'Sugar from Space': Using Satellite Imagery to Predict Cane Yield and Variability

Satellite imagery has been demonstrated to be an effective technology for producing accurate pre-harvest estimates in many agricultural crops. For Australian sugarcane, yield forecasting models have been developed from a single date SPOT satellite image acquired around peak crop growth. However, a failure to acquire a SPOT image at this critical growth stage, from continued cloud cover or from competition for the satellite, can prevent an image being captured and therefore a forecast being made for that season. In order to reduce the reliance on a single image capture and to improve the accuracies of the forecasts themselves, time series yield prediction models have been developed for eight sugarcane growing regions using multiple years of free Landsat satellite images. In addition to the forecasting of average regional yield, an automated computational and programming procedure enabling the derivation of crop vigour variability (GNDVI) maps from the freely available Sentinel 2 satellite imagery was developed. These maps, produced for 15 sugarcane growing regions during the 2017 growing season, identify both variations in crop vigour across regions and within every individual crop. These outputs were made available to collaborating mills within each growing region. This paper presents the accuracies achieved from the time series yield forecasting models versus actual 2017 yields for the respective regions, as well as provides an example of the derived mapping outputs

Gifting cultures and artisanal guilds in sixteenth-and early seventeenth-century London

This article reconsiders the gift within London's sixteenth- and early seventeenth-century livery companies. Previous research into guild gift-giving cultures has focused exclusively upon substantial bequests of money and property by mercantile elites to the ‘great twelve’ livery companies. Through charitable gifts, citizens established godly reputations and legacies, perpetuated through the guild institution. It is argued here that a rich culture of material gift-giving, hitherto overlooked by historians, also thrived within London's craft guilds. Drawing on company gift books, inventories, and material survivals from guild collections, this article examines typologies of donors and gifts, the anticipated ‘returns’ on the gift by the recipient company, and the ideal spatial and temporal contexts for gift-giving. This material approach reveals that master artisans negotiated civic status, authority, and memory through the presentation of a wide range of gifted artefacts for display and ritual use in London's livery halls. Moreover, this culture of gift-giving was so deep-rooted and significant that it survived the Reformation upheavals largely intact. Finally, the embellishment of rituals of gifting, and the synchronization of gifting and feasting rites from the second half of the sixteenth century, are further evidence for the resurgence of English civic culture in this era

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.This work was supported by the Medical Research Council (G0901310) and the Wellcome Trust (grants 085475/B/08/Z, 085475/Z/08/Z). This study was supported by the NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust and University College London and by the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust at King’s College London. Further support to EB: Mental Health Research UK’s John Grace QC award, BMA Margaret Temple grants 2016 and 2006, MRC—Korean Health Industry Development Institute Partnering Award (MC_PC_16014), MRC New Investigator Award and a MRC Centenary Award (G0901310), National Institute of Health Research UK post-doctoral fellowship, the Psychiatry Research Trust, the Schizophrenia Research Fund, the Brain and Behaviour Research foundation’s NARSAD Young Investigator Awards 2005, 2008, Wellcome Trust Research Training Fellowship, the NIHR Biomedical Research Centre at UCLH, and the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and Institute of Psychiatry King’s College London. Further support to co-authors: The Brain and Behaviour Research foundation’s (NARSAD’s) Young Investigator Award (Grant 22604, awarded to CI). The BMA Margaret Temple grant 2016 to JT. A 2014 European Research Council Marie Curie award to A Díez-Revuelta. HI has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 747429. A Medical Research Council doctoral studentship to JH-S, IA-Z and AB. A Mental Health Research UK studentship to RM. VB is supported by a Wellcome Trust Seed Award in Science (200589/Z/16/Z). FWO Senior Clinical Fellowship to RvW. The infrastructure for the GROUP consortium is funded through the Geestkracht programme of the Dutch Health Research Council (ZON-MW, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly, Janssen Cilag) and universities and mental health care organisations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Centre and the mental health institutions: GGZ Ingeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord Holland Noord. Groningen: University Medical Centre Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia psycho-medical centre The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGZ Eindhoven en De Kempen, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh voor Geestelijke Gezondheid, Mondriaan, Virenze riagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-Jozef Kortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Centre Utrecht and the mental health institutions Altrecht, GGZ Centraal and Delta). The Santander cohort was supported by Instituto de Salud Carlos III (PI020499, PI050427, PI060507), SENY Fundació (CI 2005-0308007), Fundacion Ramón Areces and Fundacion Marqués de Valdecilla (API07/011, API10/13). We thank Valdecilla Biobank for providing the biological PAFIP samples and associated data included in this study and for its help in the technical execution of this work; we also thank IDIVAL Neuroimaging Unit for its help in the acquisition and processing of imaging PAFIP data

Association of genetic susceptibility variants for type 2 diabetes with breast cancer risk in women of European ancestry.

