Academic literature on the topic 'NIR predictions'

Long-term planning for many sectors of society—including infrastructure, human health, agriculture, food security, water supply, insurance, conflict, and migration—requires an assessment of the range of possible futures which the planet might experience. Unlike short-term forecasts for which validation data exists for comparing forecast to observation, long-term forecasts have almost no validation data. As a result, researchers must rely on supporting evidence to make their projections. A review of methods for quantifying the uncertainty of climate predictions is given. The primary tool for quantifying these uncertainties are climate models, which attempt to model all the relevant processes that are important in climate change. However, neither the construction nor calibration of climate models is perfect, and therefore the uncertainties due to model errors must also be taken into account in the uncertainty quantification.Typically, prediction uncertainty is quantified by generating ensembles of solutions from climate models to span possible futures. For instance, initial condition uncertainty is quantified by generating an ensemble of initial states that are consistent with available observations and then integrating the climate model starting from each initial condition. A climate model is itself subject to uncertain choices in modeling certain physical processes. Some of these choices can be sampled using so-called perturbed physics ensembles, whereby uncertain parameters or structural switches are perturbed within a single climate model framework. For a variety of reasons, there is a strong reliance on so-called ensembles of opportunity, which are multi-model ensembles (MMEs) formed by collecting predictions from different climate modeling centers, each using a potentially different framework to represent relevant processes for climate change. The most extensive collection of these MMEs is associated with the Coupled Model Intercomparison Project (CMIP). However, the component models have biases, simplifications, and interdependencies that must be taken into account when making formal risk assessments. Techniques and concepts for integrating model projections in MMEs are reviewed, including differing paradigms of ensembles and how they relate to observations and reality. Aspects of these conceptual issues then inform the more practical matters of how to combine and weight model projections to best represent the uncertainties associated with projected climate change.

Thucydides and Tacitus are both uncomfortable authors whose unsparing commitment to revealing the truth results in grim depictions of the amoral deployment of political power—power for the sake of power—in idiosyncratic and difficult idioms. However, Tacitus never announces a program of Thucydides-imitation, whether pertaining to methodology or theme. Nor do ancient commentators link Tacitus to his Greek predecessor. Nevertheless, the two are much alike in important aspects of their historiographical achievements. The chapter explores a pair of passages in which the two historians treat one of history’s “repeating events”—defection from an imperial power. In examining the narratives of the Mytilenean and Batavian revolts (Thuc. 3.2–6, 8–18, 23–33, 35–50; Tac. H. 4.12–37, 54–79, 5.14–26), it gives due attention to “each new permutation of circumstances,” the important proviso that Thucydides attaches to his prediction about recurrence (3.82.2).

This examination of the history of the 20th century and the place of war in its unfolding presents a radical, unorthodox interpretation of both. With provision for seeing 1945 as the proper starting point for the 20th century and 1968 as the year that marked the end of the Age of Reason, this provocative study portrays the First World War as the first war of the 20th century and the Second World War as the last war of the 19th. It also provides a counterview of the Second World War as merely one part of a series of conflicts that lasted between 1931 and 1975 and the Cold War as the time when real hatreds were suspended. Moving through various insurgency campaigns, Willmott subjects the Gulf campaign of 1991 to skeptical analysis that is certain to be contentious. Challenging the view that the 20th century will be viewed by future historians as ranging from approximately 1914 to 1992, Willmott offers this volume as a counter to modern historiography which, he contends, is obsessed with micro-analysis and has lost vital context and perspective. Arguing that war is not the preserve of the intellect, and that it is neither intrinsically rational nor scientific, Willmott depicts war as a manmade phenomenon, complete with all the elements of human failure, misjudgment, and incompetence. He concludes with a consideration of modern doctrine and predictions for the future of war.

Metabolic acidosis (MA) commonly complicates critical illness, usually manifesting as a fall in arterial pH (<7.4) accompanied by a concomitant fall in serum bicarbonate concentration. Acidosis caused by unmeasured anions (UMA), can be distinguished from Hyperchloraemic acidosis by demonstrating a widening of the anion gap (AG). AG should be corrected for albumin and lactate. The base deficit (BD) calculates degree of metabolic acidosis and represents the amount of strong cation required to restore the pH to 7.4. Neither the AG nor the BD specify the cause of acidosis, and are unhelpful in the setting of mixed disorders. The base deficit gap (BDG) is used to calculate the effect of free water, sodium, chloride and albumin on the BD. It is the difference between BDcalc and BDmeasured (on a blood gas) and represents UMA. The strong ion gap more robustly calculates the amount of UMA than AG or BDG, and may be more accurate at predicting outcomes in the emergency room. Lactic acidosis is due to hypovolaemia until otherwise proven. In the majority of cases aggressive fluid resuscitation is warranted. In the presence of normal tissue blood flow regional hypoperfusion, poisoning or exogenous catecholamines should be considered. Ketoacidosis is due to intracellular glucose deficiency, caused by hypoinsulinaemia or starvation. The former is treated with isotonic crystalloid and insulin. Renal acidosis is treated with renal replacement therapy or recovery of renal function.

