree. The metabolic fingerprint of the Mediterranean plants showed a complex chemical composition, being specific for each species and plant tissue. Some conclusions were drew as described. Through analyzing the apolar extracts of leaf and root samples of eight species by GC-MS, combined with interpreting method of AMDIS, it was showed that apolar organic extracts were mainly composed of linear saturated fatty acids; 120 apolar metabolites, including fatty acids, n-alkanes, triterpenoids, steroids and oxygenated terpenoids were found. The exceptions were that major apolar metabolites were oxygenated terpenoids in D. viscosa leaf and unsaturated fatty acids with the richest component being linoleic acid in H. helix root, accounting for the observed antifungal activity. Triterpenoids and steroids were almost exclusively found in roots. Through analyzing the polar extracts of leaf and root samples of eight species by 1H-NMR, followd by statistical method of Principle Component Analysis (PCA), we found that extracts contained a total of 38 polar metabolites among all samples, including sugars, alkaloids, organic acids, free amino acids and aromatic compounds. Q. ilex and F. ornus contained large amounts of specific metabolites, quinic acid, quercitol and mannitol. D. viscosa and T. latifolia were characterized by a high content of aromatic compounds. The separation of A. mollis from the other species was due to the presence of betaine and sucrose in leaves and raffinose in roots. Hence, we could conclude that the research developed with the proposed approach possess the advantages of versatility and rapidity, thus making it suitable for a fast comparison among species and plant tissue types

Evolutionary diversification and historical biogeography of orchidaceae in Central America with emphasis on Costa Rica and Panama

In this thesis, I targeted the orchid genus Lepanthes, one of the six genera of angiosperms that surpasses 1,000 species in the Neotropics, as a study model to investigate the evolutionary processes that promoted species diversifications. To investigate this, we improved the taxonomy of the group integrating a solid phylogenetic framework with morphological evolution, assessing inter-specific relationships in species complexes with hundreds of DNA markers using anchored hybrid enrichment approach, and describing new species. In addition, we addressed the pollination of Trichosalpinx through the study of floral anatomy, pollinator behavior, and floral traits. Trichosalpinx flowers are pollinated exclusively by female biting midges that are attracted by the small quantities of proteins secreted on the flowers. Finally, we inferred the biogeographical history and diversification dynamics of the two largest Neotropical orchid groups (Cymbidieae and Pleurothallidinae), using densely sampled phylogenies coupled with geological datasets and discussed the impact of biogeographical events and orogeny on the species richness of Lepanthes. Species diversification is correlated with Andean orogeny, and multiple migrations and recolonizations across the Andes indicate that mountains do not constrain orchid dispersal over long timescales. This thesis provides new insights into the complex evolution of one of the most species-rich angiosperm.Leiden University/[]//Países BajosCentro de Biodiversidad Naturalis/[]//Países BajosUniversidad de Costa Rica/[]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Jardín Botánico Lankester (JBL

