•Ground measurements of canopy structure and chlorophyll content were adopted.•The annual change of relationships between UAV VIs and Gs was explored.•Non-linear regression algorithms were adopted to ...relate UAV VIs to Gs.•Multiple linear regression approach performed well and was considered very robust.
To further assess the sensitivity of crop chlorophyll and structure based on UAV vegetation indices (VIs) to maize water stress, a study was carried out in a maize field located in Inner Mongolia, China, with various levels of deficit irrigation over the entire 2018 and 2019 growing seasons. Ground measurements of stomatal conductance (Gs), leaf area index and leaf chlorophyll were used as references for maize water status, canopy structure and chlorophyll content, respectively. Four structure VIs and two chlorophyll VIs, and three regression algorithms (multiple linear, random forest and artificial neural networks regression) were adopted. The results showed that canopy structure derived from VIs had a significant correlation (p < 0.001) with Gs with the highest r value of 0.64 (n = 270) in 2018 and 2019. The transformed chlorophyll absorption in reflectance index, chlorophyll VI, could only estimate severe maize water stress with an r value of −0.47 (p < 0.001, n = 270) for the drier 2019. The water stress sensitivity of chlorophyll and structure VIs maybe significantly influenced by different responses of canopy structure and chlorophyll concentration to water stress, and the different spectral resolution of UAV multispectral cameras. Compared to non-linear machine learning regression algorithms, the multiple linear regression was robust enough to relate UAV-based multispectral VIs to Gs with coefficients of determination of 0.48 and 0.45 (n = 270) for 2018 and 2019, respectively. Although stable significant correlations were found between UAV multispectral VIs and Gs, annual changes in these specific expressions were also observed. Overall, our results demonstrated the potential of using structure VIs derived from UAV multispectral images and multiple linear regression approach to estimate maize water status in field scale.
This study focused on developing a novel semi-empirical model for maize’s light extinction coefficient (kp) by integrating multiple remotely sensed vegetation features from several different remote ...sensing platforms. The proposed kp model’s performance was independently evaluated using Campbell’s (1986) original and simplified kp approaches. The Limited Irrigation Research Farm (LIRF) in Greeley, Colorado, and the Irrigation Innovation Consortium (IIC) in Fort Collins, Colorado, USA, served as experimental sites for developing and evaluating the novel maize kp model. Data collection involved multiple remote sensing platforms, including Landsat-8, Sentinel-2, Planet CubeSat, a Multispectral Handheld Radiometer, and an unmanned aerial system (UAS). Ground measurements of leaf area index (LAI) and fractional vegetation canopy cover (fc) were included. The study evaluated the novel kp model through a comprehensive analysis using statistical error metrics and Sobol global sensitivity indices to assess the performance and sensitivity of the models developed for predicting maize kp. Results indicated that the novel kp model showed strong statistical regression fitting results with a coefficient of determination or R2 of 0.95. Individual remote sensor analysis confirmed consistent regression calibration results among Landsat-8, Sentinel-2, Planet CubeSat, the MSR, and UAS. A comparison with Campbell’s (1986) kp models reveals a 44% improvement in accuracy. A global sensitivity analysis identified the role of the normalized difference vegetation index (NDVI) as a critical input variable to predict kp across sensors, emphasizing the model’s robustness and potential practical environmental applications. Further research should address sensor-specific variations and expand the kp model’s applicability to a diverse set of environmental and microclimate conditions.
The main environmental risk factor associated with the development of Crohn's disease (CD) is cigarette smoking. Although the mechanism is still unknown, some studies have shown that cigarette ...exposure affects the intestinal barrier of the small bowel. Among the factors that may be involved in this process are Paneth cells. These specialized epithelial cells are located into the small intestine, and they are able to secrete antimicrobial peptides, having an essential role in the control of the growth of microorganisms. Alterations in its function are associated with inflammatory processes, such as CD. To study how cigarette components impact ileum homeostasis and Paneth cells integrity, we used intragastric administration of cigarette smoke condensate (CSC) in mice. Our results showed that inflammation was triggered after mucosal exposure of CSC, which induced particular alterations in Paneth cells granules, antimicrobial peptide production, and a reduction of bactericidal capacity. In fact, exposure to CSC generated an imbalance in the fecal bacterial population and increased the susceptibility of mice to develop ileal damage in response to bacterial infection. Moreover, our results obtained in mice unable to produce interleukin 10 (IL-10
mice) suggest that CSC treatment can induce a symptomatic enterocolitis with a pathological inflammation in genetically susceptible individuals.
