Simulation of Water Vapor and Near Infrared Radiation to Predict Vapor Pressure Deficit in a Greenhouse Using CFD

Vapor pressure deficit (VPD) can be used as an indicator to schedule greenhouse irrigation. VPD can be estimated as a function of relative humidity (RH) and temperature (T). The objective of this work was to analyze spatial variation in VPD as an indicator of water stress influenced by concentration of water vapor and intensity of near infrared (NIR). The study was carried out in an empty three-span sawtooth greenhouse with natural ventilation under the local climate in Montecillo, Mexico; these findings established a base value to analyze greenhouse field conditions prior to the influence from a crop. The experimental phase consisted of recording data (3 February 2019–24 February 2019) on temperature, humidity, solar radiation, and wind speed, which were used for developing a model in computational fluid dynamics (CFD). Then, this model was used to estimate VPD, considering changes in mass fraction of water vapor and the intensity of NIR. Scenarios with 50, 70, and 90% external RH were evaluated. It was found that without a crop, temperature was not affected by the variation in the mass fraction of water vapor and the intensity of NIR in the simulated scenarios, each of which generated a thermal gradient within the range of 4 °C. When considering the scenario of 90% external RH, we found the best VPD range along the greenhouse (2–3 kPa) that would be a favorable field condition for crops. Differences between VPD with and without a crop can be used to estimate the water quantity needs for crop growth based on the climate variables examined in this study, where higher VPD values require more water for irrigation.

Hyperthermia by near infrared radiation induced immune cells activation and infiltration in breast tumor

Breast cancer is the most common cancer that causes death in women. Conventional therapies, including surgery and chemotherapy, have different therapeutic effects and are commonly associated with risks and side effects. Near infrared radiation is a technique with few side effects that is used for local hyperthermia, typically as an adjuvant to other cancer therapies. The understanding of the use of near NIR as a monotherapy, and its effects on the immune cells activation and infiltration, are limited. In this study, we investigate the effects of HT treatment using NIR on tumor regression and on the immune cells and molecules in breast tumors. Results from this study demonstrated that local HT by NIR at 43 °C reduced tumor progression and significantly increased the median survival of tumor-bearing mice. Immunohistochemical analysis revealed a significant reduction in cells proliferation in treated tumor, which was accompanied by an abundance of heat shock protein 70 (Hsp70). Increased numbers of activated dendritic cells were observed in the draining lymph nodes of the mice, along with infiltration of T cells, NK cells and B cells into the tumor. In contrast, tumor-infiltrated regulatory T cells were largely diminished from the tumor. In addition, higher IFN-γ and IL-2 secretion was observed in tumor of treated mice. Overall, results from this present study extends the understanding of using local HT by NIR to stimulate a favourable immune response against breast cancer.

High-Resolution Airborne Hyperspectral Imagery for Assessing Yield, Biomass, Grain N Concentration, and N Output in Spring Wheat

Remote sensing allows fast assessment of crop monitoring over large areas; however, questions regarding uncertainty in crop parameter prediction and application to nitrogen (N) fertilization remain open. The objective of this study was to optimize of remote sensing spectral information for its application to grain yield (GY), biomass, grain N concentration (GNC), and N output assessment, and decision making on spring wheat fertilization. Spring wheat (Triticum turgidum L.) field experiments testing two tillage treatments, two irrigation levels and six N treatments were conducted in Northwest Mexico over four consecutive years. Hyperspectral images were acquired through 27 airborne flight campaigns. At harvest, GY, biomass, GNC and N output were determined. Spectral exploratory analysis was used to identify the best wavelength combinations, the most suitable vegetation indices (VIs) and the best growth stages to assess the agronomic variables. The relationship between the spectral information and the agronomic measurements was evaluated by the coefficient of determination (R2) and the root mean square error (RMSE). The ability of the indices to guide fertilizer recommendation was assessed through an error analysis based on the N sufficiency index. GY was better assessed from the end of flowering to the early milk stage by VIs based on the combination of bands from near infrared radiation/visible and from near infrared radiation/red-edge regions (R2 > 0.6; RMSE < 700 kg ha−1). N output was efficiently assessed by a combination of bands from near infrared radiation/red-edge at booting (R2 > 0.7; RMSE < 9 kg N ha−1). The GNC was better estimated by VIs combining bands in near infrared radiation/red-edge at early milk, but with great variability among the years studied. Some VIs were promising for guiding fertilizer recommendation for increasing GNC, but there was not a single index providing reliable recommendations every year. This study highlights the potential of remote sensing imagery to assess GY and N output in spring wheat, but the identification of GNC responsive sites needs to be improved.