AbstractRecently, it has been proposed to switch molecular markers to near-infrared (NIR) spectra for inferring relationships between individuals and further performing phenomic selection (PS), analogous to genomic selection (GS). The PS concept is similar to genomic-like omics-based (GLOB) selection, in which molecular markers are replaced by endophenotypes, such as metabolites or transcript levels, except that the phenomic information obtained for instance by near-infrared spectroscopy (NIRS) has usually a much lower cost than other omics. Though NIRS has been routinely used in breeding for several decades, especially to deal with end-product quality traits, its use to predict other traits of interest and further make selections is new. Since the seminal paper on PS, several publications have advocated the use of spectral acquisition (including NIRS and hyperspectral imaging) in plant breeding towards PS, potentially providing a scope of what is possible. In the present chapter, we first come back to the concept of PS as originally proposed and provide a classification of selected papers related to the use of phenomics in breeding. We further provide a review of the selected literature concerning the type of technology used, the preprocessing of the spectra, and the statistical modeling to make predictions. We discuss the factors that likely affect the efficiency of PS and compare it to GS in terms of predictive ability. Finally, we propose several prospects for future work and application of PS in the context of plant breeding.

AbstractDifferent algorithms combined with Near-infrared spectroscopy were investigated for the detection and classification of crayfish quality. In this study, the crawfish quality was predicted by partial least square-support vector machine, principal component analysis-support vector machine, BP neural network and support vector machine after pre-processing the NIR spectral data of crawfish. The result shows that the accuracy of near-infrared spectroscopy technology combined with SVM to classify crayfish quality can reach 100%, and the prediction can guide the sampling of crayfish food safety in practice, thus improving food safety and quality.

AbstractNear-infrared spectroscopy (NIRS) is a non-invasive technique that can measure tissue oxygen saturation in organs such as the brain, kidney, and intestine. By monitoring changes in the attenuation of near-infrared light passing through the brain, NIRS can provide cerebral regional oxygen saturation measurements (CrSO2). NIRS has been used in neonatal intensive care units (NICUs) for various indications, including monitoring extremely premature infants and neonates with encephalopathy, congenital heart disease (CHD), anemia, respiratory support, and CNS injuries. Factors such as device type, sensor position, head position, and care procedures can affect NIRS measurements. NIRS has demonstrated potential in reducing cerebral hypoxia and predicting outcomes in neonatal encephalopathy and CHD. It is also being used in anesthesia and surgery settings. Proper training and monitoring are necessary to minimize complications associated with NIRS monitoring. NIRS provides valuable insights into cerebral perfusion and oxygenation, aiding in personalized care and neuroprotection in newborns.

Many small and medium enterprises (SME) often fail to fully utilize the data they collect due to a lack of technical expertise. The ecoKI platform, a low-code solution that simplifies machine learning application for SMEs, showed a promising answer to the challenge. This study explores the application of ecoKI platform to design process monitoring tools for waste sorting plants. NIR separator data were processed through ecoKI�s building blocks to train two neural network architectures�MLP and LSTM�for predicting NIR separation efficiency. The results showed that the models accurately predicted NIR output and effectively identified regions where NIR separation performance declined, demonstrating the potential of data-driven approaches for real-time performance monitoring. This work highlights how SMEs can leverage existing data for operational efficiency and decision-making, offering an accessible solution for industries with limited machine learning expertise. The approach is adaptable to various industrial contexts, paving the way for future advancements in automated, data-driven optimization of equipment performance.

Abstract This paper introduces a novel methodology for predicting the lifetime of nonmetallic materials exposed to downhole environments, including high and low pH, H2S, H2, CO2, and brines. The methodology was developed based on fundamental material principles, including viscoelasticity, hyperelasticity, and chemical/physical degradation from laboratory aging tests, field data, and finite-element analyses. This paper describes four case studies that show this methodology's effectiveness in defining the operational limits of polymeric materials. They cover 1) a fluoroelastomer O-ring from an oilfield tool; 2) Nitrile rubber (NBR) and Hydrogenated nitrile butadiene rubber (HNBR) sealing elements degraded by H2S from a well testing job; 3) an HNBR permanent element production packer; and 4) the CO2/H2 compatibility and rapid gas decompression (RGD) of typical elastomers for carbon capture and sequestration (CCS), and H2 well storage. The proposed methodology enables a more comprehensive prediction of the sealing performance of nonmetallic components under downhole operating conditions regardless of shape or size. It can be extended to develop operational limits of nonmetallic parts in the energy industry.

There is an expressed need for non-destructive userfriendly tools that can help customers and various stakeholders of the food market to identify and qualify samples rapidly and accurately. The identification of high quality meat cuts and the determination of aging are important challenges where handheld near infrared spectroscopy can provide perfect solutions. The objective of this study was to develop multivariate models for differentiation of beef cuts and prediction of the aging time based on the NIR spectra acquired with a handheld Tellspec Enterprise Food Sensor. Sirloin and tenderloin samples were stored at 4°C in plastic bags for 10-day period during two experiments, and spectra were recorded daily. The investigated sirloin and tenderloin samples were separated in principal component analysis, and it was possible to use the principal components in a supervised classification (linear discriminant analysis) to build model on meat authentication. 85.37% of the sirloin and tenderloin samples were classified correctly in independent validation tests. Multivariate calibration on aging was developed for the separate meat types. After omitting the first and last days of the experiments, accurate calibration models were built on the aging of beef samples. Accordingly, 1.1 or 1.5 days of precision was achieved during independent predictions for aging time of sirloin or tenderloin, respectively. Our results proved that the Tellspec Enterprise Food Sensor provides the possibility for rapid and non-destructive determination of meat type and stage of aging.

