Relationships of the wild peanut species, section Arachis: A resource for botanical classification, crop improvement, and germplasm management.

PREMISE: Wild species are strategic sources of valuable traits to be introduced into crops through hybridization. For peanut, the 33 currently described wild species in the section Arachis are particularly important because of their sexual compatibility with the domesticated species, Arachis hypogaea. Although numerous wild accessions are carefully preserved in seed banks, their morphological similarities pose challenges to routine classification. METHODS: Using a high-density array, we genotyped 272 accessions encompassing all diploid species in section Arachis. Detailed relationships between accessions and species were revealed through phylogenetic analyses and interpreted using the expertise of germplasm collectors and curators. RESULTS: Two main groups were identified: one with A genome species and the other with B, D, F, G, and K genomes. Species groupings generally showed clear boundaries. Structure within groups was informative, for instance, revealing the history of the proto-domesticate A. stenosperma. However, some groupings suggested multiple sibling species. Others were polyphyletic, indicating the need for taxonomic revision. Annual species were better defined than perennial ones, revealing limitations in applying classical and phylogenetic species concepts to the genus. We suggest new species assignments for several accessions. CONCLUSIONS: Curated by germplasm collectors and curators, this analysis of species relationships lays the foundation for future species descriptions, classification of unknown accessions, and germplasm use for peanut improvement. It supports the conservation and curation of current germplasm, both critical tasks considering the threats to the genus posed by habitat loss and the current restrictions on new collections and germplasm transfer.

Unequal distributions of crowdsourced weather data in England and Wales.

Personal weather stations (PWS) can provide useful data on urban climates by densifying the number of weather measurements across major cities. They do so at a lower cost than official weather stations by national meteorological services. Despite the increasing use of PWS data, little attention has yet been paid to the underlying socio-economic and environmental inequalities in PWS coverage. Using social deprivation, demographic, and environmental indicators in England and Wales, we characterize existing inequalities in the current coverage of PWS. We find that there are fewer PWS in more deprived areas which also observe higher proportions of ethnic minorities, lower vegetation coverage, higher building height and building surface fraction, and lower proportions of inhabitants under 65 years old. This implies that data on urban climate may be less reliable or more uncertain in particular areas, which may limit the potential for climate adaptation and empowerment in those communities.

Valuing the health benefits of nature-based recreational physical activity in England.

Physical activity (PA) reduces the risk of several non-communicable diseases (NCDs). Natural environments support recreational PA. Using data including a representative cross-sectional survey of the English population, we estimated the annual value of nature-based PA conducted in England in 2019 in terms of avoided healthcare and societal costs of disease. Population-representative data from the Monitor of Engagement with the Natural Environment (MENE) survey (n = 47,580; representing 44,386,756) were used to estimate the weekly volume of nature-based recreational PA by adults in England in 2019. We used epidemiological dose-response data to calculate incident cases of six NCDs (ischaemic heart disease (IHD), ischaemic stroke (IS), type 2 diabetes (T2D), colon cancer (CC), breast cancer (BC) and major depressive disorder (MDD)) prevented through nature-based PA, and estimated associated savings using published costs of healthcare, informal care and productivity losses. We investigated additional savings resulting from hypothetical increases in: (a) visitor PA and (b) visitor numbers. In 2019, 22million adults > 16 years of age in England visited natural environments at least weekly. At reported volumes of nature-based PA, we estimated that 550 cases of IHD, 168 cases of IS, 1,410 cases of T2D, 41 cases of CC, 37 cases of BC and 10,552 cases of MDD were prevented, creating annual savings of £108.7million (95 % uncertainty interval: £70.3million; £150.3million). Nature-based recreational PA in England results in reduced burden of disease and considerable annual savings through prevention of priority NCDs. Strategies that increase nature-based PA could lead to further reductions in the societal burden of NCDs.

The potential of urban trees to reduce heat-related mortality in London.

