42 resultados para Flowering network
Resumo:
Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.
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The use of wild oat races in artificial hybridization with cultivated oat (Avena sativa L.) has been used as a way of increasing the variability. This work aimed to identify the variability for plant height and flowering date of groups of cultivated oat genotypes, wild introductions of A. fatua L. and segregating populations of natural crosses between A. sativa and A. fatua. Wide genetic variability was observed for both traits in the groups and between them. The wild group of A. fatua L. showed high plants with early maturity, but in the segregating group there was reduced plant height and early maturity. The wild introductions of A. fatua L. studied in this work can be used in oat breeding programs to increase genetic variability by transferring specific characters into the cultivated germ plasm.
Resumo:
Field experiments involving upland rice genotypes, sown in various dates in late season, were carried out to assess the relationship of carbon isotope discrimination with grain yield and drought resistance. In each one of the three years, one trial was kept under good water availability, while other suffered water shortage for a period of 18-23 days, encompassing panicle emergence and flowering. Drought stress reduced carbon isotope discrimination measured on soluble sugars (deltas) extracted from stem uppermost internode at the end of the imposition period, but had relatively less effect on bulk dry matter of leaves, sampled at the same period, or that of uppermost internodes and grains, sampled at harvest. The drought-induced reduction in deltas was accompanied of reduced spikelet fertility and grain yield. In the three trials subjected to drought, genotypes with the highest yield and spikelet fertility had the lowest deltas. However, this relationship was weak and it was concluded that deltas is not a sufficiently reliable indicator of rice drought resistance to be useful as a screening test in breeding programs. On the other hand, grain yield and spikelet fertility of genotypes which were the soonest to reach 50% flowering within the drought imposition period, were the least adversely affected by drought. Then, timing of drought in relation to panicle emergence and to flowering appeared to be a more important cause of yield variation among genotypes than variation in deltas.
Resumo:
The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.
Resumo:
The objective of this work was to determine the inheritance of the long juvenile period trait in natural variants of the Doko, BR 9 (Savana), Davis, Embrapa 1 (IAS 5RC), and BR 16 soybean cultivars. Complete diallel crosses were made between the Doko and BR 16 cultivars and their variants. A 3:1 segregation ratio was observed in the F2 populations of the 'Doko' x Doko-18T, 'Doko' x Doko-Milionária, 'Davis' x São Carlos, and 'BR 9 (Savana)' x MABR92-836 (Savanão) crosses, indicating that the long juvenile period trait is controlled by a pair of recessive genes. The difference in late flowering between the Doko cultivar and both of its variants was caused by a recessive spontaneous mutation at the same genetic locus. However, the variants Doko-18T and Doko-Milionária are identical mutants that share a pair of genes that control the long juvenile period under short-day conditions. These mutants can be used in breeding programs to develop cultivars adapted to low-latitude tropical regions.
Resumo:
ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.
Resumo:
The objective of this study was to verify the potential of SNAP III (Scheduling and Network Analysis Program) as a support tool for harvesting and wood transport planning in Brazil harvesting subsystem definition and establishment of a compatible route were assessed. Initially, machine operational and production costs were determined in seven subsystems for the study area, and quality indexes, construction and maintenance costs of forest roads were obtained and used as SNAP III program input data. The results showed, that three categories of forest road occurrence were observed in the study area: main, secondary and tertiary which, based on quality index, allowed a medium vehicle speed of about 41, 30 and 24 km/hours and a construction cost of about US$ 5,084.30, US$ 2,275.28 and US$ 1,650.00/km, respectively. The SNAP III program used as a support tool for the planning, was found to have a high potential tool in the harvesting and wood transport planning. The program was capable of defining efficiently, the harvesting subsystem on technical and economical basis, the best wood transport route and the forest road to be used in each period of the horizon planning.
Resumo:
ABSTRACT This study investigates the flowering and pollinators of the floral morphs of three co-occurring distylous species, Psychotria conjugens Müll, P. hastisepala Müll. Arg. and P. sessilis Vell., in two consecutive flowering seasons in an Atlantic Forest fragment in southeastern Brazil. The species have diurnal, cream-colored, tubular, nectariferous flowers and their flowering occurs in the rainy season, from September to April, with little or no overlapping between species, characterizing a staggered flowering. The flowering of the long-and short-styled floral morphs of each species was synchronous, but the number of open flowers per day per morph tended to vary in each flowering season. These numbers were higher in P. sessilis and P. conjugens and, probably, resulted in higher total numbers of visits on its flowers (up to 1084 visits in P. sessilis and 756 in P. conjugens), compared to that observed in P. hastisepala (up to 71). There was a higher frequency of visits to long-styled flowers of all species. The bee Ariphanarthra palpalis was a common pollinator to all species. This bee is native to Brazil, solitary, considered relatively rare and its host plants were unknown. Other native bees (Melipona spp.) also visited the flowers of the Psychotria species. The availability of flowers with similar floral features over eight months, the staggered flowering and common pollinators appear to be part of a strategy to attract floral visitors, minimizing the competition for pollinators and then favoring the legitimate pollination of these plants.