Abstract The cetane number is an important fuel property to consider for compression ignition engines as it is a measure of a fuel’s ignition delay. Derived cetane number (DCN) already varies significantly within jet fuels. With the expected increasing prevalence of alternative jet fuels, additional variability is expected. DCN is usually assigned to fuels using ASTM methods that use large equipment like the Ignition Quality Tester (IQT), which consumes a lot of fuel and is cumbersome to operate. Over the last decade, there have been advances in the development of chemometric models, which use machine learning to correlate infrared spectra of fuels to fuel properties like DCN, density, and C/H ratio, amongst many others. These techniques have certain advantages over the ASTM methods, and previous studies performed on samples of diesel fuels have shown high accuracies in DCN prediction. However, this accuracy is generally a result of high resolution, making the equipment expensive, relatively large for handheld sensors, and power-hungry. On the other hand, nondispersive infrared (NDIR) sensors, despite having a low resolution, are attractive because they can be compact, inexpensive, and power efficient. These characteristics are important for handheld or onboard fuel sensors. However, one would anticipate a trade-off between these advantages and accuracy. This study investigates this trade-off and the feasibility of low-resolution NDIR sensors to discern fuel properties such as DCN by using Machine Learning models trained on real FTIR data, and DCNs obtained from IQT. DCN predictions were made for blends of ATJ/F-24, CN fuels, and neat Jet A1, A2, and JP 5, with an error limit of 10%. It was found that there seems to be sufficient variability in the near infrared range to discern DCN with a feasible number of channels, but the channels have to be narrow (e.g. FWHMs as narrow as 60nm). For the data set in the study, the performance of linear models was better than the non-linear model. Finally, NIR region beyond 1050 nm was found to be more important in DCN prediction, primarily the regions consisting of the first and second C-H overtones and the C-H combination band.

In this paper, the process parameter effects on the thermal characteristics in powder-bed electron beam additive manufacturing (EBAM) using Ti-6Al-4V powder were investigated. The machine-specific setting, called “speed function” (SF) index that controls the beam speed and the beam current during a build, was utilized to evaluate the beam scanning speed effects. EBAM parts were fabricated using different levels of SF index (20 to 65) and build surface morphology and part microstructures were examined. A near infrared (NIR) thermal imager was used for temperatures measurements during the EBAM process. In addition, a thermal model previously developed was employed for temperature predictions and comparison with the experimental results. The major results are summarized as follows. The SF index noticeably affects the thermal characteristics in EBAM, e.g., a melt pool length of 1.72 mm vs. 1.26 mm for SF20 and SF65, respectively, at the 24.43 mm build height. This is because the higher the speed function index, the higher the beam speed, which reduces the energy density input and results in a lower process temperature. For the surface conditions and part microstructures, in general, a higher SF index tends to produce parts of rougher surfaces with more residual porosity features and large β grain columnar widths.

We develop a novel characterization of participants’ forecasts with a mixture of normal variables arising from a Markov component. Using this characterization, we formulate five behavioral specifications, including four implied by the diagnostic expectations approach, as well as three implied by REH, and derive several new predictions for Coibion and Gorodnichenko.s regression of forecast errors on forecast revisions. Predictions of all eight specifications are inconsistent with the observed instability of individual CG regressions’ coefficients, based on inflation forecasts from 24 professionals. Our findings suggest how to build on key insights of the REH and behavioral approaches in specifying individuals’ forecasts.

This study examines the potential impact of sea level rise (SLR) caused by climate change on the effects of extratropical cyclones, also known as nor?easters, in four New England coastal parks: Acadia National Park (ACAD), Boston Harbor Islands National Recreation Area (BOHA), Boston National Historical Park (BOST) and Cape Cod National Seashore (CACO). A multi-method approach is employed, including a literature review, observational data analysis, coupled hydrodynamic-wave numerical modeling, 3D visualizations, and communication of findings. The literature review examines previous studies of nor?easters and associated storm surges in New England and SLR projections across the study domain due to climate change. The observational data analysis evaluates the characteristics of nor?easters and their effects, providing a basis for validating the model. Numerical modeling is performed using the Advanced Circulation (ADCIRC) model, coupled with the Simulating Waves in the Nearshore (SWAN) model to simulate storm surges and waves. The model was validated against available observations and demonstrated its ability to simulate water levels, inland inundation, and wave heights in the study area with high accuracy. The validated model was used to simulate three powerful nor?easters (April 2007, January 2018, and March 2018) and each storm was simulated for three sea levels, (1) a baseline mean sea level representative of the year 2020, as well as with a (2) 1 ft of SLR and (3) 1 m of SLR. Analysis of the model output was used to assess the vulnerability of the parks to nor?easters by examining peak impacts in the park areas. Additional simulations were conducted to evaluate the role of waves in predicting peak water levels and the impact of inlet configurations on storm surges within coastal embayments behind the barrier beach systems in the southern Cape Cod region. The project developed maps, three-dimensional visualizations, and an interpretive film to assist the parks in planning for resource management, maintenance, emergency management, visitor access, safety, education, and outreach. These tools provide a better understanding of the potential impacts of nor?easters and SLR and enable the parks to better prepare for future storms.