Increasing temperatures and more frequent heatwave events pose threats to population health, particularly in urban environments due to the urban heat island (UHI) effect. Greening, in particular planting trees, is widely discussed as a means of reducing heat exposure and associated mortality in cities. This study aims to use data from personal weather stations (PWS) across the Greater London Authority to understand how urban temperatures vary according to tree canopy coverage and estimate the heat-health impacts of London's urban trees. Data from Netatmo PWS from 2015-2022 were cleaned, combined with official Met Office temperatures, and spatially linked to tree canopy coverage and built environment data. A generalized additive model was used to predict daily average urban temperatures under different tree canopy coverage scenarios for historical and projected future summers, and subsequent health impacts estimated. Results show areas of London with higher canopy coverage have lower urban temperatures, with average maximum daytime temperatures 0.8 °C and minimum temperatures 2.0 °C lower in the top decile versus bottom decile canopy coverage during the 2022 heatwaves. We estimate that London's urban forest helped avoid 153 heat attributable deaths from 2015-2022 (including 16 excess deaths during the 2022 heatwaves), representing around 16% of UHI-related mortality. Increasing tree coverage 10% in-line with the London strategy would have reduced UHI-related mortality by a further 10%, while a maximal tree coverage would have reduced it 55%. By 2061-2080, under RCP8.5, we estimate that London's current tree planting strategy can help avoid an additional 23 heat-attributable deaths a year, with maximal coverage increasing this to 131. Substantial benefits would also be seen for carbon storage and sequestration. Results of this study support increasing urban tree coverage as part of a wider public health effort to mitigate high urban temperatures.

Spatially Explicit Correction of Simulated Urban Air Temperatures Using Crowdsourced Data.

Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather sensors (PWSs) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that carefully quality-checked PWS data not only improve urban climate models' evaluation but can also serve for bias correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and south-east England during the hot summer of 2018 with the Weather Research and Forecasting (WRF) Model and its building Effect parameterization with the building energy model (BEP-BEM) activated, we evaluated the modeled temperatures against 402 urban PWSs and showcased a heterogeneous spatial distribution of the model's cool bias that was not captured using official weather stations only. This finding indicated a need for spatially explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models' biases in each urban grid cell. This bias-correction technique is the first to consider that modeled urban temperatures follow a nonlinear spatially heterogeneous bias that is decorrelated from urban fraction. Our results showed that the bias correction was beneficial to bias correct daily minimum, daily mean, and daily maximum temperatures in the cities. We recommend that urban climate modelers further investigate the use of quality-checked PWSs for model evaluation and derive a framework for bias correction of urban climate simulations that can serve urban climate impact studies.

Commonly used indices disagree about the effect of moisture on heat stress.

Irrigation and urban greening can mitigate extreme temperatures and reduce adverse health impacts from heat. However, some recent studies suggest these interventions could actually exacerbate heat stress by increasing humidity. These studies use different heat stress indices (HSIs), hindering intercomparisons of the relative roles of temperature and humidity. Our method uses calculus of variations to compare the sensitivity of HSIs to temperature and humidity, independent of HSI units. We explain the properties of different HSIs and identify conditions under which they disagree. We highlight recent studies where the use of different HSIs could have led to opposite conclusions. Our findings have significant implications for the evaluation of irrigation and urban greening as adaptive responses to overheating and climate adaptation measures in general. We urge researchers to be critical in their choice of HSIs, especially in relation to health outcomes; our method provides a useful tool for making informed comparisons.

Cystatin C kidney functional reserve: a simple method to predict outcome in chronic kidney disease.

BACKGROUND: Kidney functional reserve (KFR), the only clinical kidney stress test, is not routinely measured because the complexity of measurement has limited clinical application. We investigated the utility of plasma cystatin C (CysC) after oral protein loading (PL) to determine KFR in Stages 3 and 4 chronic kidney disease (CKD). METHODS: Following a 24-h low-protein diet, KFR was measured after oral protein by hourly plasma CysC and compared with simultaneous creatinine clearance (CrCl) and radionuclide 99technetium diethylenetriaminepentaacetatic acid (Tc-99m-DTPA) measured glomerular filtration rate (mGFR) measurement in an observational, single-centre cohort study of adults with CKD Stages 3 and 4. Subjects were followed for 3 years for fast (F) or slow (S) CKD progression, dialysis requirement or death or a combination of major adverse kidney events (MAKEs). RESULT: CysC, CrCl and Tc-99m-DTPA mGFR measurements of KFR in 19 CKD Stage 3 and 21 CKD Stage 4 patients yielded good agreement. KFR was not correlated with baseline kidney function. Eight CKD Stage 3 (42%) and 11 CKD Stage 4 (52%) subjects reached their lowest serum CysC concentration 4 h after PL. CysC KFR and baseline serum creatinine (sCr) predicted death or dialysis or MAKE-F with a respective area under the curve (AUC) of 0.73 [95% confidence interval (CI) 0.48-0.89] and 0.71 (95% CI 0.51-0.84). Including CysC KFR, age, baseline sCr and nadir CysC predicted a decrease in sCr-estimated GFR >1.2 mL/min/year (MAKE-S) with an AUC of 0.89. CONCLUSIONS: Serial CysC avoided timed urine collection and radionuclide exposure and yielded equivalent estimates of KFR. Serial CysC may facilitate monitoring of KFR in clinical practice.