Resumo:
The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.
Resumo:
The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.
Experimental evaluation of the performance of a wireless sensor network in agricultural environments
Resumo:
The aim of this study was to perform an experimental study to evaluate the proper operation distance between the nodes of a wireless sensor network available on the market for different agricultural crops (maize, physic nut, eucalyptus). The experimental data of the network performance offers to farmers and researchers information that might be useful to the sizing and project of the wireless sensor networks in similar situations to those studied. The evaluation showed that the separation of the nodes depends on the type of culture and it is a critical factor to ensure the feasibility of using WSN. In the configuration used, sending packets every 2 seconds, the battery life was about four days. Therefore, the autonomy may be increased with a longer interval of time between sending packets.
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This study aims to analyze the impacts of the reservoir network within Pereira de Miranda - CE catchment (also called Pentecoste) over sediment transport and storage capacity of the system. The survey of the "damming" was carried out using satellite images. We identified 502 erosion units, derived from overlaying maps of the Universal Soil Loss Equation parameters, which allowed the estimation of localized erosion in the basin and identification of areas potentially generating sediment. In order to estimate silting in Pentecoste reservoir, different system structure scenarios were considered. An average erosion rate of 59 t ha-1year-1 was estimated. According to the model, the silting of Pentecoste reservoir may vary from 1.1 to 2.6% per decade, depending on the scenario considered. It is also observed that the reservoirs upstream can retain up to 58% of the sediment that would reach the Pentecoste reservoir. Very small reservoirs with a capacity of up to 100,000 m³, although representing only 1.83% of the system water availability, are able to retain almost 8% of total sediment produced.
Resumo:
The adoption of a proper traceability system is being incorporated into meat production practices as a method of gaining consumer confidence. The various partners operating in the chain of meat production can be considered a social network, and they have the common goal of generating a communication process that can ensure each characteristic of the product, including safety. This study aimed to select the most appropriate meat traceability system “from farm to fork” that could be applied to Brazilian beef and pork production for international trade. The research was done in three steps. The first used the analytical hierarchy process (AHP) for selecting the best on-farm livestock traceability. In the second step, the actors in the meat production chain were identified to build a framework and defined each role in the network. In the third step, the selection of the traceability system was done. Results indicated that with an electronic traceability system, it is possible to acquire better connections between the links in the chain and to provide the means for managing uncertainties by creating structures that facilitate information flow more efficiently.
Resumo:
One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.
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This trial aimed to evaluate the effect of sequential applications of different plant regulators over growth and flower rachis emission of 'Meyer' zoysiagrass (Zoysia japonica). The study was conducted on 15-month old green turfgrass under a randomized complete block design with four replications. The following plant regulator and doses were tested: trinexapac-ethyl (113+113, 226+113, 226+226, 452+113, 452+226, 452+452, 678+339 e 904+452 g a.i./ha-1), prohexadione-calcium (100+100 e 200+200 g a.i. ha-1) and bispyribac-sodium (40+40 e 60+60 g a.i. ha-1), as well as an untreated control. The turfgrass was mowed again at 3.0 cm aboveground and the second plant regulator was applied when 'Meyer' zoysiagrass was between 5.0 and 6.0 cm high. The effect of the treatments was visually rated for visual injury, plant height, height and number of flower rachis, and total dry mass production of clippings. Only bispyribac-sodium had visual symptoms of injury on 'Meyer' zoysiagrass, and no intoxication was observed at 28 days after the second application (DAAB). The sequential applications of trinexapac-ethyl, prohexadione-calcium and bispyribac-sodium reduced by more than 80% the total clipping dry mass produced by 'Meyer' zoysiagrass. All the plant regulators tested also showed promising results in reducing the height and emission of rachis, especially when trinexapac-ethyl was applied at the doses 452+452, 678+339 and 904+452 g a.i. ha-1. 'Meyer' zoysiagrass turfgrass can be handled with the sequential application of a plant regulator, which reduces the need for mowing over a period up to 110 days after the application of the second plant regulator, and it also avoids deleterious visual effects over turfgrass.