945 resultados para Leaf color


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The effect of Heterodera glycines on photosynthesis, leaf area and yield of soybean (Glycine max) was studied in two experiments carried out under greenhouse condition. Soybean seeds were sown in 1.5 l (Experiment 1) or 5.0 l (Experiment 2) clay pots filled with a mixture of field soil + sand (1:1) sterilized with methyl bromide. Eight days after sowing, seedlings were thinned to one per pot, and one day later inoculated with 0; 1.200; 3.600; 10.800; 32.400 or 97.200 J2 juveniles of H. glycines. Experiment 1 was carried out during the first 45 days of the inoculation while Experiment 2 was conducted during the whole cycle of the crop. Measurements of photosynthetic rate, stomatic conductance, chlorophyll fluorescence, leaf color, leaf area, and chlorophyll leaf content were taken at ten-day intervals throughout the experiments. Data on fresh root weight, top dry weight, grain yield, number of eggs/gram of roots, and nematode reproduction factor were obtained at the end of the trials. Each treatment was replicated ten times. There was a marked reduction in both photosynthetic rate and chlorophyll content, as well as an evident yellowing of the leaves of the infected plants. Even at the lowest Pi, the effects of H. glycines on the top dry weight or grain yield were quite severe. Despite the parasitism, soybean yield was highly correlated with the integrated leaf area and, accordingly, the use of this parameter was suggested for the design of potential damage prediction models that include physiological aspects of nematode-diseased plants.

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Despite its outstanding position, the Brazilian citriculture is established on a very limited pool of varieties that limits its expansion and restricts the fruit availability throughout the year. This situation determines the urgent necessity of developing alternative scion and rootstock cultivars, with good performance under local conditions. `Folha Murcha` sweet orange (Citrus sinensis (L.) Osbeck) is a late-harvest cultivar, suitable both for the juice processing industry and the fresh fruit market, being described as tolerant to citrus canker (Xanthomonas citri subsp. citri Schaad et al.), and less affected by citrus variegated chlorosis (Xylella fastidiosa Wells et al.). A study was conducted in Bebedouro, Sao Paulo State, Brazil, to evaluate the horticultural performance of `Folha Murcha` sweet orange budded onto 12 rootstocks: the citrandarin `Changsha` mandarin (Citrus reticulata Blanco) x Poncirus trifoliata `English Small`: the hybrid `Rangpur` lime (Citrus limonia Osbeck) x `Swingle` citrumelo (P. trifoliata (L.) Raf x Citrus paradisi Macfad.); the trifoliates (P. trifoliata (L.) Raf.)`Rubidoux`, `FCAV`, and `Flying Dragon` (P. trifoliata var. monstrosa); the `Sun Chu Sha Kat` mandarin (C. reticulata Blanco); the `Sunki` mandarin (Citrus sunki (Hayata) Hart. ex. Tanaka); the `Rangpur` limes (C. limonia Osbeck) `Cravo Limeira` and `Cravo FCAV`; `Carrizo` citrange (C. sinensis x P. trifoliata), `Swingle` citrumelo (P. trifoliata x C. paradisi), and `Orlando` tangelo (C. paradisi x Citrus tangerina cv. `Dancy`). The experimental grove was planted in 2001, using a 7 m x 4 m spacing, in a randomized block design, with five replications and two plants per plot. No supplementary irrigation was applied. Fruit yield, canopy volume, tree tolerance to drought and to citrus variegated chlorosis, and fruit quality were assessed for each rootstock. Trees grafted onto the `Flying Dragon` trifoliate were smaller in size, but had largest yield efficiency when compared to those grafted onto other rootstocks. Lower alternate bearing index was observed on trees budded onto `Cravo FCAV` `Rangpur` lime. Both `Rangpur` lime rootstocks and the `Sunki` mandarin induced higher tree tolerance to drought. The `Flying Dragon` trifoliate induced better fruit quality and higher tolerance to citrus variegated chlorosis (CVC) to `Folha Murcha` trees. A cluster multivariate analysis identified three groups of rootstocks with similar effects on `Folha Murcha` tree performance. Among the 12 evaluated rootstocks, the `Flying Dragon` trifoliate has a unique effect on plant growth, tolerance to drought and CVC, fruit yield and fruit quality of `Folha Murcha` trees, and may be better suited for high-density plantings. (C) 2011 Elsevier B.V. All rights reserved.