The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid, semi-arid regions, e.g. much of Israel and vast area in US, where water is a limiting factor for crop production. A major reason for runoff of rain and overhead irrigation water is the structural crust that is generated over a bare soils surface during rainfall or overhead irrigation events and reduces its infiltration rate (IR), considerably. IR data is essential for predicting the amount of percolating rainwater and runoff. Available information on in situ infiltration rate and crust strength is necessary for the farmers to consider: when it is necessary to cultivate for breaking the soil crust, crust strength and seedlings emergence, precision farming, etc. To date, soil IR is measured in the laboratory and in small-scale field plots, using rainfall simulators. This method is tedious and consumes considerable resources. Therefore, an available, non-destructive-in situ methods for soil IR and soil crusting levels evaluations, are essential for the verification of infiltration and runoff models and the evaluation of the amount of available water in the soil. In this research, soil samples from the US and Israel were subjected to simulated rainstorms of increasing levels of cumulative energies, during which IR (crusting levels) were measured. The soils from the US were studied simultaneously in the US and in Israel in order to compare the effect of the methodology on the results. The soil surface reflectance was remotely measured, using laboratory and portable spectrometers in the VIS-NIR and SWIR spectral region (0.4-2.5mm). A correlation coefficient spectra in which the wavelength, consisting of the higher correlation, was selected to hold the highest linear correlation between the spectroscopy and the infiltration rate. There does not appear to be a single wavelength that will be best for all soils. The results with the six soils in both countries indeed showed that there is a significant correlation between the infiltration rate of crusted soils and their reflectance values. Regarding the wavelength with the highest correlation for each soil, it is likely that either a combined analysis with more then one wavelength or several "best" wavelengths will be found that will provide useful data on soil surface condition and infiltration rate. The product of this work will serve as a model for predicting infiltration rate and crusting levels solely from the reflectance readings. Developing the aforementioned methodologies will allow increased utilization of rain and irrigation water, reduced runoff, floods and soil erosion hazards, reduced seedlings emergence problems and increased plants stand and yields.

Temperate insectivorous bats value high prey abundance and appropriate vegetative structure when selecting foraging habitats. Forests, particularly in the eastern United States, provide prime foraging habitats for bats but can be heavily impacted by non-native plants, which may alter arthropod diversity and abundance, as well as vegetative structure. To investigate associations between non-native plants and insect abundance, vegetative structure, and consequently bat activity, we performed vegetation surveys, insect trapping, and acoustic monitoring at 23 forested plots in northern New Jersey, USA. We predicted that non-native vegetation would either positively influence bat activity by increasing structural openness (thus, facilitating flight) or negatively influence bat activity by lowering the abundance of putative prey. We also hypothesized that vegetative characteristics, and therefore non-native vegetation, impact bats differently depending on their foraging habitat preferences. The percent of non-native cover of the ground and midstory vegetative layers of our study plots ranged from 0?92.92% (x? = 46.94 ? 5.77 SE) and was significantly correlated with structural vegetative characteristics, such as midstory clutter (? = 0.01 ? 0.006 SE), but not putative prey abundance (? = -0.81 ? 2.57 SE). Generalized linear models with only vegetative characteristics best predicted overall bat activity and foraging, which were greatest in areas with a high percent non-native vegetation and low midstory clutter. Although percent non-native vegetation and midstory clutter were also significant effects for bats that prefer to forage in open areas, neither vegetative characteristics nor prey abundance were significant effects for clutter-loving bats. Such findings suggest that vegetative structure is more important than prey availability for predicting overall insectivorous bat activity, but other factors, such as foraging strategy and life history traits, can impact how bat guilds respond to non-native vegetation. Therefore, more research is required to reveal additional mechanisms by which non-native plants impact bats.

Background. Brush encroachment constitutes a serious problem in both Texas and Israel. We addressed the issue of efficacy of livestock herbivory - in the form of goat browsing - to change the ecological balance to the detriment of the shrub vegetation. Shrub consumption by goats is kept low by plant chemical defenses such as tannins and terpenes. Scientists at TAES and ARO have developed an innovative, cost-effective methodology using fecal Near Infrared Spectrometry to elucidate the dietary percentage of targeted, browse species (terpene-richredberry and blueberry juniper in the US, and tannin-rich Pistacialentiscus in Israel) for a large number of animals. The original research objectives of this project were: 1. to clarify the relative preference of goat breeds and the individual variation of goats within breeds, when consuming targeted brush species; 2. to assess the heritability of browse intake and validate the concept of breeding goat lines that exhibit high preference for chemically defended brush, using juniper as a model; 3. to clarify the relative contributions of genetics and learning on the preference for target species; 4. to identify mechanisms that are associated with greater intake of brush from the two target species; 5. to establish when the target species are the most vulnerable to grazing. (Issue no.5 was addressed only partly.) Major conclusions, solutions, achievements: Both the Israel and US scientists put significant efforts into improving and validating the technique of Fecal NIRS for predicting the botanical composition of goat diets. Israeli scientists validated the use of observational data for calibrating fecal NIRS, while US scientists established that calibrations could be used across animals differing in breed and age but that caution should be used in making comparisons between different sexes. These findings are important because the ability to select goat breeds or individuals within a breed for maximal efficiency of brush control is dependent upon accurate measurement of the botanical composition of the diet. In Israel it was found that Damascus goats consume diets more than twice richer in P. lentiscus than Mamber or Boer goats. In the US no differences were found between Angora and Boer cross goats but significant differences were found between individuals within breeds in juniper dietary percentage. In both countries, intervention strategies were found that further increased the consumption of the chemically defended plant. In Israel feeding polyethylene glycol (PEG, MW 4,000) that forms high-affinity complexes with tannins increased P. lentiscus dietary percentage an average of 7 percentage units. In the US feeding a protein supplement, which enhances rates of P450-catalyzed oxidations and therefore the rate of oxidation of monoterpenes, increased juniper consumption 5 percentage units. However, the effects of these interventions were not as large as breed or individual animal effects. Also, in a wide array of competitive tannin-binding assays in Israel with trypsin, salivary proteins did not bind more tannic acid or quebracho tannin than non-specific bovine serum albumin, parotid saliva did not bind more tannins than mixed saliva, no response of tannin-binding was found to levels of dietary tannins, and the breed effect was of minor importance, if any. These fundings strongly suggest that salivary proteins are not the first line of defense from tannin astringency in goats. In the US relatively low values for heritability and repeatability for juniper consumption were found (13% and 30%, respectively), possibly resulting from sampling error or non-genetic transfer of foraging behavior, i.e., social learning. Both alternatives seem to be true as significant variation between sequential observations were noted on the same animal and cross fostering studies conducted in Israel demonstrated that kids raised by Mamber goats showed lower propensity to consume P. lentiscus than counterparts raised by Damascus goats.

