Evaluation of a hybrid remote sensing evapotranspiration model for variable rate irrigation management

Accurate generation of spatial irrigation prescriptions is essential for implementation and evaluation of variable rate irrigation (VRI) technology. A hybrid remote sensing evapotranspiration (ET) model was evaluated for use in developing irrigation prescriptions for a VRI center pivot. The model is a combination of a two-source energy balance model and a reflectance based crop coefficient water balance model. Spatial ET and soil water depletion were modeled for a 10 km2 area consisting of rainfed and irrigated maize fields in eastern Nebraska for 2013. Multispectral images from Landsat 8 Operational Land Imager and Thermal Infrared Sensor were used as model input. Modeled net radiation and soil heat fluxes compared well with measurements from eddy covariance systems located within three fields in the study area. Modeled sensible heat flux did not compare well. Latent heat flux compared well for the only mid-summer image, but poorly for the one spring and two fall images. The water balance ET compared well with the two-source energy balance ET for irrigated maize, but not for dryland maize. Image frequency is thought to be a contributing factor in the poor performance of the water balance. In 2015 the hybrid model will be used to generate irrigation prescription maps for a VRI system located in the study area based on modeled soil moisture depletion. Future research will focus on model parameterization and utilize aerial imagery and satellite imagery from other sensors for improved image frequency. Note: this is a revision of the original paper correcting erroneous data where one of the flux sites was mistakenly analyzed as soybeans, when it was actually maize. Mean biased error signs have also been corrected

Water Recommendations for Vegetables

Traditionally, we irrigate using overhead sprinklers and/or flood irrigation. However, these methods can be wasteful, and so a way to conserve and still have a healthy garden is to use drip irrigation. It can reduce water use by up to about 50%. This fact sheet reviews water recommendations for growing vegetables

Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management

Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (Kcbrf) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m-2. The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m-2. We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d-1 (RMSE = 1.49 mm d-1) for PM and MBE = 0.04 mm d-1 (RMSE = 1.18 mm d-1) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d-1 (RMSE = 1.37 mm d-1) for the Kcbrfalone to -0.45 mm d-1 (RMSE = 0.98 mm d-1) and -0.39 mm d-1 (RMSE = 0.95 mm d-1) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management

ASSOCIATIONS BETWEEN CLINICAL AND PERFORMANCE TESTS IN SOCCER ATHLETES

The purpose of this study was to determine the relationship between selected Functional Movement Screen (FMS™) scores, quadriceps and hamstrings strength, and vertical jump performance to see if there is consistency between clinical and performance testing. Records for twelve NCAA-I female soccer players were selected for this study. The isolated scores from the hurdle step and deep squat portions of the FMS™ test were extracted, left and right peak knee extension and flexion torques from isokinetic tests at 60, 180, and 300 °/sec, and vertical jump heights were recorded. Bivariate correlations and a multiple regression analysis were conducted to explore relationships among variables. The results from this study indicated that the FMS™ test was a poor predictor of vertical jump height, but peak extension and flexion torques were related to the vertical jump in a complex relationship

STING-dependent recognition of cyclic di-AMP mediates type I interferon responses during Chlamydia trachomatis infection.

