Use efficiency of variable rate of nitrogen prescribed by optical sensor in corn

ABSTRACT The efficiency of nitrogen fertilizer in corn is usually low, negatively affecting plant nutrition, the economic return, and the environment. In this context, a variable rate of nitrogen, prescribed by crop sensors, has been proposed as an alternative to the uniform rate of nitrogen traditionally used by farmers. This study tested the hypothesis that variable rate of nitrogen, prescribed by optical sensor, increases the nitrogen use efficiency and grain yield as compared to uniform rate of nitrogen. The following treatments were evaluated: 0; 70; 140; and 210 kg ha-1 under uniform rate of nitrogen, and 140 kg ha -1 under variable rate of nitrogen. The nitrogen source was urea applied on the soil surface using a distributor equipped with the crop sensor. In this study, the grain yield ranged from 10.2 to 15.5 Mg ha-1, with linear response to nitrogen rates. The variable rate of nitrogen increased by 11.8 and 32.6% the nitrogen uptake and nitrogen use efficiency, respectively, compared to the uniform rate of nitrogen. However, no significant increase in grain yield was observed, indicating that the major benefit of the variable rate of nitrogen was reducing the risk of environmental impact of fertilizer.

Optical crop sensor for variable-rate nitrogen fertilization in corn: i - plant nutrition and dry matter production

Variable-rate nitrogen fertilization (VRF) based on optical spectrometry sensors of crops is a technological innovation capable of improving the nutrient use efficiency (NUE) and mitigate environmental impacts. However, studies addressing fertilization based on crop sensors are still scarce in Brazilian agriculture. This study aims to evaluate the efficiency of an optical crop sensor to assess the nutritional status of corn and compare VRF with the standard strategy of traditional single-rate N fertilization (TSF) used by farmers. With this purpose, three experiments were conducted at different locations in Southern Brazil, in the growing seasons 2008/09 and 2010/11. The following crop properties were evaluated: above-ground dry matter production, nitrogen (N) content, N uptake, relative chlorophyll content (SPAD) reading, and a vegetation index measured by the optical sensor N-Sensor® ALS. The plants were evaluated in the stages V4, V6, V8, V10, V12 and at corn flowering. The experiments had a completely randomized design at three different sites that were analyzed separately. The vegetation index was directly related to above-ground dry matter production (R² = 0.91; p<0.0001), total N uptake (R² = 0.87; p<0.0001) and SPAD reading (R² = 0.63; p<0.0001) and inversely related to plant N content (R² = 0.53; p<0.0001). The efficiency of VRF for plant nutrition was influenced by the specific climatic conditions of each site. Therefore, the efficiency of the VRF strategy was similar to that of the standard farmer fertilizer strategy at sites 1 and 2. However, at site 3 where the climatic conditions were favorable for corn growth, the use of optical sensors to determine VRF resulted in a 12 % increase in N plant uptake in relation to the standard fertilization, indicating the potential of this technology to improve NUE.

Optical crop sensor for variable-rate nitrogen fertilization in corn: II - indices of fertilizer efficiency and corn yield

Generally, in tropical and subtropical agroecosystems, the efficiency of nitrogen (N) fertilization is low, inducing a temporal variability of crop yield, economic losses, and environmental impacts. Variable-rate N fertilization (VRF), based on optical spectrometry crop sensors, could increase the N use efficiency (NUE). The objective of this study was to evaluate the corn grain yield and N fertilization efficiency under VRF determined by an optical sensor in comparison to the traditional single-application N fertilization (TSF). With this purpose, three experiments with no-tillage corn were carried out in the 2008/09 and 2010/11 growing seasons on a Hapludox in South Brazil, in a completely randomized design, at three different sites that were analyzed separately. The following crop properties were evaluated: aboveground dry matter production and quantity of N uptake at corn flowering, grain yield, and vegetation index determined by an N-Sensor® ALS optical sensor. Across the sites, the corn N fertilizer had a positive effect on corn N uptake, resulting in increased corn dry matter and grain yield. However, N fertilization induced lower increases of corn grain yield at site 2, where there was a severe drought during the growing period. The VRF defined by the optical crop sensor increased the apparent N recovery (NRE) and agronomic efficiency of N (NAE) compared to the traditional fertilizer strategy. In the average of sites 1 and 3, which were not affected by drought, VRF promoted an increase of 28.0 and 41.3 % in NAE and NRE, respectively. Despite these results, no increases in corn grain yield were observed by the use of VRF compared to TSF.