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The objective of this work was to evaluate bean genotypes for resistance to soybean looper (Chrysodeixis includens). Initially, free-choice tests were carried out with 59 genotypes, divided into three groups according to leaf color intensity (dark green, light green, and medium green), in order to evaluate oviposition preference. Subsequently, 12 genotypes with high potential for resistance were selected, as well as two susceptible commercial standards. With these genotypes, new tests were performed for oviposition in a greenhouse, besides tests for attractiveness and consumption under laboratory conditions (26±2ºC, 65±10% RH, and 14 h light: 10 h dark photophase). In the no-choice test with adults, in the greenhouse, the 'IAC Jabola', Arcelina 1, 'IAC Boreal', 'Flor de Mayo', and 'IAC Formoso' genotypes were the least oviposited, showing antixenosis-type resistance for oviposition. In the free-choice test with larvae, Arcelina 4, 'BRS Horizonte', 'Pérola', H96A102-1-1-1-52, 'IAC Boreal', 'IAC Harmonia', and 'IAC Formoso' were the less consumed genotypes, which indicates antixenosis to feeding. In the no-choice test, all genotypes (except for 'IAPAR 57') expressed moderate levels of antixenosis to feeding against C. includens larvae.

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Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. Digital cameras have been successfully used as multi-channel imaging sensors, providing measures of leaf color change information (RGB channels), or leafing phenological changes in plants. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract RGB channels from digital images and correlated with phenological changes. Our first goals were: (1) to test if the color change information is able to characterize the phenological pattern of a group of species; and (2) to test if individuals from the same functional group may be automatically identified using digital images. In this paper, we present a machine learning approach to detect phenological patterns in the digital images. Our preliminary results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; and (2) different plant species present a different behavior with respect to the color change information. Based on those results, we suggest that individuals from the same functional group might be identified using digital images, and introduce a new tool to help phenology experts in the species identification and location on-the-ground. ©2012 IEEE.

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Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The ornamental market is dynamic and demands constant novelties. The use of fruit crops as ornamental plants can be an interesting alternative with very differentiated and original products. The banana germplasm bank at Embrapa Cassava and Fruits has been primarily used in the breeding program for generating new cultivars as food. To diversify and expand the use of this collection, accessions with ornamental potential have been selected to obtain new hybrids. This work was aimed at characterizing the progeny of ornamental Musa L. spp. by grouping the hybrids according to the following uses: landscape plants, potted plants, cut flower, or minifruits. Forty-two hybrids were evaluated with 14 quantitative and 12 qualitative descriptors in three production cycles. In addition, assays for resistance to black and yellow Sigatoka and to Fusarium wilt were performed. Variability was observed for all the characteristics evaluated within progenies, especially with regard to leaf color, fruit, peduncle, rachis, and heart. All evaluated hybrids were resistant to yellow Sigatoka and to Fusarium wilt and were resistant or showed reduced symptoms of susceptibility to black Sigatoka. Most hybrids (82%) presented reduced plant height. After clustering by use category, the hybrids RM 09, RM 38, RM 37, and RM 33 were selected and recommended to be used as cut flowers, minifruits, or landscaping plants.

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Despite considerable research conducted on 'Tahiti' lime [Citrus latifolia (Yu Tanaka) Tanaka] in several countries, few long-term studies have focused on rootstock effects on fruit production and quality under non-irrigated conditions. As for many other fruit crops, rootstock studies for 'Tahiti' lime are often based on the evaluation of several horticultural responses simultaneously, instead of considering multivariate statistical approaches which may provide with more comprehensive information. Consequently, a trial was installed to evaluate the horticultural performance of non-irrigated 'Tahiti' lime trees budded onto the following 12 rootstocks: 'HRS 801' and 'HRS 827' hybrids; 'Rubidoux', 'FCAV' and 'Flying Dragon' trifoliates; 'Sun Chu Sha Kat' and 'Sunki' mandarins; 'Cravo Limeira' and 'Cravo FCAV' 'Rangpur' limes; 'Carrizo' citrange, 'Swingle' citrumelo, and 'Orlando' tangelo. The trial was installed in 2001, in an 8 m x 5 m spacing with no supplementary irrigation. Measurements of yield, fruit quality oriented to different consuming markets, canopy volume and tree tolerance to drought, were performed. A multivariate cluster analysis identified both 'Rangpur' lime rootstocks as those inducing larger cumulative yield and higher percentage of fruits for the domestic market, with highest drought tolerance to the trees. Despite of their high susceptibility to drought stress under non-irrigated conditions, the 'Flying Dragon' and 'FCAV' trifoliate rootstocks performed outstandingly for 'Tahiti' lime, inducing higher yield efficiency, early bearing and larger percentage of high-quality fruits for foreign markets, with smaller trees more suitable for high-density plantings. (c) 2012 Elsevier B.V. All rights reserved.