Research objectives : Identify genetic potential and community structure of soil and rhizosphere microbial community structure as affected by treated wastewater (TWW) irrigation. This objective was achieved through the examination soil and rhizosphere microbial communities of plants irrigated with fresh water (FW) and TWW. Genomic DNA extracted from soil and rhizosphere samples (Minz laboratory) was processed for DNA-based shotgun metagenome sequencing (Green laboratory). High-throughput bioinformatics was performed to compare both taxonomic and functional gene (and pathway) differences between sample types (treatment and location). Identify metabolic pathways induced or repressed by TWW irrigation. To accomplish this objective, shotgun metatranscriptome (RNA-based) sequencing was performed. Expressed genes and pathways were compared to identify significantly differentially expressed features between rhizosphere communities of plants irrigated with FW and TWW. Identify microbial gene functions and pathways affected by TWW irrigation*. To accomplish this objective, we will perform a metaproteome comparison between rhizosphere communities of plants irrigated with FW and TWW and selected soil microbial activities. Integration and evaluation of microbial community function in relation to its structure and genetic potential, and to infer the in situ physiology and function of microbial communities in soil and rhizospere under FW and TWW irrigation regimes. This objective is ongoing due to the need for extensive bioinformatics analysis. As a result of the capabilities of the new PI, we have also been characterizing the transcriptome of the plant roots as affected by the TWW irrigation and comparing the function of the plants to that of the microbiome. *This original objective was not achieved in the course of this study due to technical issues, especially the need to replace the American PIs during the project. However, the fact we were able to analyze more than one plant system as a result of the abilities of the new American PI strengthened the power of the conclusions derived from studies for the 1ˢᵗ and 2ⁿᵈ objectives. Background: As the world population grows, more urban waste is discharged to the environment, and fresh water sources are being polluted. Developing and industrial countries are increasing the use of wastewater and treated wastewater (TWW) for agriculture practice, thus turning the waste product into a valuable resource. Wastewater supplies a year- round reliable source of nutrient-rich water. Despite continuing enhancements in TWW quality, TWW irrigation can still result in unexplained and undesirable effects on crops. In part, these undesirable effects may be attributed to, among other factors, to the effects of TWW on the plant microbiome. Previous studies, including our own, have presented the TWW effect on soil microbial activity and community composition. To the best of our knowledge, however, no comprehensive study yet has been conducted on the microbial population associated BARD Report - Project 4662 Page 2 of 16 BARD Report - Project 4662 Page 3 of 16 with plant roots irrigated with TWW – a critical information gap. In this work, we characterize the effect of TWW irrigation on root-associated microbial community structure and function by using the most innovative tools available in analyzing bacterial community- a combination of microbial marker gene amplicon sequencing, microbial shotunmetagenomics (DNA-based total community and gene content characterization), microbial metatranscriptomics (RNA-based total community and gene content characterization), and plant host transcriptome response. At the core of this research, a mesocosm experiment was conducted to study and characterize the effect of TWW irrigation on tomato and lettuce plants. A focus of this study was on the plant roots, their associated microbial communities, and on the functional activities of plant root-associated microbial communities. We have found that TWW irrigation changes both the soil and root microbial community composition, and that the shift in the plant root microbiome associated with different irrigation was as significant as the changes caused by the plant host or soil type. The change in microbial community structure was accompanied by changes in the microbial community-wide functional potential (i.e., gene content of the entire microbial community, as determined through shotgun metagenome sequencing). The relative abundance of many genes was significantly different in TWW irrigated root microbiome relative to FW-irrigated root microbial communities. For example, the relative abundance of genes encoding for transporters increased in TWW-irrigated roots increased relative to FW-irrigated roots. Similarly, the relative abundance of genes linked to potassium efflux, respiratory systems and nitrogen metabolism were elevated in TWW irrigated roots when compared to FW-irrigated roots. The increased relative abundance of denitrifying genes in TWW systems relative FW systems, suggests that TWW-irrigated roots are more anaerobic compare to FW irrigated root. These gene functional data are consistent with geochemical measurements made from these systems. Specifically, the TWW irrigated soils had higher pH, total organic compound (TOC), sodium, potassium and electric conductivity values in comparison to FW soils. Thus, the root microbiome genetic functional potential can be correlated with pH, TOC and EC values and these factors must take part in the shaping the root microbiome. The expressed functions, as found by the metatranscriptome analysis, revealed many genes that increase in TWW-irrigated plant root microbial population relative to those in the FW-irrigated plants. The most substantial (and significant) were sodium-proton antiporters and Na(+)-translocatingNADH-quinoneoxidoreductase (NQR). The latter protein uses the cell respiratory machinery to harness redox force and convert the energy for efflux of sodium. As the roots and their microbiomes are exposed to the same environmental conditions, it was previously hypothesized that understanding the soil and rhizospheremicrobiome response will shed light on natural processes in these niches. This study demonstrate how newly available tools can better define complex processes and their downstream consequences, such as irrigation with water from different qualities, and to identify primary cues sensed by the plant host irrigated with TWW. From an agricultural perspective, many common practices are complicated processes with many ‘moving parts’, and are hard to characterize and predict. Multiple edaphic and microbial factors are involved, and these can react to many environmental cues. These complex systems are in turn affected by plant growth and exudation, and associated features such as irrigation, fertilization and use of pesticides. However, the combination of shotgun metagenomics, microbial shotgun metatranscriptomics, plant transcriptomics, and physical measurement of soil characteristics provides a mechanism for integrating data from highly complex agricultural systems to eventually provide for plant physiological response prediction and monitoring. BARD Report

