White mold detection in common beans through leaf reflectance spectroscopy

ABSTRACT This study aimed to identify wavelengths based on leaf reflectance (400-1050 nm) to estimate white mold severity in common beans at different seasons. Two experiments were carried out, one during fall and another in winter. Partial Least Squares (PLS) regression was used to establish a set of wavelengths that better estimates the disease severity at a specific date. Therefore, observations were previously divided in two sub-groups. The first one (calibration) was used for model building and the second subgroup for model testing. Error measurements and correlation between measured and predicted values of disease severity index were employed to provide the best wavelengths in both seasons. The average indexes of each experiment were of 5.8% and 7.4%, which is considered low. Spectral bands ranged between blue and green, green and red, and red and infrared, being most sensitive for disease estimation. Beyond the transition ranges, other spectral regions also presented wavelengths with potential to determine the disease severity, such as red, green, and near infrared.

Reflectance indices as a diagnostic tool for weed control performed by multipurpose equipment in precision agriculture

Several tools of precision agriculture have been developed for specific uses. However, this specificity may hinder the implementation of precision agriculture due to an increasing in costs and operational complexity. The use of vegetation index sensors which are traditionally developed for crop fertilization, for site-specific weed management can provide multiple utilizations of these sensors and result in the optimization of precision agriculture. The aim of this study was to evaluate the relationship between reflectance indices of weeds obtained by the GreenSeekerTM sensor and conventional parameters used for weed interference quantification. Two experiments were conducted with soybean and corn by establishing a gradient of weed interference through the use of pre- and post-emergence herbicides. The weed quantification was evaluated by the normalized difference vegetation index (NDVI) and the ratio of red to near infrared (Red/NIR) obtained using the GreenSeekerTM sensor, the visual weed control, the weed dry matter, and digital photographs, which supplied information about the leaf area coverage proportions of weed and straw. The weed leaf coverage obtained using digital photography was highly associated with the NDVI (r = 0.78) and the Red/NIR (r = -0.74). The weed dry matter also positively correlated with the NDVI obtained in 1 m linear (r = 0.66). The results indicated that the GreenSeekerTM sensor originally used for crop fertilization could also be used to obtain reflectance indices in the area between rows of crops to support decision-making programs for weed control.

Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR data

This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI LiDAR estimates were derived in two ways (1) from the probability of discrete pulses reaching the ground without being intercepted (point method) and (2) from raw waveform canopy height profile processing adapted to small-footprint laser altimetry (waveform method) accounting for reflectance ratio between vegetation and ground. The best results, that matched hemispherical photography estimates, were achieved for the waveform method with a study area-adjusted reflectance ratio of 0.4 (RMSE of 0.15 and 0.03 at plot and site level, respectively). The point method generally overestimated, whereas the waveform method with an arbitrary reflectance ratio of 0.5 underestimated the fish-eye lens LAI estimates.

Modelling spectral reflectance of open cork oak woodland: a simulation analysis of the effects of vegetation structure and background

This study analyses the influence of vegetation structure (i.e. leaf area index and canopy cover) and seasonal background changes on moderate-resolution imaging spectrometer (MODIS)-simulated reflectance data in open woodland. Approximately monthly spectral reflectance and transmittance field measurements (May 2011 to October 2013) of cork oak tree leaves (Quercus suber) and of the herbaceous understorey were recorded in the region of Ribatejo, Portugal. The geometric-optical and radiative transfer (GORT) model was used to simulate MODIS response (red, near-infrared) and to calculate vegetation indices, investigating their response to changes in the structure of the overstorey vegetation and to seasonal changes in the understorey using scenarios corresponding to contrasting phenological status (dry season vs. wet season). The performance of normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) is discussed. Results showed that SAVI and EVI were very sensitive to the emergence of background vegetation in the wet season compared to NDVI and that shading effects lead to an opposing trend in the vegetation indices. The information provided by this research can be useful to improve our understanding of the temporal dynamic of vegetation, monitored by vegetation indices.