Regional disparities and seasonal differences in climate risk to rice labour.

The 880 million agricultural workers of the world are especially vulnerable to increasing heat stress due to climate change, affecting the health of individuals and reducing labour productivity. In this study, we focus on rice harvests across Asia and estimate the future impact on labour productivity by considering changes in climate at the time of the annual harvest. During these specific times of the year, heat stress is often high compared to the rest of the year. Examining climate simulations of the Coupled Model Intercomparison Project 6 (CMIP6), we identified that labour productivity metrics for the rice harvest, based on local wet-bulb globe temperature, are strongly correlated with global mean near-surface air temperature in the long term (p ≪ 0.01, R 2 > 0.98 in all models). Limiting global warming to 1.5 °C rather than 2.0 °C prevents a clear reduction in labour capacity of 1% across all Asia and 2% across Southeast Asia, affecting the livelihoods of around 100 million people. Due to differences in mechanization between and within countries, we find that rice labour is especially vulnerable in Indonesia, the Philippines, Bangladesh, and the Indian states of West Bengal and Kerala. Our results highlight the regional disparities and importance in considering seasonal differences in the estimation of the effect of climate change on labour productivity and occupational heat-stress.

Raman spectroscopy-based diagnostics of water deficit and salinity stresses in two accessions of peanut.

Water deficit and salinity are two major abiotic stresses that have tremendous effect on crop yield worldwide. Timely identification of these stresses can help limit associated yield loss. Confirmatory detection and identification of water deficit stress can also enable proper irrigation management. Traditionally, unmanned aerial vehicle (UAV)-based imaging and satellite-based imaging, together with visual field observation, are used for diagnostics of such stresses. However, these approaches can only detect salinity and water deficit stress at the symptomatic stage. Raman spectroscopy (RS) is a noninvasive and nondestructive technique that can identify and detect plant biotic and abiotic stress. In this study, we investigated accuracy of Raman-based diagnostics of water deficit and salinity stresses on two greenhouse-grown peanut accessions: tolerant and susceptible to water deficit. Plants were grown for 76 days prior to application of the water deficit and salinity stresses. Water deficit treatments received no irrigation for 5 days, and salinity treatments received 1.0 L of 240-mM salt water per day for the duration of 5-day sampling. Every day after the stress was imposed, plant leaves were collected and immediately analyzed by a hand-held Raman spectrometer. RS and chemometrics could identify control and stressed (either water deficit or salinity) susceptible plants with 95% and 80% accuracy just 1 day after treatment. Water deficit and salinity stressed plants could be differentiated from each other with 87% and 86% accuracy, respectively. In the tolerant accessions at the same timepoint, the identification accuracies were 66%, 65%, 67%, and 69% for control, combined stresses, water deficit, and salinity stresses, respectively. The high selectivity and specificity for presymptomatic identification of abiotic stresses in the susceptible line provide evidence for the potential of Raman-based surveillance in commercial-scale agriculture and digital farming.

Evaluation and Selection of Interspecific Lines of Groundnut (Arachis hypogaea L.) for Resistance to Leaf Spot Disease and for Yield Improvement.

