scholarly journals SCALING UP SAGEBRUSH CHEMISTRY WITH NEAR-INFRARED SPECTROSCOPY AND UAS-ACQUIRED HYPERSPECTRAL IMAGERY

2021 ◽  
Vol XLIV-M-3-2021 ◽  
pp. 127-132
Author(s):  
P. J. Olsoy ◽  
S. N. Barrett ◽  
B. C. Robb ◽  
J. S. Forbey ◽  
T. T. Caughlin ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Crude Protein ◽  
Near Infrared ◽  
Small Sample Size ◽  
Small Sample ◽  
Sagebrush Steppe ◽  
Plant Chemistry ◽  
Spectral Patterns ◽  
Hyperspectral Sensor

Abstract. Sagebrush ecosystems (Artemisia spp.) face many threats including large wildfires and conversion to invasive annuals, and thus are the focus of intense restoration efforts across the western United States. Specific attention has been given to restoration of sagebrush systems for threatened herbivores, such as Greater Sage-Grouse (Centrocercus urophasianus) and pygmy rabbits (Brachylagus idahoensis), reliant on sagebrush as forage. Despite this, plant chemistry (e.g., crude protein, monoterpenes and phenolics) is rarely considered during reseeding efforts or when deciding which areas to conserve. Near-infrared spectroscopy (NIRS) has proven effective in predicting plant chemistry under laboratory conditions in a variety of ecosystems, including the sagebrush steppe. Our objectives were to demonstrate the scalability of these models from the laboratory to the field, and in the air with a hyperspectral sensor on an unoccupied aerial system (UAS). Sagebrush leaf samples were collected at a study site in eastern Idaho, USA. Plants were scanned with an ASD FieldSpec 4 spectroradiometer in the field and laboratory, and a subset of the same plants were imaged with a SteadiDrone Hexacopter UAS equipped with a Rikola hyperspectral sensor (HSI). All three sensors generated spectral patterns that were distinct among species and morphotypes of sagebrush at specific wavelengths. Lab-based NIRS was accurate for predicting crude protein and total monoterpenes (R2 = 0.7–0.8), but the same NIRS sensor in the field was unable to predict either crude protein or total monoterpenes (R2 < 0.1). The hyperspectral sensor on the UAS was unable to predict most chemicals (R2 < 0.2), likely due to a combination of too few bands in the Rikola HSI camera (16 bands), the range of wavelengths (500–900 nm), and small sample size of overlapping plants (n = 28–60). These results show both the potential for scaling NIRS from the lab to the field and the challenges in predicting complex plant chemistry with hyperspectral UAS. We conclude with recommendations for next steps in applying UAS to sagebrush ecosystems with a variety of new sensors.

Prediction of crude protein and neutral detergent fibre concentration in residues of in situ ruminal degradation of pasture samples by near-infrared spectroscopy (NIRS)

2016 ◽  
Vol 56 (9) ◽  
pp. 1504 ◽  
Author(s):  
J. P. Keim ◽  
H. Charles ◽  
D. Alomar
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Crude Protein ◽  
Near Infrared ◽  
External Validation ◽  
Neutral Detergent Fibre ◽  
Insufficient Amount ◽  
Ruminal Degradation ◽  
Animal Feedstuffs

An important constraint of in situ degradability studies is the need to analyse a high number of samples and often with insufficient amount of residue, especially after the longer incubations of high-quality forages, that impede the study of more than one nutritional component. Near-infrared spectroscopy (NIRS) has been established as a reliable method for predicting composition of many entities, including forages and other animal feedstuffs. The objective of this work was to evaluate the potential of NIRS for predicting the crude protein (CP) and neutral detergent fibre (NDF) concentration in rumen incubation residues of permanent and sown temperate pastures in a vegetative stage. In situ residues (n = 236) from four swards were scanned for their visible-NIR spectra and analysed for CP and NDF. Selected equations developed by partial least-squares multivariate regression presented high coefficients of determination (CP = 0.99, NDF = 0.95) and low standard errors (CP = 4.17 g/kg, NDF = 7.91 g/kg) in cross-validation. These errors compare favourably to the average concentrations of CP and NDF (146.5 and 711.2 g/kg, respectively) and represent a low fraction of their standard deviation (CP = 38.2 g/kg, NDF = 34.4 g/kg). An external validation was not as successful, with R2 of 0.83 and 0.82 and a standard error of prediction of 14.8 and 15.2 g/kg, for CP and NDF, respectively. It is concluded that NIRS has the potential to predict CP and NDF of in situ incubation residues of leafy pastures typical of humid temperate zones, but more robust calibrations should be developed.