Purpose: Type 2 diabetes (T2D) has been reported to be associated with an elevated risk of breast cancer. It is unclear, however, whether this association is due to shared genetic factors. Methods: We constructed a genetic risk score (GRS) using risk variants from 33 known independent T2D susceptibility loci and evaluated its relation to breast cancer risk using the data from two consortia, including 62,328 breast cancer patients and 83,817 controls of European ancestry. Unconditional logistic regression models were used to derive adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) to measure the association of breast cancer risk with T2D GRS or T2D-associated genetic risk variants. Meta-analyses were conducted to obtain summary ORs across all studies. Results: The T2D GRS was not found to be associated with breast cancer risk, overall, by menopausal status, or for estrogen receptor positive or negative breast cancer. Three T2D associated risk variants were individually associated with breast cancer risk after adjustment for multiple comparisons using the Bonferroni method (at p < 0.001), rs9939609 (FTO) (OR 0.94, 95 % CI = 0.92–0.95, p = 4.13E−13), rs7903146 (TCF7L2) (OR 1.04, 95 % CI = 1.02–1.06, p = 1.26E−05), and rs8042680 (PRC1) (OR 0.97, 95 % CI = 0.95–0.99, p = 8.05E−04). Conclusions: We have shown that several genetic risk variants were associated with the risk of both T2D and breast cancer. However, overall genetic susceptibility to T2D may not be related to breast cancer risk

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

BHPR research: qualitative1. Complex reasoning determines patients' perception of outcome following foot surgery in rheumatoid arhtritis

Background: Foot surgery is common in patients with RA but research into surgical outcomes is limited and conceptually flawed as current outcome measures lack face validity: to date no one has asked patients what is important to them. This study aimed to determine which factors are important to patients when evaluating the success of foot surgery in RA Methods: Semi structured interviews of RA patients who had undergone foot surgery were conducted and transcribed verbatim. Thematic analysis of interviews was conducted to explore issues that were important to patients. Results: 11 RA patients (9 ♂, mean age 59, dis dur = 22yrs, mean of 3 yrs post op) with mixed experiences of foot surgery were interviewed. Patients interpreted outcome in respect to a multitude of factors, frequently positive change in one aspect contrasted with negative opinions about another. Overall, four major themes emerged. Function: Functional ability & participation in valued activities were very important to patients. Walking ability was a key concern but patients interpreted levels of activity in light of other aspects of their disease, reflecting on change in functional ability more than overall level. Positive feelings of improved mobility were often moderated by negative self perception ("I mean, I still walk like a waddling duck”). Appearance: Appearance was important to almost all patients but perhaps the most complex theme of all. Physical appearance, foot shape, and footwear were closely interlinked, yet patients saw these as distinct separate concepts. Patients need to legitimize these feelings was clear and they frequently entered into a defensive repertoire ("it's not cosmetic surgery; it's something that's more important than that, you know?”). Clinician opinion: Surgeons' post operative evaluation of the procedure was very influential. The impact of this appraisal continued to affect patients' lasting impression irrespective of how the outcome compared to their initial goals ("when he'd done it ... he said that hasn't worked as good as he'd wanted to ... but the pain has gone”). Pain: Whilst pain was important to almost all patients, it appeared to be less important than the other themes. Pain was predominately raised when it influenced other themes, such as function; many still felt the need to legitimize their foot pain in order for health professionals to take it seriously ("in the end I went to my GP because it had happened a few times and I went to an orthopaedic surgeon who was quite dismissive of it, it was like what are you complaining about”). Conclusions: Patients interpret the outcome of foot surgery using a multitude of interrelated factors, particularly functional ability, appearance and surgeons' appraisal of the procedure. While pain was often noted, this appeared less important than other factors in the overall outcome of the surgery. Future research into foot surgery should incorporate the complexity of how patients determine their outcome Disclosure statement: All authors have declared no conflicts of interes