Early and late leaf spot are two devastating diseases of peanut (Arachis hypogaea L.) worldwide. The development of a fertile, cross-compatible synthetic amphidiploid, TxAG-6 ([A. batizocoi × (A. cardenasii × A. diogoi)]4x), opened novel opportunities for the introgression of wild alleles for disease and pest resistance into commercial cultivars. Twenty-seven interspecific lines selected from prior evaluation of an advanced backcross population were evaluated for resistance to early and late leaf spot, and for yield in two locations in Ghana in 2006 and 2007. Several interspecific lines had early leaf spot scores significantly lower than the susceptible parent, indicating that resistance to leaf spot had been successfully introgressed and retained after three cycles of backcrossing. Time to appearance of early leaf spot symptoms was less in the introgression lines than in susceptible check cultivars, but the opposite was true for late leaf spot. Selected lines from families 43-08, 43-09, 50-04, and 60-02 had significantly reduced leaf spot scores, while lines from families 43-09, 44-10, and 63-06 had high pod yields. One line combined both resistance to leaf spot and high pod yield, and several other useful lines were also identified. Results suggest that it is possible to break linkage drag for low yield that accompanies resistance. However, results also suggest that resistance was diluted in many of the breeding lines, likely a result of the multigenic nature of resistance. Future QTL analysis may be useful to identify alleles for resistance and allow recombination and pyramiding of resistance alleles while reducing linkage drag.

Treatment of Vocal Fold Polyps with In-Office Potassium Titanyl Phosphate (KTP) Laser Ablation in Professional Singers.

Vocal fold polyp (VFP) is an exophytic gelatinous lesion with an atrophic epithelium. After behavioral and conservative management, phonomicrosurgery is the treatment of choice for VFPs with excellent outcomes in terms of lesion resolution and postoperative vocal function. Office-based potassium titanyl phosphate (KTP) laser ablation is a new treatment modality for VFPs but its efficacy for professional singers has yet to be validated. Reported is a consecutive series of six professional singers (with seven episodes of VFP) who, based on patient and provider preference, underwent in-office KTP laser ablation of VFP. Two polyps required two ablation procedures; otherwise, a single treatment was successful in resolution of VFP at a mean resolution time of 44 days. Singing voice handicap index 10 improved from a mean of 30.8 (range 4-40) to 6.0 (range 0-22). All patients resumed their professional singing careers without vocal limitations. Posttreatment videos were reviewed by three blinded fellowship trained laryngologists, who were not able to accurately predict the laterality of the polyp (52% correct, p = 0.99).

A Proof-of-Principle Study of Non-invasive Identification of Peanut Genotypes and Nematode Resistance Using Raman Spectroscopy.

Identification of peanut cultivars for distinct phenotypic or genotypic traits whether using visual characterization or laboratory analysis requires substantial expertise, time, and resources. A less subjective and more precise method is needed for identification of peanut germplasm throughout the value chain. In this proof-of-principle study, the accuracy of Raman spectroscopy (RS), a non-invasive, non-destructive technique, in peanut phenotyping and identification is explored. We show that RS can be used for highly accurate peanut phenotyping via surface scans of peanut leaves and the resulting chemometric analysis: On average 94% accuracy in identification of peanut cultivars and breeding lines was achieved. Our results also suggest that RS can be used for highly accurate determination of nematode resistance and susceptibility of those breeding lines and cultivars. Specifically, nematode-resistant peanut cultivars can be identified with 92% accuracy, whereas susceptible breeding lines were identified with 81% accuracy. Finally, RS revealed substantial differences in biochemical composition between resistant and susceptible peanut cultivars. We found that resistant cultivars exhibit substantially higher carotenoid content compared to the susceptible breeding lines. The results of this study show that RS can be used for quick, accurate, and non-invasive identification of genotype, nematode resistance, and nutrient content. Armed with this knowledge, the peanut industry can utilize Raman spectroscopy for expedited breeding to increase yields, nutrition, and maintaining purity levels of cultivars following release.

Use of Targeted Amplicon Sequencing in Peanut to Generate Allele Information on Allotetraploid Sub-Genomes.