•Remote sensing techniques can quantify evapotranspiration of crops.•Three methods are compared to determine the basal crop coefficient.•Four thermal methods are used to determine the stress ...coefficient.•Thermal indices DANS and DACT are calibrated to rescale to the stress coefficient.•Stress detection methods that require less inputs are responsive to water stress.
Remotely sensed data such as spectral reflectance and infrared canopy temperature can be used to quantify crop canopy cover and/or crop water stress, often through the use of vegetation indices calculated from the near-infrared and red bands, and stress indices calculated from the thermal wavelengths. Standardized dual crop coefficient methods calculate both a non-stressed transpiration coefficient (Kcb) that is related to canopy cover, and a stress or transpiration reduction coefficient (Ks) that can be related to soil water deficit or other stress factors (e.g. disease). This study compares several remote sensing methods to determine Kcb and Ks and resulting evapotranspiration (ET) in a deficit irrigation experiment of corn (Zea mays L.) near Greeley, Colorado. Three methods were used to calculate Kcb (tabular, normalized difference vegetation index – NDVI, and canopy cover). Four canopy temperature based methods were used to calculate Ks: Crop Water Stress Index – CWSI, Canopy Temperature Ratio – Tcratio, Degrees Above Non-Stressed – DANS, Degrees Above Canopy Threshold – DACT. Crop ET predicted by these methods was compared to observation and water balance based ET measurements. Thermal indices DANS and DACT were calibrated to convert to Ks. Results showed that stress coefficient methods with less data requirements such as DANS and DACT are responsive to crop water stress as demonstrated by low RMSE of ET calculations, comparable to more data intensive methods such as CWSI. Results indicate which remote sensing methods are appropriate to use given certain data availability and irrigation level, in addition to providing an estimation of the associated error in ET.
Abstract
Atmospheric longwave downward radiation (
L
d
) is one of the significant components of net radiation (R
n
), and it drives several essential ecosystem processes.
L
d
can be estimated with ...simple empirical methods using atmospheric emissivity (ε
a
) submodels. In this study, eight global models for ε
a
were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the R
n
estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert’s equation coefficient should not be considered a constant value for use in ε
a
estimation, nor in time or location.
With an increasing demand of fresh water resources in arid/semi-arid parts of the world, researchers and practitioners are relying more than ever on remote sensing techniques for monitoring and ...evaluating crop water status and for estimating crop water use or crop actual evapotranspiration (ETa). In this present study, infrared thermometry was used in conjunction with a few weather parameters to develop non-water-stressed and non-transpiring baselines for irrigated maize in a semi-arid region of Colorado in the western USA. A remote sensing-based Crop Water Stress Index (CWSI) was then estimated for four hourly periods each day during 5 August to 2 September 2011 (29 days). The estimated CWSI was smallest during the 10:00–11:00 a.m. and largest during the 12:00–13:00 p.m. hours. Plotting volumetric water content of the topsoil vs. CWSI revealed that there is a high correlation between the two parameters during the analyzed period. CWSI values were also used to estimate maize actual transpiration (Ta). Ta estimates were more influenced by crop biomass rather than irrigation depths alone, mainly due to the fact that the effects of deficit irrigation were largely masked by the significant precipitation during the growing season. During the study period, applying an independent remotely sensed energy balance model showed that maize ETa was 159 mm, 30% larger than CWSI-Ta (122 mm) and 9% smaller than standard-condition maize ET (174 mm).
Bisphenols such as bisphenol A (BPA), S (BPS), C (BPC), F (BPF), AF (BPAF), tetrabromobisphenol, nonylphenol, and octylphenol are plasticizers used worldwide to manufacture daily-use articles. ...Exposure to these compounds is related to many pathologies of public health importance, such as infertility. Using a protector compound against the reproductive toxicological effects of bisphenols is of scientific interest. Melatonin and vitamins have been tested, but the results are not conclusive. To this end, this systematic review and meta-analysis compared the response of reproductive variables to melatonin and vitamin administration as protectors against damage caused by bisphenols. We search for controlled studies of male rats exposed to bisphenols to induce alterations in reproduction, with at least one intervention group receiving melatonin or vitamins (B, C, or E). Also, molecular docking simulations were performed between the androgen (AR) and estrogen receptors (ER), melatonin, and vitamins. About 1234 records were initially found; finally, 13 studies were qualified for review and meta-analysis. Melatonin plus bisphenol improves sperm concentration and viability of sperm and increases testosterone serum levels compared with control groups; however, groups receiving vitamins plus bisphenols had lower sperm concentration, total testis weight, and testosterone serum levels than the control. In the docking analysis, vitamin E had the highest negative MolDock score, representing the best binding affinity with AR and ER, compared with other vitamins and melatonin in the docking. Our findings suggest that vitamins could act as an endocrine disruptor, and melatonin is most effective in protecting against the toxic effects of bisphenols.