1.1 Resumen macroeconómico En el segundo trimestre la economía enfrentó varios choques, principalmente de oferta y de costos, la mayoría de los cuales no fueron anticipados, o los previstos fueron más persistentes de lo esperado, y que en conjunto interrumpieron la recuperación de la actividad económica observada a comienzos de año y llevaron la inflación total a niveles superiores a la meta. La inflación básica (sin alimentos ni regulados: SAR) aumentó, pero se mantuvo baja y acorde con lo esperado por el equipo técnico. A comienzos de abril se inició una tercera ola de pandemia, más acentuada y prolongada que la anterior, con un elevado costo en vidas humanas y algún impacto negativo en la recuperación económica. Entre mayo y mediados de junio los bloqueos de las carreteras y los problemas de orden público tuvieron un fuerte efecto negativo sobre la actividad económica y la inflación. Se estima que la magnitud de estos dos choques combinados habría generado una caída en niveles en el producto interno bruto (PIB) con respecto al primer trimestre del año. Adicionalmente, los bloqueos causaron un aumento significativo de los precios de los alimentos. A estos choques se sumaron los efectos acumulados de la disrupción global en algunas cadenas de valor y el incremento en los fletes internacionales que desde finales de 2020 vienen generando restricciones de oferta y aumentos de costos. Todos estos factores, que afectaron principalmente el índice de precios al consumidor (IPC) de bienes y de alimentos, explicaron la mayor parte del error de pronóstico del equipo técnico y el aumento de la inflación total a niveles superiores a la meta del 3 %. El incremento en la inflación básica y de los precios de los regulados fue acorde con lo esperado por el equipo técnico, y se explica principalmente por la eliminación de varios alivios de precios otorgados un año atrás. A todo esto se suma la mayor percepción de riesgo soberano y las presiones al alza que esto implica sobre el costo de financiamiento externo y la tasa de cambio. A pesar de los fuertes choques negativos, el crecimiento económico esperado para la primera mitad del año (9,1%), es significativamente mayor que lo proyectado en el informe de abril (7,1%), signo de una economía más dinámica que se recuperaría más rápido de lo previsto. Desde finales de 2020 las diferentes cifras de actividad económica han mostrado un crecimiento mayor que el esperado. Esto sugiere que los efectos negativos sobre el producto de las recurrentes olas de contagio estarían siendo cada vez menos fuertes y duraderos. No obstante, la tercera ola de contagio del Covid-19, y en mayor medida los bloqueos a las vías y los problemas de orden público, habrían generado una caída del PIB durante el segundo trimestre, frente al primero. Pese a lo anterior, los datos del índice de seguimiento a la economía (ISE) de abril y mayo han resultado mayores que lo esperado, y las nuevas cifras de actividad económica sectoriales sugieren que el impacto negativo de la pandemia sobre el producto se sigue moderando, en un entorno de menores restricciones a la movilidad y de mayor avance en el ritmo de vacunación. Los registros de transporte de carga (junio) y la demanda de energía no regulada (julio), entre otros, indican una recuperación importante después de los bloqueos en mayo. Con todo lo anterior, el incremento anual del PIB del segundo trimestre se habría situado alrededor del 17,3 % (antes 15,8 %), explicado en gran parte por una base baja de comparación. Para todo 2021 el equipo técnico incrementó su proyección de crecimiento desde un 6 % hasta el 7,5 %. Este pronóstico, que está rodeado de una incertidumbre inusualmente elevada, supone que no se presentarán problemas de orden público y que posibles nuevas olas de contagio del Covid-19 no tendrán efectos negativos adicionales sobre la actividad económica. Frente al pronóstico del informe pasado, la recuperación de la demanda externa, los niveles de precios de algunos bienes básicos que exporta el país y la dinámica de las remesas de trabajadores han sido mejores que las esperadas y seguirían impulsando la recuperación del ingreso nacional en lo que resta del año. A esto se sumaría la aún amplia liquidez internacional, la aceleración en el proceso de vacunación y las bajas tasas de interés, factores que continuarían favoreciendo la actividad económica. La mejor dinámica del primer semestre, que llevó a una revisión al alza en el crecimiento de todos los componentes del gasto, continuaría hacia adelante y, antes de lo esperado en abril, la economía recuperaría los niveles de producción de 2019 a finales de 2021. El pronóstico continúa incluyendo efectos de corto plazo sobre la demanda agregada de una reforma tributaria de magnitud similar a la proyectada por el Gobierno. Con todo eso, en el escenario central de este informe, el pronóstico de crecimiento para 2021 es del 7,5 % y para 2022 del 3,1 %. A pesar de esto, el nivel de la actividad económica seguiría siendo inferior a su potencial. La mejora en estas proyecciones, sin embargo, está rodeada de una alta incertidumbre. En junio la inflación anual (3,63 %) aumentó más de lo esperado debido al comportamiento del grupo de alimentos, mientras que la inflación básica (1,87 %) fue similar a la proyectada. En lo que resta del año el mayor nivel del IPC de alimentos persistiría y contribuiría a mantener la inflación por encima de la meta. A finales de 2022 la inflación total y básica