Development of an optical redox chemical sensor for nitrite determination

An optical chemical sensor for the determination of nitrite based on incorporating methyltrioctylammonium chloride as an anionic exchanger on the triacetylcellulose polymer has been reported. The response of the sensor is based on the redox reaction between nitrite in aqueous solution and iodide adsorbed on sensing membrane using anion exchange phenomena. The sensing membrane reversibly responses to nitrite ion over the range of 6.52×10-6 - 8.70×10-5 mol L-1 with a detection limit of 6.05×10-7 mol L-1 (0.03 µg mL-1) and response time of 6 min. The relative standard deviation for eight replicate measurements of 8.70×10-6 and 4.34×10-5 mol L-1 of nitrite was 4.4 and 2.5 %, respectively. The sensor was successfully applied for determination of nitrite in food, saliva and water samples.

Sugarcane response to nitrogen rates, measured by a canopy reflectance sensor

Abstract:The objective of this work was to evaluate whether a canopy sensor is capable of estimating sugarcane response to N, as well as to propose strategies for handling the data generated by this device during the decision-making process for crop N fertilization. Four N rate-response experiments were carried out, with N rates varying from 0 to 240 kg ha-1. Two evaluations with the canopy sensor were performed when the plants reached average stalk height of 0.3 and 0.5 m. Only two experiments showed stalk yield response to N rates. The canopy sensor was able to identify the crop response to different N rates and the relationship of the nutrient with sugarcane yield. The response index values obtained from the canopy sensor readings were useful in assessing sugarcane response to the applied N rate. Canopy reflectance sensors can help to identify areas responsive to N fertilization and, therefore, improve sugarcane fertilizer management.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Uso de membranas de Nafion para a construção de sensores ópticos para medidas de pH

The behaviour of Nafion® polymeric membranes containing acid-base dyes, bromothymol blue (BB) and methyl violet (MV), were studied aiming at constructing an optical sensor for pH measurement. BB revealed to be inadequate for developing sensing phases due to the electrostatic repulsion between negative groups of their molecules and the negative charge of the sulfonate group of the Nafion®, which causes leaching of the dye from the membrane. On the other hand, MV showed to be suitable due to the presence of positive groups in its structure. The membrane prepared from a methanolic solution whose Nafion®/dye molar ratio was 20 presented the best analytical properties, changing its color from green to violet in the pH range from 0.6 to 3.0. The membrane can be prepared with good reproducibility, presenting durability of ca. 6 months and response time of 22 s, making possible its use for pH determination in flow analysis systems.

Alternative technique for biodiesel quality control using an optical fiber long-period grating sensor

We report the use of an optical fiber sensor to measure the soybean oil concentration in samples obtained from the mixture of pure biodiesel and commercial soybean oil. The operation of the device is based on the long-period grating sensitivity to the surrounding medium refractive index, which leads to measurable modifications in the grating transmission spectrum. The proposed analysis method results in errors in the oil concentration of 0.4% and 2.6% for pure biodiesel and commercial soybean oil, respectively. Techniques of total glycerol, dynamic viscosity, density, and hydrogen nuclear magnetic resonance spectroscopy were also employed to validate the proposed method.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Utilização do sensor linear de luz ILX554 em espectroscopia óptica

This technical note describes the construction of a low-cost optical detector. This device is composed by a high-sensitive linear light sensor (model ILX554) and a microcontroller. The performance of the detector was demonstrated by the detection of emission and Raman spectra of the several atomic systems and the results reproduce those found in the literature.

O USO DE UM SENSOR DE LUZ LINEAR COMO RECURSO DIDÁTICO PARA DEMONSTRAR PRINCÍPIOS DE DIFRAÇÃO E ESPECTROSCOPIA

This article presents a discussion on light diffraction by slits and grids as well as the development of an experimental apparatus which provides quantitative observation of the phenomenon. We conducted a brief historical survey on the evolution of the wave theory of light and the role of diffraction in the context of optical spectroscopy. We also reviewed the use of Huygens’ principle to calculate the intensity pattern obtained when light is diffracted by slits and compared the predictions with experimental results obtained using the apparatus developed. Finally, the use of the apparatus in an optical spectroscopy experiment was demonstrated.