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Os métodos tradicionais para a quantificação de clorofilas implicam na destruição das folhas, além de serem demorados e dispendiosos. Uma alternativa aos métodos destrutivos é o uso de medidores portáteis, dentre eles o SPAD 502, que mede a intensidade da cor verde das folhas, resultando no índice SPAD (Soil Plant Analysis Development). No entanto, o índice SPAD deve ser ajustado para o teor de clorofilas, conforme a espécie de interesse. O objetivo do presente trabalho foi calibrar o índice SPAD para a quantificação de clorofilas em folhas de plantas de vime ( Salix viminalis ). Folhas desta espécie, com tonalidade variando de verde-amarelada (clorótica) a verde-escura, foram avaliadas individualmente com o SPAD-502, seguido de quantificações destrutivas dos teores de clorofilas a, b e totais, expressos em unidade de área e massa fresca foliar. Houve elevado coeficiente de determinação (R²) entre os valores de índice SPAD e os teores de clorofila a, b e totais nas folhas, expressos em μg cm-2 de área foliar (R² de 0,86; 0,88 e 0,93, respectivamente) e entre os valores de índice SPAD e os teores de clorofilas b e totais, expressos em μg g-1 de massa fresca (R² 0,79 e 0,81, respectivamente). Os resultados mostram que existe viabilidade no uso do clorofilômetro SPAD 502, como alternativa aos métodos destrutivos, para a quantificação de clorofilas (em unidade de área; μg cm-2) em folhas de vimeiro.

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Tissue N analysis a tool available for N management of turfgrass. However, peer-reviewed calibration studies to determine optimum tissue N values are lacking. A field experiment with a mixed cool-season species lawn and a greenhouse experiment with Kentucky bluegrass (Poa pratensis L.) were conducted across 2 yr, each with randomized complete block design. Treatments were N application rates between 0 and 587 kg N ha-1 yr-1. In the field experiment, clipping samples were taken monthly from May to September, dried, ground, and analyzed for total N. Clippings samples were collected one to two mowings after plots were fertilized. Linear plateau models comparing relative clipping yield, Commission Internationale de l' Eclairage hue, and CM1000 index to leaf N concentrations were developed. In the greenhouse experiment, clipping samples were taken every 2 wk from May to October and composited across sample dates for leaf N analysis. Color and clipping yields were related to leaf N concentrations using linear plateau models. These models indicated small marginal improvements in growth or color when leaf N exceeded 30 g kg-1, suggesting that a leaf N test can separate turf with optimum leaf N concentrations from turf with below optimum leaf N concentrations. Plateaus in leaf N concentrations with increasing N fertilizer rates suggest, however, that this test may be unable to identify sites with excess available soil N when turf has been mowed before tissue sampling.

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Pea-shoots are a new option as ready-to-eat baby-leaf vegetable. However, data about the nutritional composition and the shelf-life stability of these leaves, especially their phytonutrient composition is scarce. In this work, the macronutrient, micronutrient and phytonutrients profile of minimally processed pea shoots were evaluated at the beginning and at the end of a 10-day storage period. Several physicochemical characteristics (color, pH, total soluble solids, and total titratable acidity) were also monitored. Standard AOAC methods were applied in the nutritional value evaluation, while chromatographic methods with UV–vis and mass detection were used to analyze free forms of vitamins (HPLC-DAD-ESI-MS/MS), carotenoids (HPLC-DAD-APCI-MSn) and flavonoid compounds (HPLC-DAD-ESI-MSn). Atomic absorption spectrometry (HR-CS-AAS) was employed to characterize the mineral content of the leaves. As expected, pea leaves had a high water (91.5%) and low fat (0.3%) and carbohydrate (1.9%) contents, being a good source of dietary fiber (2.1%). Pea shoots showed a high content of vitamins C, E and A, potassium and phosphorous compared to other ready-to-eat green leafy vegetables. The carotenoid profile revealed a high content of β-carotene and lutein, typical from green leafy vegetables. The leaves had a mean flavonoid content of 329 mg/100 g of fresh product, mainly composed by glycosylated quercetin and kaempferol derivatives. Pea shoots kept their fresh appearance during the storage being color maintained throughout the shelf-life. The nutritional composition was in general stable during storage, showing some significant (p < 0.05) variation in certain water-soluble vitamins.