UnlabelledSTING (stimulator of interferon [IFN] genes) initiates type I IFN responses in mammalian cells through the detection of microbial nucleic acids. The membrane-bound obligate intracellular bacterium Chlamydia trachomatis induces a STING-dependent type I IFN response in infected cells, yet the IFN-inducing ligand remains unknown. In this report, we provide evidence that Chlamydia synthesizes cyclic di-AMP (c-di-AMP), a nucleic acid metabolite not previously identified in Gram-negative bacteria, and that this metabolite is a prominent ligand for STING-mediated activation of IFN responses during infection. We used primary mouse lung fibroblasts and HEK293T cells to compare IFN-β responses to Chlamydia infection, c-di-AMP, and other type I IFN-inducing stimuli. Chlamydia infection and c-di-AMP treatment induced type I IFN responses in cells expressing STING but not in cells expressing STING variants that cannot sense cyclic dinucleotides but still respond to cytoplasmic DNA. The failure to induce a type I IFN response to Chlamydia and c-di-AMP correlated with the inability of STING to relocalize from the endoplasmic reticulum to cytoplasmic punctate signaling complexes required for IFN activation. We conclude that Chlamydia induces STING-mediated IFN responses through the detection of c-di-AMP in the host cell cytosol and propose that c-di-AMP is the ligand predominantly responsible for inducing such a response in Chlamydia-infected cells.ImportanceThis study shows that the Gram-negative obligate pathogen Chlamydia trachomatis, a major cause of pelvic inflammatory disease and infertility, synthesizes cyclic di-AMP (c-di-AMP), a nucleic acid metabolite that thus far has been described only in Gram-positive bacteria. We further provide evidence that the host cell employs an endoplasmic reticulum (ER)-localized cytoplasmic sensor, STING (stimulator of interferon [IFN] genes), to detect c-di-AMP synthesized by Chlamydia and induce a protective IFN response. This detection occurs even though Chlamydia is confined to a membrane-bound vacuole. This raises the possibility that the ER, an organelle that innervates the entire cytoplasm, is equipped with pattern recognition receptors that can directly survey membrane-bound pathogen-containing vacuoles for leaking microbe-specific metabolites to mount type I IFN responses required to control microbial infections

Evaluation of variable rate irrigation using a remote-sensing-based model

Improvements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRINP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as an input. Both 2015 and 2016 had above-average precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 mm, 6 mm, and –12 mm less in separate analyses than for the uniform treatment. Irrigation for the VRIRS was about 40 mm, 50 mm, and –98 mm greater in separate analyses than the uniform at Mead and about 18mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates

The Tumor Microenvironment of High Grade Serous Ovarian Cancer

The Special Issue on high grade serous ovarian cancer (HGSOC) and the contribution of the tumor micro-environment (TME) consisted of reviews contributed by leaders in the ovarian cancer (OC) field. [...]

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska under Full and Deficit Irrigation

Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model performance was promising, as it was executed unaided by measurements of soil water content throughout the season. VRI prescriptions did not correlate well with available water capacity (R2 \u3c 0.4); however, they correlated better with modeled ET in 2018 (R2 = 0. 69, VRI-Full; R2 = 0.55, VRI-Deficit). No significant differences were observed in total intended gross irrigation depth in 2017 (VRI-Full = 351mm, Uniform Full = 344). However, in 2018, VRI resulted in lower mean prescribed gross irrigation than the corresponding uniform treatments (VRI-Full = 265mm, Uniform Full = 282mm, VRI-Deficit = 234mm, and Uniform Deficit = 267mm). Notwithstanding the differences in prescribed irrigation (in 2018), VRI did not affect dry grain yield, with no statistically significant differences being found between any treatments in either year (F = 0.03, p = 0.87 in 2017; F = 0.00, p = 0.96 for VRI/Uniform and F = 0.01, p = 0.93 for Full/Deficit in 2018). Likewise, any reduction in irrigation application apparently did not result in detectable reductions in deep percolation potential or actual evapotranspiration. Additional research is needed to further vet the model as a deficit irrigation management tool. Suggested model improvements include a continuous function for water stress and an optimization routine in computing the basal crop coefficient

The Tumor Microenvironment of High Grade Serous Ovarian Cancer

The Special Issue on high grade serous ovarian cancer (HGSOC) and the contribution of the tumor microenviroment (TME) consists of reviews contributed by leaders in the OC field. As HGSOC metastases have a highly complex TME, there is an urgent need to better understand the TME in general, its distinct components in particular, and the role of the TME in the context of disease recurrence and development of chemoresistance. The Special Issue incorporates the current understanding of the different parts of thd TME components, including the cancer cells themselves, the cells surrounding the cancer cells or stromal cells, and the cells of the immune system, which are attracted to the site of metastases. In addition to these cells of the TME, the role of various cellular factors made by the cells of the TME are also the subject of the reviews. In addition, reviews in this Special Issue cover the complex relationships between the molecular mechanisms of HGSOC progression, including genomic, epigenomic and transcriptomic changes and changes in the immune cell landscape, as these may provide attractive new molecular targets for HGSOC therapy