Validazione e applicazioni cliniche della metodica NIRA (Near Infrared Reflectance Analysis) per la valutazione del contenuto nutrizionale del latte materno in terapia intensiva neonatale

Phase 1: To validate Near-Infrared Reflectance Analysis (NIRA) as a fast, reliable and suitable method for routine evaluation of human milk’s nitrogen and fat content. Phase 2: To determine whether fat content, protein content and osmolality of HM before and after fortification may affect gastroesophageal reflux (GER) in symptomatic preterm infants. Patients and Methods: Phase 1: 124 samples of expressed human milk (55 from preterm mothers and 69 from term mothers) were used to validate NIRA against traditional methods (Gerber method for fat and Kjeldhal method for nitrogen). Phase 2: GER was evaluated in 17 symptomatic preterm newborns fed naïve and fortified HM by combined pH/intraluminal-impedance monitoring (pH-MII). HM fat and protein content was analysed by a Near-Infrared-Reflectance-Analysis (NIRA). HM osmolality was tested before and after fortification. GER indexes measured before and after fortification were compared, and were also related with HM fat and protein content and osmolality before and after fortification. Results: Phase 1: · A strong agreement was found between traditional methods’ and NIRA’s results (expressed as g/100 g of milk), both for fat and nitrogen content in term (mean fat content: NIRA=2.76; Gerber=2.76; mean nitrogen content: NIRA=1.88; Kjeldhal =1.92) and preterm (mean fat content: NIRA=3.56; Kjeldhal=3.52; mean nitrogen content: NIRA=1.91; Kjeldhal =1.89) mother’s milk. · Nitrogen content of the milk samples, measured by NIRA, ranged from 1.18 to 2.71 g/100 g of milk in preterm milk and from 1.48 to 2.47 in term milk; fat content ranged from 1.27 to 6.23 g/100 g of milk in preterm milk and from 1.01 to 6.01 g/100 g of milk in term milk. Phase 2: · An inverse correlation was found between naïve HM protein content and acid reflux index (RIpH: p=0.041, rho=-0.501). · After fortification, osmolality often exceeded the values recommended for infant feeds; furthermore, a statistically significant (p<.05) increase in non acid reflux indexes was observed. Conclusions: NIRA can be used as a fast, reliable and suitable tool for routine monitoring of macronutrient content of human milk. Protein content of naïve HM may influence acid GER in preterm infants. A standard fortification of HM may worsen non acid GER indexes and, due to the extreme variability in HM composition, may overcome both recommended protein intake and HM osmolality. Thus, an individualized fortification, based on the analysis of the composition of naïve HM, could optimize both nutrient intake and feeding tolerance.

Relationships between soil nitrate desorbed from anion-exchange membranes, canopy reflectance and nitrate leaching losses from cool-season lawn turf.

Nutrient leaching studies are expensive and require expertise in water collection and analyses. Less expensive or easier methods that estimate leaching losses would be desirable. The objective of this study was to determine if anion-exchange membranes (AEMs) and reflectance meters could predict nitrate (NO3-N) leaching losses from a cool-season lawn turf. A two-year field study used an established 90% Kentucky bluegrass (Poa pratensis L.)-10% creeping red fescue (Festuca rubra L.) turf that received 0 to 98 kg N ha-1 month-1, from May through November. Soil monolith lysimeters collected leachate that was analyzed for NO3-N concentration. Soil NO3-N was estimated with AEMs. Spectral reflectance measurements of the turf were obtained with chlorophyll and chroma meters. No significant (p > 0.05) increase in percolate flow-weighted NO3-N concentration (FWC) or mass loss occurred when AEM desorbed soil NO3-N was below 0.84 µg cm-2 d-1. A linear increase in FWC and mass loss (p < 0.0001) occurred, however, when AEM soil NO3-N was above this value. The maximum contaminant level (MCL) for drinking water (10 mg L-1 NO3-N) was reached with an AEM soil NO3-N value of 1.6 µg cm-2 d-1. Maximum meter readings were obtained when AEM soil NO3 N reached or exceeded 2.3 µg cm-2 d-1. As chlorophyll index and hue angle (greenness) increased, there was an increased probability of exceeding the NO3-N MCL. These data suggest that AEMs and reflectance meters can serve as tools to predict NO3-N leaching losses from cool-season lawn turf, and to provide objective guides for N fertilization.

Organic geochemistry, visual composition, atomic ratios, and reflectance at DSDP Site 87-582, 87-583 and 87-584

Geochemical analyses of organic matter were carried out on Quaternary sediments from Sites 582 and 583 (Nankai Trough) and on Pliocene to Miocene sediments from Site 584 (Japan Trench), DSDP Leg 87, to evaluate petroleum-generating potential and to characterize the organic matter. The vitrinite-huminite reflectances of indigenous materials for these sites are less than 0.3% indicating the immature nature of the sediments. The sediments, however, contain remarkable amounts of recycled organic materials. The Quaternary sediments from Sites 582 and 583 contain small amounts of amorphous organic matter (less than 0.75 wt.% organic carbon and 66-90% amorphous debris), which is composed of predominantly recycled, oxidized, and over-matured (or matured) Type III material. The amount of hydrocarbon yield indicates that those sediments have lean-source potential for commercial hydrocarbon generation. The Pliocene to Miocene sediments from Site 584 contain organic matter (0.3-1.09 wt.% organic carbon) of predominantly amorphous debris (68-96%) that originated in two sources, an indigenous Type II material and a recycled, over-matured material. Pyrolysis shows an upward increase in the section of hydrocarbon yield and the same trend is also observed in organic-carbon content. The amount of the yield indicates that the Miocene sediments have lean-to-fair source potential and the Pliocene sediments have fair-to-good source potential.

Use of the First Derivative of Spectral Reflectance to Detect Mold on Tomatoes

The first derivative of spectral reflectance of tomatoes was studied to see whether it can detect molds and sunscald damage on the fruit. The results indicate that a quality index based on the derivative values of reflectance at 590- and 710-nm wavelengths can be used to separate good tomates from those with black mold, gray mold, and sunscald.

Vitrinite reflectance and carbon chemistry of ODP Leg 122 samples (Table 1)

A summary of shipboard Rock-Eval measurements shows that organic matter in Upper Triassic siltstone from the Wombat Plateau is dominated by Type III kerogen and is thermally immature. Neocomian siltstone from the Exmouth Plateau similarly contain thermally immature Type III organic matter. Overlying Upper Cretaceous to Quaternary carbonates are poor in organic matter at both locations, yet significant amounts of methane-dominated gas are dissolved in the pore waters of the thick carbonate sequence present on the Exmouth Plateau. This dry gas is believed to have migrated from deeper and more mature strata containing Type III kerogen.

A catalog of data compilations on photochemical and photophysical processes in solution /

Item 247.

Influence of parameters of drying on laser induced diffuse reflectance of banana discs

Banana discs of 1 cm thickness were immersed into different antioxidant solutions to slow down potentially disturbing discoloration during drying. Samples were randomly split into 8 groups according to the 2^p experimental design. Two antioxidant solutions with 1.66% and 4.59% ascorbic acid, two levels of drying temperature with 50°C and 80°C, two levels of drying time with 6h and 8h were used or adjusted. Laser diodes of seven wavelengths (532, 635, 650, 780, 808, 850 and 1064 nm) were selected to illuminate the surface and light penetration pattern was evaluated on the basis of radial profiles. Profiles acquired at three wavelengths (532, 635 and 650 nm) were found to respond sensitively to adjusted parameters. As a result of drying, intensity decay was observed to move closer to incident point. Significant effect (p<0.01) of temperature, drying time and their interaction was found on extracted descriptive attributes of intensity profiles: full width at half maximum (FWHM), distance of inflection point (DIP) and slope of logarithmic decay (SLD). Beyond their presence, antioxidant concentration was neutral factor without significant contribution to the model. Results were in agreement with reference spectroscopic measurements, especially with NDVI index. Promising results suggest that evaluated method might be suitable for monitoring purposes during drying of fruits.

Sugarcane leaf area estimate obtained from the corrected normalized difference vegetation index (NDVI)

v. 46, n. 2, p. 140-148, apr./jun. 2016.