retornarían a tasas cercanas al 3 %, en un entorno de desaceleración del IPC de alimentos y de menores excesos de capacidad productiva. En los meses recientes el aumento en los precios internacionales de los fletes y de los bienes agrícolas, y las mayores exportaciones de carne y el ciclo ganadero han ejercido presiones al alza sobre el precio de los alimentos, principalmente de los procesados. A estas fuerzas persistentes se sumaron los bloqueos de las vías nacionales y los problemas de orden público en varias ciudades registrados en mayo y parte de junio, los cuales se reflejaron en una fuerte restricción en la oferta y en un aumento anual no esperado del IPC de alimentos (8,52 %). El grupo de regulados (5,93 %) también se aceleró, debido a la baja base de comparación en los precios de la gasolina y a la disolución de parte de los alivios a las tarifas de servicios públicos otorgados en 2020. Como se proyectaba, la inflación SAR repuntó al 1,87 %, debido a la reactivación de los impuestos indirectos de algunos bienes y servicios eliminados un año atrás, y por las presiones al alza que ejercieron los alimentos sobre las comidas fuera del hogar (CFH), entre otros. En lo que resta del año se espera que el aumento en los alimentos perecederos se revierta, siempre y cuando no se registren nuevos bloqueos duraderos a las vías nacionales. El mayor nivel de precios de los alimentos procesados persistiría y contribuiría a mantener la inflación por encima de la meta a finales de año. La inflación SAR continuaría con una tendencia creciente, en la medida en que los excesos de capacidad productiva se sigan cerrando y registraría un aumento transitorio en marzo de 2022, debido principalmente al restablecimiento del impuesto al consumo en las CFH. Con todo esto, para finales de 2021 y 2022 se estima una inflación total del 4,1 % y 3,1 %, y una inflación básica del 2,6 % y 3,2 %, respectivamente. El comportamiento conjunto de los precios del IPC SAR, junto con continuas sorpresas al alza en la actividad económica, son interpretados por el equipo técnico como señales de amplios excesos de capacidad productiva de la economía. Estos persistirían en los siguientes dos años, al final de los cuales la brecha del producto se cerraría. El mayor crecimiento económico sugiere una brecha del producto menos negativa que la estimada hace un trimestre. Sin embargo, el comportamiento de la inflación básica, especialmente en servicios, indica que el PIB potencial se ha recuperado de forma sorpresiva y que los excesos de capacidad siguen siendo amplios, con una demanda agregada afectada de forma persistente. Esta interpretación encuentra soporte en el mercado laboral, en donde persiste un desempleo alto y la recuperación de los empleos perdidos se estancó. Adicionalmente, los aumentos en la inflación en buena medida están explicados por choques de oferta y de costos y por la disolución de algunos alivios de precios otorgados un año atrás. Los pronósticos de crecimiento y de inflación descritos son coherentes con una brecha del producto que se cierra más rápido y es menos negativa en todo el horizonte de pronóstico con respecto al informe de abril. No obstante, la incertidumbre sobre los excesos de capacidad es muy alta y es un riesgo sobre el pronóstico. Las perspectivas de las cuentas fiscales de Colombia se deterioraron, Standard & Poor’s Global Ratings (S&P) y Fitch Ratings (Fitch) redujeron su calificación crediticia, los bloqueos y problemas de orden público afectaron el producto y el país enfrentó una nueva ola de contagios de Covid-19 más acentuada y prolongada que las pasadas. Todo lo anterior se ha reflejado en un aumento de las primas de riesgo y en una depreciación del peso frente al dólar. Esto ha ocurrido en un entorno favorable de ingresos externos. Los precios internacionales del petróleo, del café y de otros bienes básicos que exporta el país aumentaron y han contribuido a la recuperación de los términos de intercambio y del ingreso nacional, y han mitigado las presiones al alza sobre las primas de riesgo y la tasa de cambio. En el presente informe se incrementó el precio esperado del petróleo para 2021 a USD 68 por barril (antes USD 61 bl) y para 2022 a USD 66 bl (antes USD 60 bl). Esta mayor senda presenta una convergencia hacia precios menores que los observados recientemente, como resultado de una mayor oferta mundial esperada de petróleo, la cual más que compensaría el incremento en la demanda de este bien básico. Por ende, se supone que el aumento reciente de los precios tiene un carácter transitorio. En el escenario macroeconómico actual se espera que las condiciones financieras internacionales sean algo menos favorables, a pesar de la mejora en los ingresos externos por cuenta de una mayor demanda y unos precios del petróleo y de otros productos de exportación más altos. Frente al informe de abril el crecimiento de la demanda externa fue mejor que el esperado, y las proyecciones para 2021 y 2022 aumentaron del 5,2 % al 6,0 % y del 3,4 % al 3,5 %, respectivamente. En lo corrido del año las cifras de actividad económica muestran una demanda externa más dinámica de la esperada. En los Estados Unidos y China la recuperación del producto ha sido más rápida que la registrada en los países de la región. En estos últimos la reactivación económica ha estado limitada por los rebrotes del Covid-19, las limitaciones en la oferta de vacunas y el poco espacio fiscal para enfrentar la pandemia, entre otros