A neuro-genetic hybrid approach to automatic identification of plant leaves

Plants are essential for the existence of most living things on this planet. Plants are used for providing food, shelter, and medicine. The ability to identify plants is very important for several applications, including conservation of endangered plant species, rehabilitation of lands after mining activities and differentiating crop plants from weeds. In recent times, many researchers have made attempts to develop automated plant species recognition systems. However, the current computer-based plants recognition systems have limitations as some plants are naturally complex, thus it is difficult to extract and represent their features. Further, natural differences of features within the same plant and similarities between plants of different species cause problems in classification. This thesis developed a novel hybrid intelligent system based on a neuro-genetic model for automatic recognition of plants using leaf image analysis based on novel approach of combining several image descriptors with Cellular Neural Networks (CNN), Genetic Algorithm (GA), and Probabilistic Neural Networks (PNN) to address classification challenges in plant computer-based plant species identification using the images of plant leaves. A GA-based feature selection module was developed to select the best of these leaf features. Particle Swam Optimization (PSO) and Principal Component Analysis (PCA) were also used sideways for comparison and to provide rigorous feature selection and analysis. Statistical analysis using ANOVA and correlation techniques confirmed the effectiveness of the GA-based and PSO-based techniques as there were no redundant features, since the subset of features selected by both techniques correlated well. The number of principal components (PC) from the past were selected by conventional method associated with PCA. However, in this study, GA was used to select a minimum number of PC from the original PC space. This reduced computational cost with respect to time and increased the accuracy of the classifier used. The algebraic nature of the GA’s fitness function ensures good performance of the GA. Furthermore, GA was also used to optimize the parameters of a CNN (CNN for image segmentation) and then uniquely combined with PNN to improve and stabilize the performance of the classification system. The CNN (being an ordinary differential equation (ODE)) was solved using Runge-Kutta 4th order algorithm in order to minimize descritisation errors associated with edge detection. This study involved the extraction of 112 features from the images of plant species found in the Flavia dataset (publically available) using MATLAB programming environment. These features include Zernike Moments (20 ZMs), Fourier Descriptors (21 FDs), Legendre Moments (20 LMs), Hu 7 Moments (7 Hu7Ms), Texture Properties (22 TP) , Geometrical Properties (10 GP), and Colour features (12 CF). With the use of GA, only 14 features were finally selected for optimal accuracy. The PNN was genetically optimized to ensure optimal accuracy since it is not the best practise to fix the tunning parameters for the PNN arbitrarily. Two separate GA algorithms were implemented to optimize the PNN, that is, the GA provided by MATLAB Optimization Toolbox (GA1) and a separately implemented GA (GA2). The best chromosome (PNN spread) for GA1 was 0.035 with associated classification accuracy of 91.3740% while a spread value of 0.06 was obtained from GA2 giving rise to improved classification accuracy of 92.62%. The PNN-based classifier used in this study was benchmarked against other classifiers such as Multi-layer perceptron (MLP), K Nearest Neigbhour (kNN), Naive Bayes Classifier (NBC), Radial Basis Function (RBF), Ensemble classifiers (Adaboost). The best candidate among these classifiers was the genetically optimized PNN. Some computational theoretic properties on PNN are also presented