This study evaluated the performance of remote sensing (RS) algorithms for the estimation of actual maize evapotranspiration (ETa) using different spaceborne, airborne, and proximal multispectral ...data in a semi-arid climate region to identify the optimal platform that provides the best ETa estimates to improve irrigation water management and help make irrigated agriculture sustainable. The RS platforms used in the study included Landsat-8 (30 m pixel spatial resolution), Sentinel-2 (10 m), Planet CubeSat (3 m), multispectral radiometer or MSR (1 m), and a small uncrewed aerial system or sUAS (0.03 m). Two-source surface energy balance (TSEB) models, implementing the series and parallel surface resistance approaches, were used in this study to estimate hourly maize ETa. The data used in this study were obtained from two maize research sites in Greeley and Fort Collins, CO, USA, in 2020 and 2021. Each research site had different irrigation systems. The Greeley site had a subsurface drip system, while the Fort Collins site had surface irrigation (furrow). Maize ETa predictions were compared to observed maize ETa data from an eddy covariance system installed at each research site. Results indicated that the MSR5 proximal platform (1 m) provided optimal RS data for the TSEB algorithms. The MSR5 “point-based” nadir-looking surface reflectance data and surface radiometric temperature combination resulted in the smallest error when predicting hourly (mm/h) maize ETa. The mean bias and root mean square errors (MBE and RMSE, respectively), when predicting maize hourly ETa using the MSR5 sensor data, were equal to −0.02 (−3%) ± 0.07 (11%) mm/h MBE ± RMSE and −0.02 (−3%) ± 0.09 (14%) mm/h for the TSEB parallel and series approaches, respectively. The poorest performance, when predicting hourly TSEB maize ETa, was from Landsat-8 (30 m) multispectral data combined with its original thermal data, since the errors were −0.03 (−5%) ± 0.16 (29%) mm/h and −0.07 (−13%) ± 0.15 (29%) mm/h for the TSEB parallel and series approaches, respectively. These results indicate the need to develop methods to improve the quality of the RS data from sub-optimal platforms/sensors/scales/calibration to further advance sustainable irrigation water management.
Determining water stress levels of vegetated surfaces is crucial for irrigation scheduling. This paper aims to evaluate a new method for obtaining crop water stress index (CWSI) based on the ...estimation of sensible heat flux using an aerodynamic temperature gradient approach. Data were collected on a deficit irrigated maize field at a research farm located in Greeley, Colorado, USA, in 2017 and 2018. The irrigation treatment used subsurface drip. Weather data were measured on-site at 3.3 m above ground level. RED and NIR surface reflectance data were obtained on-site through multispectral radiometer measurements. Nadir surface temperature data were measured using infra-red thermometers at 1 m above canopy. CWSI estimated values were used to assess daily soil water stress index (SWSI), calculated from measurements of volumetric soil water content (VWC) and management allowed depletion (MAD) of 40%. Results show that SWSI is best represented through a non-linear rational CWSI function. Modeled CWSI estimates were compared to measured surface heat fluxes, resulting in a mean bias error of − 0.02 and a root mean square error of 0.09, while errors were 0.02 and 0.06 when compared with observed CWSI based on canopy transpiration measured with plant sap flow devices. Results seem to validate the proposed sensible heat flux-based CWSI model. The CWSI approach presented could be used to manage irrigation and conserve water resources for maize in semi-arid regions.
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•Mushrooms are a source of functional molecules for diverse system-levels.•Huitlacoche is a low explored Mexican edible mushroom with potential health benefits.•Ergothionine shows ...meaningful attributes, relevant in health and food fields.•Huitlacoche could propel economic, health, pharmaceutical and agricultural growth.
Macrofungi, mushrooms or higher fungi have been employed for medicinal and food purposes for decades, nevertheless, also represent, a novel and fruitful source of biologically relevant compounds, that could serve as health enhancers in diverse human illness conditions; specially, mushrooms, are considered a relevant source of the distictive molecule – ergothioneine, an excellent supply of important antioxidant, which boosts human health and shows potential as a preservative in food, promoting their utilization as functional foods, in this context, the present review overviews and complies current knowledge and trends of nutrients as well as bioactive mushroom components including the potential of Huitlacoche and ergothioneine, and the possible health benefits of these biological products and their activities have been explored which enhances the utilization of mushrooms.
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