Measuring higher order optical aberrations of the human eye: techniques and applications

In the present paper we discuss the development of "wave-front", an instrument for determining the lower and higher optical aberrations of the human eye. We also discuss the advantages that such instrumentation and techniques might bring to the ophthalmology professional of the 21st century. By shining a small light spot on the retina of subjects and observing the light that is reflected back from within the eye, we are able to quantitatively determine the amount of lower order aberrations (astigmatism, myopia, hyperopia) and higher order aberrations (coma, spherical aberration, etc.). We have measured artificial eyes with calibrated ametropia ranging from +5 to -5 D, with and without 2 D astigmatism with axis at 45º and 90º. We used a device known as the Hartmann-Shack (HS) sensor, originally developed for measuring the optical aberrations of optical instruments and general refracting surfaces in astronomical telescopes. The HS sensor sends information to a computer software for decomposition of wave-front aberrations into a set of Zernike polynomials. These polynomials have special mathematical properties and are more suitable in this case than the traditional Seidel polynomials. We have demonstrated that this technique is more precise than conventional autorefraction, with a root mean square error (RMSE) of less than 0.1 µm for a 4-mm diameter pupil. In terms of dioptric power this represents an RMSE error of less than 0.04 D and 5º for the axis. This precision is sufficient for customized corneal ablations, among other applications.

Evapotranspiração real diária em sub-bacias do Paracatu, utilizando produtos do sensor Modis

A evapotranspiração define a perda total de água do sistema solo-planta para a atmosfera. Nas áreas agrícolas, particularmente onde se pratica algum tipo de irrigação, a determinação da evapotranspiração, por via de sensoriamento remoto, vem ganhando cada vez mais importância, pois possibilita identificar a eficiência com que a água tem sido utilizada. Nesse contexto, este trabalho tem o objetivo de determinar a evapotranspiração real diária (ETr diária), com a utilização de produtos do sensor MODIS, nas sub-bacias do Ribeirão Entre Ribeiros e Rio Preto, que ficam entre os Estados de Goiás e Minas Gerais. O SEBAL (Surface Energy Balance Algorithm for Land) foi utilizado para a obtenção da ETr diária em quatro dias diferentes, no período de julho a outubro de 2007. Os resultados encontrados foram compatíveis com os citados em outras literaturas e a comparação entre a evapotranspiração, obtida pelo SEBAL, e a evapotranspiração da cultura (ETc) demonstraram que esse algoritmo pode ser utilizado como boa opção para determinar, com a utilização de produtos do sensor MODIS, a evapotranspiração diária nas condições das sub-bacias do ribeirão Entre Ribeiros e rio Preto.

Causes of low vision and use of optical aids in the elderly

PURPOSE: To determine the causes of low vision in an elderly population attended by a university visual rehabilitation service and to check for the use of prescribed optical aids. METHOD: A cross-sectional study was carried out on patients aged 60 years or over attending for the first time a university low vision service in 2001. Ophthalmic reevaluation and interview were performed by means of a structured questionnaire in 2002. RESULTS: The sample comprised 50 subjects aged between 60 and 90 years. Severe low vision (<20/200) was present in 68.0% of patients. The main cause of low vision was age-related macular degeneration (44.0%). Regarding literacy, 16.0% were illiterate and 72.0% had completed fundamental schooling. Thirty-one patients (62.0%) had been prescribed optical aids; 54.8% of these patients stated that they use them. A majority (70.6%) held a favorable opinion of these aids. CONCLUSIONS: The main cause of low vision was age-related macular degeneration. Approximately half of those receiving prescriptions reported actually using the aids in their daily activities. Making best use of residual vision in the elderly population with visual impairment is a priority, given the social context, if the independence necessary for enhanced quality of life is to be achieved.

Mapeamento do uso e cobertura da terra a partir da segmentação e classificação de imagens-fração solo, sombra e vegetação derivadas do modelo linear de mistura aplicado a dados do sensor TM/Landsat5, na região do reservatório de Tucuruí - PA

Técnicas de sensoriamento remoto são fundamentais para o monitoramento das mudanças de uso da terra, principalmente em áreas extensas como a Amazônia. O mapeamento de uso da terra, geralmente é realizado por métodos de classificação manual ou digital pixel a pixel, os quais consomem muito tempo. Este estudo aborda a aplicação do modelo linear de mistura em uma imagem Landsat-TM segmentada para o mapeamento das classes de uso da terra na região do reservatório de Tucuruí-PA para os anos de 1996 e 2001.