Abstract 46: Initial Experience with Bedside Monitoring of Stroke and Cerebral Perfusion using Time Domain Near-infrared Spectroscopy (TD-NIRS): Feasibility and Future Directions

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Eric S Rosenthal ◽  
Juliette Selb ◽  
Lee H Schwamm ◽  
Nicusor Iftimia
Keyword(s):  
Ischemic Stroke ◽  
Infrared Spectroscopy ◽  
Subarachnoid Hemorrhage ◽  
Near Infrared Spectroscopy ◽  
Time Domain ◽  
Normal Tissue ◽  
Near Infrared ◽  
Small Sample ◽  
Pulsed Light ◽  
Spatial Coverage

Background: Near-infrared Spectroscopy (NIRS) may provide continuous, multiregional parenchymal bedside perfusion monitoring without the risks of patient transport, contrast, or radiation. Time-domain NIRS (TD-NIRS) uses pulsed light attenuation at multiple wavelengths (600-950 nm) to discretely quantify oxyhemoglobin and deoxyhemoglobin and determine total hemoglobin, oxygen saturation (OS) and cerebral blood volume (BV) in the region between each light source and detector. This study aimed to assess the feasibility of employing a novel TD-NIRS technology to assess absolute levels of cerebral BV and OS with broad spatial coverage in order to detect regions of ischemia. Methods: Ischemic stroke (IS) and subarachnoid hemorrhage (SAH) patients underwent TD-NIRS measurements. IS patients were fitted with a rectangular probe over the region of ischemia (2 rows of 4 sources between 3 rows of 5 detectors), using CT as a guide (external acoustic meatus as reference). SAH patients were fitted with a linear “anterior crown” probe with light sources and detectors arranged alternating in a single row (7 sources, 6 detectors). Clearance above the frontal sinus was guided by CT imaging (nasion as reference). 1.8 cm separated all source-detector pairs. Time-correlated single photon-counting photomultiplier tubes detected photons to measure absorption of pulsed light emitted at 3 wavelengths (690, 805, and 835 nm). Maximal OS (OSmax) and BV (BVmax) were calculated for the entire region measured by the probe to enable multiple comparisons. Results: In IS patients, ischemic regions (n=4) had an OSmax of 65.8 SD 13.1; contralateral normal tissue had an OSmax of 85.3 SD 27.1 (paired t-test; p 0.14). Ischemic regions had a BVmax of 76.25 SD 24.17 compared with 104.0 SD 42.5 in contralateral normal tissue (p 0.18). Regional inspection showed good visual correlation with infarcts ( Figure ). Of SAH patients with serial measures (n=2), one developed heparin-induced thrombocytopenia and bilateral infarcts, coincident with decreased BVmax on the right (72, day 1; 48, day 12) and left (153, day 1; 56, day 12); OS did not change. Conclusion: We were able to calculate multiregional BV and OS for patients with cerebral ischemia. Despite small sample size, we demonstrated a trend between contralateral (ischemic stroke) and historical (subarachnoid hemorrhage) controls. Leakage of light and absorption by hair produced artifacts that will require improvement in future applications. This system requires validation and further ergonomic refinement but has potential to enable continuous multiregional parenchymal monitoring.

Corrigendum to: Optimisation of dry matter and nutrients in feed rations through use of a near-infrared spectroscopy system mounted on a self-propelled feed mixer

2021 ◽  
Vol 61 (5) ◽  
pp. 540
Author(s):  
Ehab Mostafa ◽  
Philipp Twickler ◽  
Alexander Schmithausen ◽  
Christian Maack ◽  
Abdelkader Ghaly ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Nutritional Composition ◽  
Preliminary Evaluation ◽  
Maize Silage ◽  
Nutrient Contents ◽  
Physical Form

Context Knowledge of the nutrient requirements of dairy cows, and the nutritional composition and physical form of the feed resources used to prepare the total mixed ration (TMR) of basic and concentrated feeds, is essential to achieving high milk yields, health and welfare in modern commercial herds. Grass and maize silage components can vary widely in composition depending on harvesting intervals and weather; thus, the distribution of dry matter (DM) and nutrients in silos may vary greatly, resulting in serious errors during sampling and analysis. In addition, the flow of information from the stored silage stops once the forages are stored in the silo. Aims The objective of this study was to develop a practical approach for measuring variations in DM and silage quality parameters (crude protein, fibre, ash and fat) during the feed-extraction process from a bunker silo by a self-propelled feed mixer, which would ultimately help farmers to optimise the TMR. Methods Near-infrared spectroscopy (NIRS) technology was used to estimate fodder DM and nutrient contents in the material flow. Wet chemical analyses were used for preliminary evaluation of grass and maize silage samples. A portable NIRS was developed to record the spectra of various silage samples. Key results The spans of calibration of sample DM content were 21.3–59.2% for grass and 26–46.7% for maize. Crude protein content had span values of 11.4–18.3% for the grass silage and 5.4–10.8% for the maize silage models. Conclusions NIRS technology was used successfully to estimate the DM and nutrient contents of the fodder. The location for the functional unit on the self-propelled feed mixer may need to be modified for series production because it is not fully accessible. Implications NIRS is a suitable method for measuring DM and nutrient contents continuously during feed extraction from the bunker silo and can be used to help farmers to optimise the TMR.

scholarly journals Rapid non-invasive assessment of quality parameters in ground soybean using near-infrared spectroscopy