The use of molecular markers in plant breeding has become a routine practice, but the cost per accession can be a hindrance to the routine use of Quantitative Trait Loci (QTL) identification in breeding programs. In this study, we demonstrate the use of targeted re-sequencing as a proof of concept of a cost-effective approach to retrieve highly informative allele information, as well as develop a bioinformatics strategy to capture the genome-specific information of a polyploid species. SNPs were identified from alignment of raw transcriptome reads (2 × 50 bp) to a synthetic tetraploid genome using BWA followed by a GATK pipeline. Regions containing high polymorphic SNPs in both A genome and B genomes were selected as targets for the resequencing study. Targets were amplified using multiplex PCR followed by sequencing on an Illumina HiSeq. Eighty-one percent of the SNP calls in diploids and 68% of the SNP calls in tetraploids were confirmed. These results were also confirmed by KASP validation. Based on this study, we find that targeted resequencing technologies have potential for obtaining maximum allele information in allopolyploids at reduced cost.

Raman Spectroscopy Enables Non-Invasive Identification of Peanut Genotypes and Value-Added Traits.

Identification of specific genotypes can be accomplished by visual recognition of their distinct phenotypical appearance, as well as DNA analysis. Visual identification (ID) of species is subjective and usually requires substantial taxonomic expertise. Genotyping and sequencing are destructive, time- and labor-consuming. In this study, we investigate the potential use of Raman spectroscopy (RS) as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of peanut genotypes. We show that chemometric analysis of peanut leaflet spectra provides accurate identification of different varieties. This same analysis can be used for prediction of nematode resistance and oleic-linoleic oil (O/L) ratio. Raman-based analysis of seeds provides accurate genotype identification in 95% of samples. Additionally, we present data on the identification of carbohydrates, proteins, fiber and other nutrients obtained from spectroscopic signatures of peanut seeds. These results demonstrate that RS allows for fast, accurate and non-invasive screening and selection of plants which can be used for precision breeding.

Office-Based 532-Nanometer Pulsed Potassium-Titanyl-Phosphate Laser Procedures in Laryngology.

With fiber-based lasers that may be passed via the working channel of a flexible laryngoscope, in-office laser laryngeal surgery has become possible. The potassium-titanyl-phosphate laser has several features that make it ideal for laryngeal surgery, and it is now the laser of choice for in-office management of a variety of laryngeal lesions. Its applications have expanded significantly since its introduction, with reports of new indications continuing to appear in the literature. This article provides a comprehensive review of the indications and technical details of in-office potassium-titanyl-phosphate laser laryngeal surgery, and a summary of the existing literature regarding outcomes of these procedures.

SNP genotyping reveals major QTLs for plant architectural traits between A-genome peanut wild species.

KEY MESSAGE: QTL mapping of important architectural traits was successfully applied to an A-genome diploid population using gene-specific variations. Peanut wild species are an important source of resistance to biotic and possibly abiotic stress; because these species differ from the cultigen in many traits, we have undertaken to identify QTLs for several plant architecture-related traits. In this study, we took recently identified SNPs, converted them into markers, and identified QTLs for architectural traits. SNPs from RNASeq data distinguishing two parents, A. duranensis (KSSc38901) and A. cardenasii (GKP10017), of a mapping population were identified using three references-A. duranensis V14167 genome sequence, and transcriptome sequences of A. duranensis KSSc38901 and OLin. More than 49,000 SNPs differentiated the parents, and 87.9% of the 190 SNP calls tested were validated. SNPs were then genotyped on 91 F2 lines using KASP chemistry on a Roche LightCycler 480 and a Fluidigm Biomark HD, and using SNPType chemistry on the Fluidigm Biomark HD. A linkage map was constructed having ten linkage groups, with 144 loci spanning a total map distance of 1040 cM. Comparison of the A-genome map to the A. duranensis genome sequence revealed a high degree of synteny. QTL analysis was also performed on the mapping population for important architectural traits. Fifteen definitive and 16 putative QTLs for petiole length, leaflet length and width, leaflet area, leaflet length/width ratio, main stem height, presence of flowers on the main stem, and seed mass were identified. Results demonstrate that SNPs identified from transcriptome sequencing could be converted to KASP or SNPType markers with a high success rate, and used to identify alleles with significant phenotypic effects, These could serve as information useful for introgression of alleles into cultivated peanut from wild species and have the potential to allow breeders to more easily fix these alleles using a marker-assisted backcrossing approach.