Assessing variability in yield performance and nutritional quality of citron watermelon (citrullus lanatus var. citroides (L.H. Bailey) mansf. ex greb.) genotypes under drought conditions.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Research is needed to investigate the potential of Neglected Underutilized Crop Species (NUCS) such as citron watermelon, to increase crop diversity and mitigate the effects of prolonged drought because of climate change. Little is known about citron watermelon’s food quality attributes (seed popping yield, nutritional value, and lignin content). In addition, there is a need to understand the agro-morphological, physiological and biochemical characteristics associated with drought tolerance in citron watermelon. Therefore, the objectives of this study were: (1) to assess citron watermelon genotypes for food quality attributes (popping yield, chewability and nutritive value) of seeds based on visual appearance, (2) to screen citron watermelon accessions for drought tolerance using morphological and physiological traits, (3) to study the root system architecture of citron watermelon accessions and identify droughtadaptive root traits for cultivar improvement under water-stressed environments and (4) to reveal how citron watermelon responds to combined stress (water deficit and high temperature) with respect to growth, water status, reserve mobilization and metabolite partitioning at seedling stage. The first study determined whether citron watermelon seed’s nutrient composition and physical properties are related to the visual appearance of seed coat. Brown and red-coloured seeds have a higher popping yield than dark-coloured seeds with poor popping ability and are prone to burning during roasting. Seed coat thickness was closely related to hemicellulose contents and cellulose across all seed coat colours. High hemicellulose, cellulose and lignin contents were found in dark and red seeds associated with thick seed coats and increased chewing strength than white seeds. From a nutritional perspective, dark and red seeds were good sources of Cu, Zn, nitrogen and sulfur than brown seeds. Dark and brown seeds were good Mg sources, whereas dark and red seeds were vital sources of potassium. The second study determined variation in drought tolerance among South African citron watermelon landrace accessions for selection and use as genetic stock for drought-tolerance breeding in this crop and closely related cucurbit crops such as sweet watermelon. The forty citron watermelon accessions evaluated showed varying levels of drought tolerance based on morphological and physiological traits. These allowed five distinct groupings, namely: A (highly drought-tolerant), B (drought-tolerant), C (moderately drought tolerant), D (droughtsensitive) and E (highly drought-sensitive) based on various drought tolerance indices. The following accessions (WWM02, WWM-05, WWM-09, WWM-15, WWM-37(2), WWM-39, WWM-41 (A), WWM-46, WWM-47, WWM-57, WWM-64, WWM-66, WWM-68 and WWM-79) were categorized as highly-drought tolerant and accessions WWM-03, WWM-08, WWM-14, WWM-21, WWM-33, WWM-35(1), WWM-35(2), WWM-67 and WWM-76 as drought tolerant. These are useful genetic stocks for improving drought tolerance in this crop and related cucurbit crops, including sweet watermelon. The third study examined citron watermelon accessions’ root system architecture and identified drought-adaptive root traits for cultivar improvement under water-stressed environments. The study showed that plasticity and biomass allocation shift according to genotype, presumably to optimise the use of limited resources. The study found significant phenotypic variation in root architecture among citron watermelon accessions that may relate to differences in water uptake. The following traits of root system architecture (RSA) (total root length, root system width, convex hull area and total root volume) were associated with drought tolerance. Further, RSA traits such as root dry mass and root shoot mass ratio were highly correlated with root branch count, root system depth, total root length and leaf number. These traits are useful selection criteria for breeding and developing water-efficient citron watermelon accessions for cultivation in drought-prone environments. The fourth study identified multiple abiotic stress-induced modifications in different phytosterols (campesterol, sitosterol and stigmasterol) in the seedling axis (embryonic leaf and root) of genetically distinct citron watermelon accessions. Detailed evaluation of phytosterols was done and the effects of the changes observed in stressed plants were discussed

Plant secondary metabolites in Peucedanum palustre and Angelica archangelica and their plant cell cultures