factores. La buena dinámica en el comercio externo de bienes se ha dado en un entorno de deterioro en las cadenas de valor y de un aumento importante en los precios de las materias primas y en el costo de los fletes. En los Estados Unidos la inflación sorprendió al alza y su valor observado y esperado se mantiene por encima de la meta, al tiempo que se incrementó la proyección de crecimiento económico. Con esto, el inicio de la normalización de la política monetaria en ese país se daría antes de lo proyectado. En este informe se estima que el primer incremento en la tasa de interés de la Reserva Federal de los Estados Unidos se dé a finales de 2022 (antes del primer trimestre de 2023). Para Colombia se supone una mayor prima de riesgo frente al informe de abril y se sigue esperando que presente una tendencia creciente, dada la acumulación de deuda pública y externa del país. Todo esto contribuiría a un incremento en el costo del financiamiento externo en el horizonte de pronóstico. La postura expansiva de la política monetaria sigue soportando unas condiciones financieras internas favorables. En el segundo trimestre la tasa de interés interbancaria y el índice bancario de referencia (IBR) se han mantenido acordes con la tasa de interés de política. Las tasas de interés promedio de captación y crédito continuaron históricamente bajas, a pesar de algunos incrementos observados a finales de junio. La cartera en moneda nacional detuvo su desaceleración anual y, entre marzo y junio, el crédito a los hogares se aceleró, principalmente para compra de vivienda. La recuperación de la cartera comercial y de los desembolsos a ese sector fue importante, y se alcanzó de nuevo el elevado saldo observado un año atrás, cuando las empresas requirieron niveles significativos de liquidez para enfrentar los efectos económicos de la pandemia. El riesgo de crédito aumentó, las provisiones se mantienes altas y algunos bancos han retirado de su balance una parte de su cartera vencida. No obstante, las utilidades del sistema financiero se han recuperado y sus niveles de liquidez y solvencia se mantienen por encima del mínimo regulatorio. A partir de este informe se implementará una nueva metodología para cuantificar y comunicar la incertidumbre que rodea los pronósticos del escenario macroeconómico central, en un entorno de política monetaria activa. Esta metodología se conoce como densidades predictivas (DP) y se explica en detalle en el Recuadro 1. Partiendo del balance de riesgos que contiene los principales factores que, de acuerdo con el juicio del equipo técnico, podrían afectar a la economía en el horizonte de pronóstico, la metodología DP produce distribuciones de probabilidad sobre el pronóstico de las principales variables (v. g.: crecimiento, inflación). Estas distribuciones reflejan el resultado de los posibles choques (a variables externas, precios y actividad económica) que podría recibir la economía y su transmisión, considerando la estructura económica y la respuesta de política monetaria en el futuro. En este sentido, permiten cuantificar la incertidumbre alrededor del pronóstico y su sesgo. El ejercicio DP muestra un sesgo a la baja en el crecimiento económico y en la brecha del producto, y al alza en la inflación. El balance de riesgos indica que las disyuntivas para la política monetaria serán potencialmente más complejas que lo contemplado en el pasado. Por el lado de las condiciones de financiamiento externo, se considera que el mayor riesgo es que se tornen un poco menos favorables, en un escenario en el cual la Reserva Federal de los Estados Unidos incremente con mayor prontitud su tasa de interés. Esto último, ante un crecimiento económico y del empleo mayor que el esperado en los Estados Unidos que genere presiones significativas sobre la inflación de ese país. A esto se suma la incertidumbre sobre el panorama fiscal en Colombia y sus efectos sobre la prima de riesgo y el costo del financiamiento externo. En el caso del crecimiento, la mayoría de los riesgos son a la baja, destacándose los efectos de la incertidumbre política y fiscal sobre las decisiones de consumo e inversión, la aparición de nuevas olas de contagio de la pandemia del Covid-19 y sus impactos sobre la actividad económica. En el caso de la inflación, se incorporó el riesgo de una mayor persistencia de los choques asociados con la disrupción de las cadenas de valor, mayores precios internacionales de las materias primas y de los alimentos, y una recuperación más lenta que la esperada de la cadena agrícola nacional afectada por los pasados bloqueos a las vías. Estos riesgos presionarían al alza principalmente los precios de los alimentos y de los bienes. Como principal riesgo a la baja se incluyó un alza de los arriendos menor que el esperado en el escenario central, explicada por una demanda débil y por una mayor oferta en 2022 dadas las altas ventas de vivienda observadas en el presente año. Con todo, el crecimiento económico presenta un sesgo a la baja y, con el 90 % de confianza, se encontraría entre un 6,1 % y 9,1 % para 2021 y entre el 0,5 % y 4,1 % para 2022. La brecha del producto tendría un sesgo a la baja, principalmente en 2022. El sesgo de la inflación es al alza, y se encontraría entre el 3,7 % y 4,9 % en 2021, y el 2,2 % y 4,7 % en 2022, con un 90 % de probabilidad. 1.2 Decisión de política monetaria En las reuniones de junio y julio la JDBR decidió mantener la tasa de política monetaria inalterada en 1,75 %.