Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R2 (LL R2) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design. 相似文献
Environment, Development and Sustainability - The COVID-19 pandemic has caused a global emergence, and the absence of a proven vaccine or medicine has led to the implementation of measures to... 相似文献
Food loss and waste is a major issue affecting food security, environmental pollution, producer profitability, consumer prices, and climate change. About 1.3 billion tons of food products are yearly lost globally, with China producing approximately 20 million tons of soybean dregs annually. Here, we review food and agricultural byproducts with emphasis on the strategies to convert this waste into valuable materials. Byproducts can be used for animal and plant nutrition, biogas production, food, extraction of oils and bioactive substances, and production of vinegar, wine, edible coatings and organic fertilizers. For instance, bioactive compounds represent approximately 8–20% of apple pomace, 5–17% of orange peel, 10–25% of grape seeds, 3–15% of pomegranate peel, and 2–13% of date palm seeds. Similarly, the pharmaceutical industry uses approximately 6.5% of the total output of gelatin derived from fish bones and animal skin. Animals fed with pomegranate peel and olive pomace improved the concentration of deoxyribonucleic acid and protein, the litter size, the milk yield, and nest characteristics. Biogas production amounts to 57.1% using soybean residue, 53.7% using papaya peel, and 49.1% using sugarcane bagasse.
Objective: Though motor vehicle crashes (MVCs) were the main cause of head trauma from road traffic injuries (RTIs), motorcycle crashes (MCCs) are now a major cause of RTI-related head injury (HI) in many developing countries.
Methods: Using a prospective database of HIs from a neurosurgical practice in a sub-Saharan African developing country, a cross-sectional survey was conducted for the trauma demography and clinical epidemiology of this MCC-related HI.
Results: Motorcycle crashes accounted for 57% (473/833) of all RTI-related HIs in this registry. The victims, with a mean age of 33.1 years (SD = 18.3), consisted mainly of males (83.1%), those of low socioeconomic status (>90%), and those aged between 20 and 40 years old (56%). MCCs involved only riders in 114 cases (114/473, 32.1%), of which 69% were motorcycle–motorcycle crashes. The HI was moderate–severe in 50.8%; clinical symptomatology of significant HI included loss of consciousness (92%), anisocoria (35%), Abbreviated Injury Scale head (AIS–head) score > 3 (28%), and CT-Rotterdam score > 3 (30%). Extracranial systemic injury involved the limbs most frequently, with an Injury Severity Score (ISS) >25 in 49%. The fatality rate was 24%.
MCC-related HI among pedestrian victims involved more vulnerable age groups (the young and elderly) but have lower mean ISS compared to motorcycle passengers (mean ISS = 23.5 [11.6] vs. 27.4 [13.0]; 95% confidence interval [CI], 1.27–6.49; P = .004). In addition, compared to a contemporary cohort of MVC-related HIs in our registry, MCC victims were older (mean age 34.8 years [18.0] vs. 30.8 [18.4]; P = .002); had higher proportions of certain extracranial trauma like long bone fractures (71 vs. 29%; P = .02); and suffered fewer surgical brain lesions (25.5 vs. 17.2%; P = .004).
Conclusions: Motorcycle crashes are now a significant threat to the heads, limbs, and lives of vulnerable road users in developing countries. 相似文献
Environmental Science and Pollution Research - Resident physicians are the first-line health service providers, subjected to prolonged working hours, sleep deprivation and high job demands. Work... 相似文献
Conventional wastewater treatments are not efficient in removing parabens, which may thus end up in surface waters, posing a threat to aquatic biota and hu 相似文献
We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.相似文献
The growing industrial interest in adopting sustainability programmes has ushered in studies regarding sustainability indicators which have continually flourished in current literature. However, limited attention is given to the development of priority ranking, which is an important input for any adopting firm. This paper presents a hybrid multi-criteria approach in determining priority areas in sustainable manufacturing (SM). Using fuzzy analytic hierarchy process to address uncertainty in hierarchical decision-making, this paper determines SM priority strategies and eventually identifies even lower level strategies. The computed sustainable manufacturing index is presented at both the organizational and operational levels for a real case study of an industrial plastic manufacturing firm. This work provides a detailed and transparent hierarchical decision-making approach based on SM framework, the use of which could be valuable to practicing managers across industries in their pursuit of greater sustainability. 相似文献