Proximal and remote sensing for early detection and assessment of herbicide drift damage on cotton crops

The herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) is one of the most successful selective herbicides used in agriculture to control broadleaf weeds. Unfortunately, cotton crops are highly susceptible to 2,4-D, and they are often damaged by the offtarget movement of the active ingredient when sprayed as a herbicide on surrounding farms. This action, referred to as herbicide drift, affects the cotton industry every season, causing losses of millions of dollars. Although the economic repercussions on the industry are high, the traditional (visual) assessment of damage is often imprecise and inaccurate. Crop sensing tools can offer alternative and reliable methods to overcome the typical limitations of visual assessments by providing accurate estimations of crop performance. The aim of this research project was to assess the capabilities of crop sensing techniques of providing spatial and quantitative information of cotton yield after being affected by 2,4-D herbicide drift. This information is valuable to agronomic planners for evaluating their crop management strategies in order to maximise cotton production while safeguarding the environment in the affected area. The research area was located in a cotton-growing region in Jondaryan, Queensland, Australia. Two study cases and three remote/proximal sensing approaches were tested. The first study case consisted of controlled doses to simulate accidental exposure to 2,4-D, where three doses (D) and three timing of exposures (S) were examined at four different dates after the exposure (DAE): 2, 7, 14 and 28 DAE. In this case, a hyperspectral sensor and a terrestrial laser scanner (TLS) were evaluated to assess their ability to predict yield loss, dose and canopy structure variability. The second case examined the potential capabilities of satellite imagery for yield loss assessment in an uncontrolled exposure of cotton crops to 2,4-D. For this case, several multispectral (Landsat 8 Operational Land Imager - OLI) images were analysed and a comprehensive approach was developed to overcome the potential limitation of moderate resolution imagery at the field level. The controlled case revealed that hyperspectral data can be used to predict yield loss with high accuracy (R2 = 0.88) regardless of the timing of exposure and dose, and that 7 DAE and 28 DAE (RMSECV: 2.6 bales/ha; R2 = 0.88 and RMSECV: 3.2 bales/ha; R2 = 0.84, respectively) were the best times for data collection purposes. The main difference in the model performance between the best (7 DAE) and the worst (14 DAE) prediction model was the inclusion of the NIR range, as the 14 DAE was the only model with no significant wavelengths in this range. Through this case, it was possible to better understand how the internal changes of the contaminated leaves, that is photosynthesis, stomatal conductance and hormone contents, influenced their spectral response and the lint quality of the cotton. Most of the variables analysed in this study manifested a significant relationship with hyperspectral data ( value 70%) were obtained regardless of the method, D or S. However, the timing of exposure (S) resulted in being a determinant to improve the classification accuracy to more than 90%. The analysis of laser scanner-derived data provided accurate information about the canopy height and canopy volume that could be strongly correlated (r > 0.88) with yield at different times of assessment (2 DAE, 7 DAE and 14 DAE). High R2 (> 0.90) between measured and estimated canopy height validates the height values estimated from the TLS-derived data. Furthermore, the weak relationship (R2 =0.39, value > 0.05) between point density and estimated canopy volume provided an insight that the approach implemented to estimate cotton canopy height and volume overcame the reported limitations of terrestrial laser scanners in the field. The uncontrolled case (i.e. Landsat 8 imagery) tested six different dates for optimal data collection purposes. The results demonstrated that traditional vegetation indices (VI) and individual multispectral bands were incapable of predicting yield in neither affected nor unaffected cotton areas (R2 < 0.27). However, PLS-R models optimized the information provided by the multispectral bands. As a result, the R2 increased, in some cases, by more than 60%. From the PLS- model results, it was determined that one week after the exposure was the best time for the prediction of yield in affected areas (RMSEP = 1.19 bales/ha and R2 = 0.60). Satellite imagery could be then implemented to support targeted monitoring programs in 2,4-D-injured areas. The technologies implemented in this study were proven to be reliable for damage assessment after an accidental spray drift by accurately predicting yield and dose and also by estimating canopy structure variables strongly correlated with yield in 2,4-Daffected areas. These comprehensive analytical approaches also provided information on temporal windows for optimal data collection after an incident, and also on less-recommended dates for the same purpose. These methods indicated an optimal window between seven and 14 days, or more than 28 days after the exposure, for the prediction of damage. However, as soon as two days after the cotton plant was exposed, hyperspectral measurements and TLS-derived data recorded significant differences in comparison with unaffected control plants

Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data

Proximal and remote sensors have proved their effectiveness for the estimation of several biophysical and biochemical variables, including yield, in many different crops. Evaluation of their accuracy in vegetable crops is limited. This study explored the accuracy of proximal hyperspectral and satellite multispectral sensors (Sentinel-2 and WorldView-3) for the prediction of carrot root yield across three growing regions featuring different cropping configurations, seasons and soil conditions. Above ground biomass (AGB), canopy reflectance measurements and corresponding yield measures were collected from 414 sample sites in 24 fields in Western Australia (WA), Queensland (Qld) and Tasmania (Tas), Australia. The optimal sensor (hyperspectral or multispectral) was identified by the highest overall coefficient of determination between yield and different vegetation indices (VIs) whilst linear and non-linear models were tested to determine the best VIs and the impact of the spatial resolution. The optimal regression fit per region was used to extrapolate the point source measurements to all pixels in each sampled crop to produce a forecasted yield map and estimate average carrot root yield (t/ha) at the crop level. The latter were compared to commercial carrot root yield (t/ha) obtained from the growers to determine the accuracy of prediction. The measured yield varied from 17 to 113 t/ha across all crops, with forecasts of average yield achieving overall accuracies (% error) of 9.2% in WA, 10.2% in Qld and 12.7% in Tas. VIs derived from hyperspectral sensors produced poorer yield correlation coefficients (R2 < 0.1) than similar measures from the multispectral sensors (R2 < 0.57, p < 0.05). Increasing the spatial resolution from 10 to 1.2 m improved the regression performance by 69%. It is impossible to non-destructively estimate the pre-harvest spatial yield variability of root vegetables such as carrots. Hence, this method of yield forecasting offers great benefit for managing harvest logistics and forward selling decisions

Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data

Proximal and remote sensors have proved their effectiveness for the estimation of several biophysical and biochemical variables, including yield, in many different crops. Evaluation of their accuracy in vegetable crops is limited. This study explored the accuracy of proximal hyperspectral and satellite multispectral sensors (Sentinel-2 and WorldView-3) for the prediction of carrot root yield across three growing regions featuring different cropping configurations, seasons and soil conditions. Above ground biomass (AGB), canopy reflectance measurements and corresponding yield measures were collected from 414 sample sites in 24 fields in Western Australia (WA), Queensland (Qld) and Tasmania (Tas), Australia. The optimal sensor (hyperspectral or multispectral) was identified by the highest overall coefficient of determination between yield and different vegetation indices (VIs) whilst linear and non-linear models were tested to determine the best VIs and the impact of the spatial resolution. The optimal regression fit per region was used to extrapolate the point source measurements to all pixels in each sampled crop to produce a forecasted yield map and estimate average carrot root yield (t/ha) at the crop level. The latter were compared to commercial carrot root yield (t/ha) obtained from the growers to determine the accuracy of prediction. The measured yield varied from 17 to 113 t/ha across all crops, with forecasts of average yield achieving overall accuracies (% error) of 9.2% in WA, 10.2% in Qld and 12.7% in Tas. VIs derived from hyperspectral sensors produced poorer yield correlation coefficients (R2 2

Effectiveness of an intervention for improving drug prescription in primary care patients with multimorbidity and polypharmacy:Study protocol of a cluster randomized clinical trial (Multi-PAP project)

