Castor oil and PEG‐based shape memory polyurethane films for biomedical applications

A series of polyurethane film were prepared from poly(ethylene glycol) with different molecular weight (PEG 1500, 3000, and 8000) and castor oil by one‐shot bulk polymerization method. Hexamethylene diisocyanate and 1,4‐buthane diol were used as diisocyanate and chain extender, respectively. In order to characterize the samples, their density, swelling ratio, water contact angle, surface free energy, gel content, thermal, and viscoelastic properties were determined. The effect of the soft segment length (SSL) and hard segment content (HSC) of all polyurethane films on their shape memory behavior such as shape fixity (R_f) and shape recovery (R_r) rates were investigated by bending test. Direct contact and MTT tests were used for assessment of cell adhesion and proliferation. The relatively high R_f and R_r values were obtained for the samples programmed at high temperature difference. R_f increased with decreasing HSC. On the other hand, R_r tended to decrease with increasing SSL. After evaluating experimental data by a nonlinear equation, it was found that HSC is more effective parameter on shape memory property than SSL. The gel content, swelling ratio, and water contact angle of the samples were dependent on both SSL and HSC in their structures. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40590.     

SWIR-based spectral indices for assessing nitrogen content in potato fields

Nitrogen (N) is an essential element in plant growth and productivity, and N fertilizer is therefore of prime importance in cultivated crops. The amount and timing of N application has economic and environmental implications and is consequently considered to be an important issue in precision agriculture. Spectral indices derived from handheld, airborne and spaceborne spectrometers are used for assessing N content. The majority of these indices are based on indirect indicators, mostly chlorophyll content, which is proven to be physiologically linked to N content. The current research aimed to explore the performance of new N spectral indices dependent upon the shortwave infrared (SWIR) region (1200–2500 nm), and particularly the 1510 nm band because it is related directly to N content. Traditional nitrogen indices (NIs) and four proposed new SWIR-based indices were tested with canopy-level spectral data obtained during two growing seasons in potato experimental plots in the northwest Negev, Israel. Above-ground biomass samples were collected at the same location of the spectral sampling to provide in-situ N content data. The performance of all indices was evaluated by three methods: (1) correlations between the existing and proposed indices and N as well as correlations among the indices themselves; (2) the root mean square error prediction (RMSEP) of the N content; and (3) the indices relative sensitivity (S _r) to the N content. The results reveal a firm advantage for the proposed SWIR-based indices in their ability to predict, and in their sensitivity to, N content. The best index is one that combines information from the 1510 and 660 nm bands but no significant differences were found among the new SWIR-based indices.     

Cover Image,Volume 100, Issue 11

The cover image is based on the Research Article The Israeli Palestinian wheat landraces collection: restoration and characterization of lost genetic diversity by Sivan Frankin et al., https://doi.org/10.1002/jsfa.9822 .

     

Monitoring infiltration rates in semiarid soils using airborne hyperspectral technology

Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid and semi-arid regions. The physical crust that forms on the soil surface during rain events is one of the major causes of increased run-off and reduced water infiltration into the soil profile. Based on previous studies that showed significant correlation between crusted soil and soil reflectance properties, we performed a systematic study over Loess soil from Israel, in order to map the infiltration rate from a remote distance, using Hyperspectral (or Imaging Spectroscopy, IS) technology. First, we simulated rain events under laboratory conditions, using the selected soil and varying rain energy treatments. After measuring the reflectance properties of the crusted soils, we developed a spectral parameter for assessment of crust status. The parameter, Normalized Spectral Area (NSA), uses the area under a ratio spectrum across the VIS-NIR spectral region (calculated from the ratio of the crusted (treated) soil spectrum to the non-crusted soil spectrum). The correlation between the NSA and infiltration rate values provided a significant calibration equation. Based on these results, we conducted an airborne campaign, employing the AISA imaging scanner adjusted to 30-channel data in the VIS-NIR, and established control plots (crusted and non-crusted soil) on the ground, to examine the NSA parameter for mapping the infiltration properties of Loess soils. Reasonable agreement was obtained between the two datasets (laboratory and air), suggesting that infiltration rates can be estimated remotely. Further research is necessary to expand the analysis to other areas and conditions (e.g. diverse CaCO₃ and moisture content of soil). The paper shows that spectral reflectance information in the VIS-NIR region can be used to assess soil infiltration affected by the soil crust, in both laboratory and air domains. It is strongly suggested that future study in this regard use the full optical range (VIS-NIR-SWIR-TIR), as well as a spectral library of crusted soils collected in or within the rain simulator environment.     

LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands

Leaf Area Index (LAI) is an important variable that governs canopy processes and can be monitored by satellites. The current study aims at exploring the potential and limitations of using the red-edge spectral bands of the forthcoming superspectral satellites, namely—Vegetation and Environmental New micro Spacecraft (VENμS) and Sentinel-2, for assessing LAI in field crops. The research was conducted in experimental plots of wheat and potato in the northwestern Negev, Israel. Continuous spectral data were collected by a field spectrometer and LAI data were obtained by a ceptometer. The spectral data were resampled to the superspectral VENμS and Sentinel-2 resolutions. The data were divided into seven datasets (four seasons, two crops, and one including all data). The LAI prediction abilities by Partial Least Squares (PLS) models for continuous spectra and the resampled spectra were compared and evaluated. For wheat and potato of the continuous, VENμS, and Sentinel-2 data formations, the PLS correlation coefficients (r) values were 0.93, 0.93, and 0.92, respectively. In most cases, the red-edge region was found to be the most important spectral region for the three data formations, according to the Variable Importance in Projection (VIP) analysis. Additionally, Normalized Difference Vegetation Index (NDVI) and the Red-Edge Inflection Point (REIP) were computed for the three data formations in order to observe relation to as well as prediction accuracy in retrieving LAI values. The prediction abilities of the calculated indices by the data formations were compared, peaking for wheat, with r values of 0.91 for the REIP for the three data formations. Therefore, it is concluded that VENμS and Sentinel-2 can spectrally assess LAI as good as a hyperspectral sensor. The REIP was found to be a significantly better predictor than NDVI for wheat data and therefore can potentially be implemented for future LAI monitoring applications by superspectral sensors that contain four red-edge bands.     

Nutritional education for management of osteodystrophy: Impact on serum phosphorus,quality of life,and malnutrition

Introduction Osteodystrophy management includes dietary phosphorus restriction, which may limit protein intake, exacerbate malnutrition‐inflammation syndrome and mortality among hemodialysis patients. Methods A multicenter randomized controlled trial was conducted in Lebanon, to test the hypothesis that intensive nutrition education focused on phosphorus‐to‐protein balance will improve patient outcomes. Six hemodialysis units were randomly assigned to the trained hospital dietitian (THD) protocol (210 patients). Six others (184 patients) were divided equally according to the patients’ dialysis shifts and assigned to Dedicated Dietitian (DD) and Control protocols. Patients in the THD group received nutrition education from hospital dietitians who were trained by the study team on renal dietetics, but had limited time for hemodialysis patients. Patients in the DD group received individualized nutritional education on dietary phosphorus and protein management for 6 months (2‐hour/patient/month) from study renal dietitians. Patients in the control group continued receiving routine care from hospital dietitians who had limited time for these patients and were blinded to the study. Serum phosphorus (mmol/L), malnutrition‐inflammation score (MIS), health‐related quality of life (HRQOL) index and length of hospital stay (LOS) were assessed at T0 (baseline), T1 (postintervention) and T2 (post6 month follow up). Findings Only the DD protocol significantly improved serum phosphorus (T0:1.78 ± 0.5, T1:1.63 ± 0.46, T2:1.69 ± 0.53), 3 domains of the HRQOL and maintained MIS at T1, but this protective effect resolved at T2. The LOS significantly dropped for all groups. Discussion The presence of competent renal dietitians fully dedicated to hemodialysis units was superior over the other protocols in temporarily improving patient outcomes.