Transcriptome Sequencing of Diverse Peanut (Arachis) Wild Species and the Cultivated Species Reveals a Wealth of Untapped Genetic Variability.

To test the hypothesis that the cultivated peanut species possesses almost no molecular variability, we sequenced a diverse panel of 22 Arachis accessions representing Arachis hypogaea botanical classes, A-, B-, and K- genome diploids, a synthetic amphidiploid, and a tetraploid wild species. RNASeq was performed on pools of three tissues, and de novo assembly was performed. Realignment of individual accession reads to transcripts of the cultivar OLin identified 306,820 biallelic SNPs. Among 10 naturally occurring tetraploid accessions, 40,382 unique homozygous SNPs were identified in 14,719 contigs. In eight diploid accessions, 291,115 unique SNPs were identified in 26,320 contigs. The average SNP rate among the 10 cultivated tetraploids was 0.5, and among eight diploids was 9.2 per 1000 bp. Diversity analysis indicated grouping of diploids according to genome classification, and cultivated tetraploids by subspecies. Cluster analysis of variants indicated that sequences of B genome species were the most similar to the tetraploids, and the next closest diploid accession belonged to the A genome species. A subset of 66 SNPs selected from the dataset was validated; of 782 SNP calls, 636 (81.32%) were confirmed using an allele-specific discrimination assay. We conclude that substantial genetic variability exists among wild species. Additionally, significant but lesser variability at the molecular level occurs among accessions of the cultivated species. This survey is the first to report significant SNP level diversity among transcripts, and may explain some of the phenotypic differences observed in germplasm surveys. Understanding SNP variants in the Arachis accessions will benefit in developing markers for selection.

A model-based approach for imputing censored data in source apportionment studies.

Sources of particulate matter (PM) air pollution are generally inferred from PM chemical constituent concentrations using source apportionment models. Concentrations of PM constituents are often censored below minimum detection limits (MDL) and most source apportionment models cannot handle these censored data. Frequently, censored data are first substituted by a constant proportion of the MDL or are removed to create a truncated dataset before sources are estimated. When estimating the complete data distribution, these commonly applied methods to adjust censored data perform poorly compared with model-based imputation methods. Model-based imputation has not been used in source apportionment and may lead to better source estimation. However if the censored chemical constituents are not important for estimating sources, censoring adjustment methods may have little impact on source estimation. We focus on two source apportionment models applied in the literature and provide a comprehensive assessment of how censoring adjustment methods, including model-based imputation, impact source estimation. A review of censoring adjustment methods critically informs how censored data should be handled in these source apportionment models. In a simulation study, we demonstrated that model-based multiple imputation frequently leads to better source estimation compared with commonly used censoring adjustment methods. We estimated sources of PM in New York City and found estimated source distributions differed by censoring adjustment method. In this study, we provide guidance for adjusting censored PM constituent data in common source apportionment models, which is necessary for estimation of PM sources and their subsequent health effects.

Successful crosses between fungal-resistant wild species of Arachis (section Arachis) and Arachis hypogaea.

Peanut (Arachis hypogaea) is the fifth most produced oil crop worldwide. Besides lack of water, fungal diseases are the most limiting factors for the crop. Several species of Arachis are resistant to certain pests and diseases. This study aimed to successfully cross the A-genome with B-K-A genome wild species previously selected for fungal disease resistance, but that are still untested. We also aimed to polyplodize the amphihaploid chromosomes; cross the synthetic amphidiploids and A. hypogaea to introgress disease resistance genes into the cultivated peanut; and analyze pollen viability and morphological descriptors for all progenies and their parents. We selected 12 A-genome accessions as male parents and three B-genome species, one K-genome species, and one A-genome species as female parents. Of the 26 distinct cross combinations, 13 different interspecific AB-genome and three AA-genome hybrids were obtained. These sterile hybrids were polyploidized and five combinations produced tetraploid flowers. Next, 16 combinations were crossed between A. hypogaea and the synthetic amphidiploids, resulting in 11 different hybrid combinations. Our results confirm that it is possible to introgress resistance genes from wild species into the peanut using artificial hybridization, and that more species than previously reported can be used, thus enhancing the genetic variability in peanut genetic improvement programs.