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana): A Case Study in Bundaberg, Australia

Accurate pre-harvest estimation of avocado (Persea americana cv. Haas) yield offers a range of benefits to industry and growers. Currently there is no commercial yield monitor available for avocado tree crops and the manual count method used for yield forecasting can be highly inaccurate. Remote sensing using satellite imagery offers a potential means to achieve accurate pre-harvest yield forecasting. This study evaluated the accuracies of high resolution WorldView (WV) 2 and 3 satellite imagery and targeted field sampling for the pre-harvest prediction of total fruit weight (kg·tree−1) and average fruit size (g) and for mapping the spatial distribution of these yield parameters across the orchard block. WV 2 satellite imagery was acquired over two avocado orchards during 2014, and WV3 imagery was acquired in 2016 and 2017 over these same two orchards plus an additional three orchards. Sample trees representing high, medium and low vigour zones were selected from normalised difference vegetation index (NDVI) derived from the WV images and sampled for total fruit weight (kg·tree−1) and average fruit size (g) per tree. For each sample tree, spectral reflectance data was extracted from the eight band multispectral WV imagery and 18 vegetation indices (VIs) derived. Principal component analysis (PCA) and non-linear regression analysis was applied to each of the derived VIs to determine the index with the strongest relationship to the measured total fruit weight and average fruit size. For all trees measured over the three year period (2014, 2016, and 2017) a consistent positive relationship was identified between the VI using near infrared band one and the red edge band (RENDVI1) to both total fruit weight (kg·tree−1) (R2 = 0.45, 0.28, and 0.29 respectively) and average fruit size (g) (R2 = 0.56, 0.37, and 0.29 respectively) across all orchard blocks. Separate analysis of each orchard block produced higher R2 values as well as identifying different optimal VIs for each orchard block and year. This suggests orchard location and growing season are influencing the relationship of spectral reflectance to total fruit weight and average fruit size. Classified maps of avocado yield (kg·tree−1) and average fruit size per tree (g) were produced using the relationships developed for each orchard block. Using the relationships derived between the measured yield parameters and the optimal VIs, total fruit yield (kg) was calculated for each of the five sampled blocks for the 2016 and 2017 seasons and compared to actual yield at time of harvest and pre-season grower estimates. Prediction accuracies achieved for each block far exceeded those provided by the grower estimates

Multi-temporal landsat algorithms for the yield prediction of sugarcane crops in Australia

Accurate with-in season yield prediction is important for the Australian sugarcane industry as it supports crop management and decision making processes, including those associated with harvest scheduling, storage, milling, and forward selling. In a recent study, a quadratic model was developed from multi-temporal Landsat imagery (30 m spatial resolution) acquired between 2001-2014 (15th November to 31st July) for the prediction of sugarcane yield grown in the Bundaberg region of Queensland, Australia. The resultant high accuracy of prediction achieved from the Bundaberg model for the 2015 and 2016 seasons inspired the development of similar models for the Tully and Mackay growing regions. As with the Bundaberg model, historical Landsat imagery was acquired over a 12 year (Tully) and 10 year (Mackay) period with the capture window again specified to be between 1st November to 30th June to coincide with the sugarcane growing season. All Landsat images were downloaded and processed using Python programing to automate image processing and data extraction. This allowed the model to be applied rapidly over large areas. For each region, the average green normalized difference vegetation index (GNDVI) for all sugarcane crops was extracted from each image and overlayed onto one time scale 1st November to 30th June. Using the quadratic model derived from each regional data set, the maximum GNDVI achieved for each season was calculated and regressed against the corresponding annual average regional sugarcane yield producing strong correlation for both Tully (R2 = 0.89 and RMSE = 5.5 t/ha) and Mackay (R2 = 0.63 and RMSE = 5.3 t/ha). Moreover, the establishment of an annual crop growth profile from each quadratic model has enabled a benchmark of historic crop development to be derived. Any deviation of future crops from this benchmark can be used as an indicator of widespread abiotic or biotic constraints. As well as regional forecasts, the yield algorithms can also be applied at the pixel level to allow individual yield maps to be derived and delivered near real time to all Australian growers and millers