This study was funded by the Fondo de Investigaciones Sanitarias ISCIII (Grant Numbers PI15/00276, PI15/00572, PI15/00996), REDISSEC (Project Numbers RD12/0001/0012, RD16/0001/0005), and the European Regional Development Fund ("A way to build Europe").Background: Multimorbidity is associated with negative effects both on people's health and on healthcare systems. A key problem linked to multimorbidity is polypharmacy, which in turn is associated with increased risk of partly preventable adverse effects, including mortality. The Ariadne principles describe a model of care based on a thorough assessment of diseases, treatments (and potential interactions), clinical status, context and preferences of patients with multimorbidity, with the aim of prioritizing and sharing realistic treatment goals that guide an individualized management. The aim of this study is to evaluate the effectiveness of a complex intervention that implements the Ariadne principles in a population of young-old patients with multimorbidity and polypharmacy. The intervention seeks to improve the appropriateness of prescribing in primary care (PC), as measured by the medication appropriateness index (MAI) score at 6 and 12months, as compared with usual care. Methods/Design: Design:pragmatic cluster randomized clinical trial. Unit of randomization: family physician (FP). Unit of analysis: patient. Scope: PC health centres in three autonomous communities: Aragon, Madrid, and Andalusia (Spain). Population: patients aged 65-74years with multimorbidity (≥3 chronic diseases) and polypharmacy (≥5 drugs prescribed in ≥3months). Sample size: n=400 (200 per study arm). Intervention: complex intervention based on the implementation of the Ariadne principles with two components: (1) FP training and (2) FP-patient interview. Outcomes: MAI score, health services use, quality of life (Euroqol 5D-5L), pharmacotherapy and adherence to treatment (Morisky-Green, Haynes-Sackett), and clinical and socio-demographic variables. Statistical analysis: primary outcome is the difference in MAI score between T0 and T1 and corresponding 95% confidence interval. Adjustment for confounding factors will be performed by multilevel analysis. All analyses will be carried out in accordance with the intention-to-treat principle. Discussion: It is essential to provide evidence concerning interventions on PC patients with polypharmacy and multimorbidity, conducted in the context of routine clinical practice, and involving young-old patients with significant potential for preventing negative health outcomes. Trial registration: Clinicaltrials.gov, NCT02866799Publisher PDFPeer reviewe

Incident type 2 diabetes attributable to suboptimal diet in 184 countries

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.publishedVersio

Children’s and adolescents’ rising animal-source food intakes in 1990–2018 were impacted by age, region, parental education and urbanicity

Animal-source foods (ASF) provide nutrition for children and adolescents’ physical and cognitive development. Here, we use data from the Global Dietary Database and Bayesian hierarchical models to quantify global, regional and national ASF intakes between 1990 and 2018 by age group across 185 countries, representing 93% of the world’s child population. Mean ASF intake was 1.9 servings per day, representing 16% of children consuming at least three daily servings. Intake was similar between boys and girls, but higher among urban children with educated parents. Consumption varied by age from 0.6 at <1 year to 2.5 servings per day at 15–19 years. Between 1990 and 2018, mean ASF intake increased by 0.5 servings per week, with increases in all regions except sub-Saharan Africa. In 2018, total ASF consumption was highest in Russia, Brazil, Mexico and Turkey, and lowest in Uganda, India, Kenya and Bangladesh. These findings can inform policy to address malnutrition through targeted ASF consumption programmes.publishedVersio

Estudios de Caso sobre Ciencias Agropecuarias y Rurales en el siglo XXI.

Libro científico sobre estudios de casos en el medio agropecuario y ruralCon el advenimiento del siglo XXI y el avance de los procesos de globalización, el medio rural presenta diversos cambios económicos, sociales, políticos y culturales. Lo anterior significa que el campo es un objeto de estudio altamente dinámico, complejo e inasible. las ciencias agropecuarias y rurales, en la actualidad, requieren de un abordaje sistémico e interdisciplinario que den cuenta de la heterogeneidad de situaciones y contextos que enfrenta el campo mexicano. La presente obra agrupa 18 estudios de caso, que capturan algunas fotografías de las diversas problemáticas de la ruralidad mexicana, con lo cual se pretende dar cuenta tanto de los objetivos de estudio como de la perspectiva teórico metodológico desde que estos son abordados. lo anterior tiene que ver con el hecho de que las ciencias agropecuarias y rurales manifiestan un alto grado de observación empírica, motivo por el que los estudios de caso se convierten en la perspectiva metodológica idónea que permite ir y venir de la realidad a la teoría y viceversa para la construcción de objetos de estudio. En este volumen se aborda una gran diversidad de casos, que sintetizan la heterogeneidad de enfoques y perspectivas mediante las cuales los fenómenos agropecuarios y rurales han sido abordados en el Instituto de Ciencias Agropecuarias y Rurales de la Universidad Autónoma del Estado de México, en los últimos 30 años

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat