Visible and near infrared spectroscopy in soil science

This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy. Our intention is for the review to serve as a source of up-to date information on the past and current role of vis–NIR spectroscopy in soil science. It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions. To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations. A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals. We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pre-tratments, co-variations in data sets, and mathematical data preprocessing. Field analyses and strategies for the practical use of vis–NIR are considered. We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content. Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned. For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function. To do this, research in soil spectroscopy needs to be more collaborative and strategic. The development of the Global Soil Spectral Library might be a step in the right direction

Development of a Proximal Soil Sensing System for the Continuous Management of Acid Soil

The notion that agriculturally productive land may be treated as a relatively homogeneous resource at thewithin-field scale is not sound. This assumption and the subsequent uniform application of planting material,chemicals and/or tillage effort may result in zones within a field being under- or over-treated. Arising fromthese are problems associated with the inefficient use of input resources, economically significant yield losses,excessive energy costs, gaseous or percolatory release of chemicals into the environment, unacceptable long-term retention of chemicals and a less-than-optimal growing environment. The environmental impact of cropproduction systems is substantial. In this millennium, three important issues for scientists and agrariancommunities to address are the need to efficiently manage agricultural land for sustainable production, the maintenance of soil and water resources and the environmental quality of agricultural land.Precision agriculture (PA) aims to identify soil and crop attribute variability, and manage it in an accurate and timely manner for near-optimal crop production. Unlike conventional agricultural management where an averaged whole-field analytical result is employed for decision-making, management in PA is based on site-specific soil and crop information. That is, resource application and agronomic practices are matched with variation in soil attributes and crop requirements across a field or management unit. Conceptually PA makes economic and environmental sense, optimising gross margins and minimising the environmental impact of crop production systems. Although the economic justification for PA can be readily calculated, concepts such as environmental containment and the safety of agrochemicals in soil are more difficult to estimate. However,it may be argued that if PA lessens the overall agrochemical load in agricultural and non-agricultural environments, then its value as a management system for agriculture increases substantially.Management using PA requires detailed information of the spatial and temporal variation in crop yield components, weeds, soil-borne pests and attributes of physical, chemical and biological soil fertility. However,detailed descriptions of fine scale variation in soil properties have always been difficult and costly to perform.Sensing and scanning technologies need to be developed to more efficiently and economically obtain accurate information on the extent and variability of soil attributes that affect crop growth and yield. The primary aim of this work is to conduct research towards the development of an 'on-the-go' proximal soil pH and lime requirement sensing system for real-time continuous management of acid soil. It is divided into four sections.Section one consists of two chapters; the first describes global and historical events that converged into the development of precision agriculture, while chapter two provides reviews of statistical and geostatistical techniques that are used for the quantification of soil spatial variability and of topics that are integral to the concept of precision agriculture. The review then focuses on technologies that are used for the complete enumeration of soil, namely remote and proximal sensing.Section two comprises three chapters that deal with sampling and mapping methods. Chapter three provides a general description of the environment in the experimental field. It provides descriptions of the field site,topography, soil condition at the time of sampling, and the spatial variability of surface soil chemical properties. It also described the methods of sampling and laboratory analyses. Chapter four discusses some of the implications of soil sampling on analytical results and presents a review that quantifies the accuracy,precision and cost of current laboratory techniques. The chapter also presents analytical results that show theloss of information in kriged maps of lime requirement resulting from decreases in sample size. The messageof chapter four is that the evolution of precision agriculture calls for the development of 'on-the-go' proximal soil sensing systems to characterise soil spatial variability rapidly, economically, accurately and in a timely manner. Chapter five suggests that for sparsely sampled data the choice of spatial modelling and mapping techniques is important for reliable results and accurate representations of field soil variability. It assesses a number of geostatistical methodologies that may be used to model and map non-stationary soil data, in this instance soil pH and organic carbon. Intrinsic random functions of order k produced the most accurate and parsimonious predictions of all of the methods tested.Section three consists of two chapters whose theme pertains to sustainable and efficient management of acid agricultural soil. Chapter six discusses soil acidity, its causes, consequences and current management practices.It also reports the global extent of soil acidity and that which occurs in Australia. The chapter closes by proposing a real-time continuous management system for the management of acid soil. Chapter seven reports results from experiments conducted towards the development of an 'on-the-go' proximal soil pH and lime requirement sensing system that may be used for the real-time continuous management of acid soil. Assessment of four potentiometric sensors showed that the pH Ion Sensitive Field Effect Transistor (ISFET)was most suitable for inclusion in the proposed sensing system. It is accurate and precise, drift and hysteresis are low, and most importantly it's response time is small. A design for the analytical system was presented based on flow injection analysis (FIA) and sequential injection analysis (SIA) concepts. Two different modes of operation were described. Kinetic experiments were conducted to characterise soil:0.01M CaCl2 pH(pHCaCl2) and soil:lime requirement buffer (pH buffer) reactions. Modelling of the pH buffer reactions described their sequential, biphasic nature. A statistical methodology was devised to predict pH buffer measurements using only initial reaction measurements at 0.5s, 1s, 2s and 3s measurements. The accuracy of the technique was 0.1pH buffer units and the bias was low. Finally, the chapter describes a framework for the development of a prototype soil pH and lime requirement sensing system and the creative design of the system.The final section relates to the management of acid soil by liming. Chapter eight describes the development of empirical deterministic models for rapid predictions of lime requirement. The response surface models are based on soil:lime incubations, pH buffer measurements and the selection of target pH values. These models are more accurate and more practical than more conventional techniques, and may be more suitably incorporated into the spatial decision-support system of the proposed real-time continuous system for the management of acid soil. Chapter nine presents a glasshouse liming experiment that was used to authenticate the lime requirement model derived in the previous chapter. It also presents soil property interactions and soil-plant relationships in acid and ameliorated soil, to compare the effects of no lime applications, single-rate and variable-rate liming. Chapter X presents a methodology for modelling crop yields in the presence of uncertainty. The local uncertainty about soil properties and the uncertainty about model parameters were accounted for by using indicator kriging and Latin Hypercube Sampling for the propagation of uncertainties through two regression functions; a yield response function and one that equates resultant pH after the application of lime. Under the assumptions and constraints of the analysis, single-rate liming was found to be the best management option

Electric field effect on the luminescence of KI:Tl

Thermoluminescence of KI:Tl, x- or &#946;-irradiated at T<77°K showed 2 main peaks at 105 and 170°K. They are resp. attributed to the recombination of mobile VK centers with Tl0 centers and to the recombination of thermally released electrons from Tl0 centers with Tl2+ centres. Similar experiments performed under static electric fields (E<40 kV cm-1) show that the intensity of the 2nd glow peak is strongly reduced. The relative intensity variation is anticorrelated with the intensity of glow peaks occurring at >230°K. We suggestthat in the temperature range in which Tl0 centres are thermally ionised, the effect of the electric field favour the retrapping of these electrons on other traps (still unknown). Irradiation doses also play an important role and their effects are studied at 77°K and T=200°K

Are you really my clone? Identity verification of the in-trust sweetpotato collection at the International Potato Center.

The global in-trust sweetpotato collection maintained by the International Potato Center (CIP) in Lima, Peru consists of over 5,000 cultivated sweetpotato accessions maintained as clones in vitro as well as over 1,000 accessions from 67 species of Ipomoea maintained as seed populations. The clonal sweetpotato collection at CIP was initiated in the 1980’s and for 60% of the collection, original material still exists as potted plants in the greenhouse. This provides a unique opportunity where genetic integrity of a clonal collection, maintained in vitro for the past thirty years, can be confirmed by a side-by-side comparison of the same accession from the greenhouse. Initial molecular comparison is done using a set of twenty SSR primers followed by side-by-side comparison in the field using 30 morphological descriptors. Confirmation of identity requires both genetic and morphological analysis as a low percentage of the accessions appear to be duplicates based on SSR yet are morphologically distinct. Historical morphological descriptor data is used as a check to confirm identity and is being used as the sole check for accessions where we do not have original material for comparison. SSR results from 70% of the collection has confirmed that 85% of the in vitro accessions are true-to-type. In vitro accessions which are not true-to-type are reisolated and cleaned of viruses from the confirmed true-to-type greenhouse accessions. Accessions which are true-to-type are fingerprinted using DArTseq to provide a sequence-based fingerprint

Determinants of new drugs prescription in the Swiss healthcare market.

Drug markets are very complex and, while many new drugs are registered each year, little is known about what drives the prescription of these new drugs. This study attempts to lift the veil from this important subject by analyzing simultaneously the impact of several variables on the prescription of novelty. Data provided by four Swiss sickness funds were analyzed. These data included information about more than 470,000 insured, notably their drug intake. Outcome variable that captured novelty was the age of the drug prescribed. The overall variance in novelty was partitioned across five levels (substitutable drug market, patient, physician, region, and prescription) and the influence of several variables measured at each of these levels was assessed using a non-hierarchical multilevel model estimated by Bayesian Markov Chain Monte Carlo methods. More than 92% of the variation in novelty was explained at the substitutable drug market-level and at the prescription-level. Newer drugs were prescribed in markets that were costlier, less concentrated, included more insured, provided more drugs and included more active substances. Over-the-counter drugs were on average 12.5 years older while generic drugs were more than 15 years older than non-generics. Regional disparities in terms of age of prescribed drugs could reach 2.8 years. Regulation of the demand has low impact, with little variation explained at the patient-level and physician-level. In contrary, the market structure (e.g. end of patent with generic apparition, concurrence among producers) had a strong contribution to the variation of drugs ages

Mental health and its associations with weight in women with gestational diabetes mellitus. A prospective clinical cohort study.

Despite the prevalence of depression in women with gestational diabetes mellitus (GDM) and the relationship between mental health (depression and well-being) and metabolic health, little is known about mental health or its metabolic impact in GDM pregnancy. This prospective clinical cohort study aimed to investigate associations between 1) well-being and depression, and 2) mental health and weight/weight gain in women with GDM. We included 334 pregnant women with GDM treated at a Swiss University Hospital between January 2016 and December 2018. They completed two self-report questionnaires: The World Health Organization well-being index (WHO-5) at the first (29 weeks of gestation) and last (36 weeks of gestation) GDM visits during pregnancy and the Edinburgh Postnatal Depression Scale (EPDS) at the first GDM visit. A cut-off of ≥11 was selected for this questionnaire to indicate the presence of elevated depression scores. There was an inverse association between the well-being and depression total scores at the first GDM visit during pregnancy (r = -0.55; p &lt; 0.0001). Elevated depression scores at the first GDM visit were associated with subsequent weight gain in GDM pregnancy (β = 1.249; p = 0.019). In women with GDM, elevated depression scores during pregnancy are prospectively associated with weight gain. Depression symptoms should therefore be screened for and treated in women with GDM to reduce the risks associated with excessive weight gain during pregnancy

Mental health and its associations with glucose-lowering medication in women with gestational diabetes mellitus. A prospective clinical cohort study.

Mental health symptoms are frequent in women with gestational diabetes mellitus (GDM) and may influence glycemic control. We therefore investigated if mental health symptoms (high depression and low well-being scores) predicted a need for glucose-lowering medication and if this use of medication influenced the trajectory of mental health during pregnancy and in the postpartum period. We included 341 pregnant women from a cohort of GDM women in a Swiss University Hospital. The World Health Organization Well-being Index-Five was collected at the first and last GDM and at the postpartum clinical visits and the Edinburgh Postnatal Depression Scale at the first GDM and the postpartum clinical visits. Medication intake was extracted from participants' medical records. We conducted linear and logistic regressions with depression as an interaction factor. Mental health symptoms did not predict a need for medication (all p ≥ 0.29). Mental health improved over time (both p ≤ 0.001) and use of medication did not predict this change (all p ≥ 0.40). In women with symptoms of depression, medication was associated with less improvement in well-being at the postpartum clinical visit (p for interaction=0.013). Mental health and glucose-lowering medication did not influence each other in an unfavourable way in this cohort of women with GDM