A reversed-phase, high-performance liquid chromatographic method (RP-HPLC) with atmospheric pressure chemical ionisation mass spectrometry (APCI-MS) detection was developed utilising Turbo Method Development® and DryLab® programmes for the separation and identification of coumarins in Peucedanum palustre L. (Moench) and Angelica archangelica (L.) var. archangelica both belonging to the endemic flora of Finland. Fifteen coumarins were identified both in P. palustre and in A. archangelica. This is the first report on the xanthotoxin, isopimpinellin, pimpinellin, and coumarin composition of the umbels of P. palustre. The coumarin composition of Finnish P. palustre populations was analyzed and verified chromatographically. The main coumarin in roots was oxypeucedanin, and in aerial parts peulustrin/isopeulustrin. The highly varying total coumarin concentration was the highest in umbels and the lowest in stems. Leaves and roots contained comparable amounts of coumarins. The total coumarin concentration decreased towards the north. As regards the aerial parts, the coumarin content of the umbels and leaves resembled each other the most. The effective temperature sum clearly correlated with the coumarin concentrations of the aerial parts, but not with the roots of the plant. The study did not support the existence of chemotypes in Finnish P. palustre populations. A spontaneously embryogenic cell line of A. archangelica was established from seedlings via callus formation. The highest coumarin production was achieved after three weeks of cultivation in the medium containing 3.0% sucrose. Cryopreservation was found to be a suitable method for storing the cell line. Plantlets propagated in an air-sparged bioreactor were transferable directly to soil. The coumarin composition and levels in the regenerated plants were comparable to those in intact plants. A mathematical computer-aided model CELLOP was constructed in which the desirability functions in a three-dimensional experimental design are used for optimising the growing conditions for plant cultures. The calcium, inorganic nitrogen, and sucrose concentrations in the medium were optimised for coumarin-producing, spontaneously embryogenic cell lines of A. archangelica and P. palustre. In comparison to the reference, the dry mass for A. archangelica was 24.7% and the coumarin concentration 40.5% higher in the optimised conditions, and the dry mass for P. palustre 61.8% and the coumarin concentration 58.1% higher. For A. archangelica the highest embryogenic activity occurred in the medium containing 1.25 mM calcium and for P. palustre in the medium containing 50.0 mM NO3- and 4.01 mM NH4+.Suomessa luonnonvaraisina kasvavien suoputken Peucedanum palustre L. (Moench) ja väinönputken Angelica archangelica (L.) var. archangelica sisältämien kumariinien erottamiseksi ja tunnistamiseksi kehitettiin analyysimenetelmä Turbo Method Development® and DryLab® menetelmänkehitysohjelmien avulla. Käänteisfaasi-suuren erotuskyvyn nestekromatografia (RP-HPLC) yhdessä ilmakehänpaineessa tapahtuvan kemiallisen ionisaation massaspektrometrian (APCI-MS) kanssa mahdollisti viidentoista kumariinirakenteisen yhdisteen tunnistamisen kummastakin kasvista, joista ksantotoksiini, isopimpinelliini ja pimpinelliini löydettiin ensimmäistä kertaa suoputkessa. Tämä on myös ensimmäinen raportti suoputken kukinnon kumariinikoostumuksesta. Suomalaisten suoputkipopulaatioiden kumariinikoostumus määritettiin ja varmennettiin kromatografisesti. Pääkumariini juurissa oli oksipeusedaniini ja maanpäällisissä osissa peulustriini/isopeulustriini. Suuresti vaihteleva kumariinipitoisuus oli korkein kukinnoissa ja alhaisin varsissa. Lehdet ja juuret sisälsivät kumariineja samansuuruisia määriä. Maanpäällisissä osissa kukintojen ja lehtien kumariinikoostumus muistutti eniten toisiaan. Kokonaiskumariinipitoisuus pieneni kasveissa pohjoista kohti. Kasvupaikan tehollinen lämpösumma korreloi selvästi maanpäällisten osien kumariinipitoisuuden kanssa mutta ei juurien sisältämien kumariinien kanssa. Tutkimuksessa ei saatu näyttöä erilaisten kemotyyppien olemassaolosta suomalaisissa suoputkipopulaatioissa. Spontaanisti embrygeeninen solulinja saatiin aikaiseksi väinönputken taimien muodostamasta haavasolukosta. Uuden solulinjan kumariinipitoisuus oli korkein kolmen viikon kasvatuksen jälkeen 3 % sakkaroosia sisältävässä kasvatusalustassa. Syväjäädytyksen todettiin sopivan solulinjan pitkäaikaissäilytykseen. Ilmastetussa bioreaktorissa saatiin tuotettua taimia, jotka voitiin istuttaa suoraan multaan. Uudesta solulinjasta lisättyjen ja kasvatettujen kasvien laadullinen ja määrällinen kumariinikoostumus vastasivat luonnonvaraisia kasveja. Kasvisoluviljelmien kasvatusolosuhteiden optimointiin kehitettiin matemaattinen tietokoneavusteinen malli CELLOP, joka perustuu desirabiliteettifunktioiden käyttöön kolmiulotteisessa koejärjestelmässä. Kasvatusalustan kalsiumin, epäorgaanisen typen ja sakkaroosin pitoisuudet optimoitiin kumariineja tuottaville, spontaanisti embryogeenisille väinönputken ja suoputken soluviljelmille. Optimoiduissa olosuhteissa väinönputken kuivamassa oli 24,7 % ja kumariinipitoisuus 40,5 % korkeampi ja suoputken kuivamassa oli 61,8 % ja kumariinipitoisuus 58,1 % korkeampi kuin vertailukasvualustassa. Väinönputken korkein embryogeeninen aktiivisuus saavutettiin 1,25 mM kalsiumia sisältävässä kasvatusalustassa, ja suoputkella kasvatusalustassa, jonka nitraattipitoisuus oli 50,0 mM ja ammoniumpitoisuus 4,01 mM