2018 ◽  
Vol 53 (1) ◽  
pp. 97-104 ◽  
Author(s):  
Larissa Rocha dos Santos ◽  
Marcela de Souza Zangirolami ◽  
Núbia Oliveira Silva ◽  
Patrícia Valderrama ◽  
Paulo Henrique Março
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Crude Protein ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Quality Parameters ◽  
Total Lipids ◽  
Non Invasive ◽  
Accuracy And Precision ◽  
Alternative Methodology

Abstract: The objective of this work was to evaluate multivariate calibration models to predict total lipids, crude protein, and moisture content in grinded soybean grains using near-infrared spectroscopy and partial least squares (PLS). Three hundred samples of grinded soybean, evaluated in duplicate, were used for reference and spectral measurements. The PLS models for total lipids, crude protein, and moisture were validated by figures of merit for accuracy and precision, respectively, of 0.75 and 0.67 for total lipids, 0.51 and 0.46 for crude protein, and 0.97 and 0.99 for moisture. The PLS models developed for total lipids, crude protein, and moisture can be used as an alternative methodology for the determination of physicochemical parameters, and, therefore, they can be applied in quality control in soybean processing industries.

scholarly journals The Estimation of Crude Protein and Dry Matter Degradability of Maize and Grass Silages by near Infrared Spectroscopy

1998 ◽  
Vol 6 (1) ◽  
pp. 145-151 ◽  
Author(s):  
Begoña De la Roza ◽  
Adela Martínez ◽  
Begoña Santos ◽  
Javier González ◽  
Guillermo Gómez
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
General Procedure ◽  
Good Method ◽  
Least Squares Regression ◽  
Ruminal Degradability ◽  
High Consistency

A total of 130 silages samples (53 of maize silages and 77 of grass silages), which were ensiled with or without silage additives, with different soil contamination levels, with different weed percentages and with or without wilting, were used to evaluate the dry matter (DM) and crude protein (CP) ruminal degradability. The ruminal degradability of the samples was calculated from the corresponding in situ degradation parameters and from the measured passage rates of the silages fed to each experimental animal. The DM and CP degradation parameters were obtained using the logistic model of Van Milgen and Baumont. The fitting of the models to the kinetics of degradation and particle passage was carried out by non-linear regression. The value of the effective degradability, considering in the rumen simultaneously an outflow compartment and a mixing–reduction compartment, were calculated in both cases from an adaptation of the general procedure proposed by Ørskov and McDonald. A NIRSystems 6500 spectrometer was used for the prediction of the DM and the CP degradation characteristics of the samples. Calibration equations were obtained by modified partial least squares regression, using reflectance spectra transformed into the second derivative. The results showed that near infrared spectroscopy is a good method for predicting the DM and CP degradation characteristics. The calibrations for effective degradability of maize and grass silages indicated a high consistency.

Measurement of gut oxygenation in the neonatal population using near-infrared spectroscopy: a clinical tool?

2019 ◽  
Vol 105 (1) ◽  
pp. 76-86 ◽  
Author(s):  
Emilie Seager ◽  
Catherine Longley ◽  
Narendra Aladangady ◽  
Jayanta Banerjee
Keyword(s):  
Infrared Spectroscopy ◽  
Clinical Practice ◽  
Near Infrared Spectroscopy ◽  
Observational Studies ◽  
Near Infrared ◽  
Newborn Infants ◽  
Review Literature ◽  
Small Sample ◽  
Clinical Tool ◽  
Neonatal Population

ContextNear-infrared spectroscopy (NIRS) is a non-invasive bedside monitor of tissue oxygenation that may be a useful clinical tool in monitoring of gut oxygenation in newborn infants.ObjectiveTo systematically review literature to determine whether NIRS is a reliable tool to monitor gut oxygenation on neonatal units.Data sourcesPubMed and Embase databases were searched using the terms ‘neonate’, ‘preterm infants’, ‘NIRS’ and ‘gut oxygenation’ (2001–2018).Study selectionStudies were included if they met inclusion criteria (clinical trial, observational studies, neonatal population, articles in English and reviewing regional gut oxygen saturations) and exclusion criteria (not evaluating abdominal NIRS or regional oxygen saturations).Data extractionTwo authors independently searched PubMed and Embase using the predefined terms, appraised study quality and extracted from 30 studies the study design and outcome data.LimitationsPotential for publication bias, majority of studies were prospective cohort studies and small sample sizes.ResultsThirty studies were reviewed assessing the validity of abdominal NIRS and potential application in neonates. Studies reviewed assessed abdominal NIRS in different settings including normal neonates, bolus and continuous feeding, during feed intolerance, necrotising enterocolitis and transfusion with packed red cells. Several observational studies demonstrated how NIRS could be used in clinical practice.ConclusionsNIRS may prove to be a useful bedside tool on the neonatal unit, working alongside current clinical tools in the monitoring of newborn infants (preterm and term) and inform clinical management. We recommend further studies including randomised controlled trials looking at specific measurements and cut-offs for abdominal NIRS for use in further clinical practice.

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