[Quantitative evaluation of a SEIR model for forecasting COVID-19 cases].

Introduction: Epidemiological models have been widely used during the COVID-19 pandemic, although performance evaluation has been limited. The objective of this work was to thoroughly evaluate a SEIR model used for the short-term (1 to 3 weeks) prediction of cases, quantifying its actual past performance, and its potential performance by optimizing the model parameters.

Methods: Daily case forecasts were obtained for the first wave of cases (July 31, 2020 to March 11, 2021) in the district of General Pueyrredón (Argentina), quantifying the model performance in terms of uncertainty, inaccuracy and imprecision.

Open Science Drone Toolkit: Open source hardware and software for aerial data capture.

Despite the increased access to scientific publications and data as a result of open science initiatives, access to scientific tools remains limited. Uncrewed aerial vehicles (UAVs, or drones) can be a powerful tool for research in disciplines such as agriculture and environmental sciences, but their use in research is currently dominated by proprietary, closed source tools. The objective of this work was to collect, curate, organize and test a set of open source tools for aerial data capture for research purposes.

IRimage: open source software for processing images from infrared thermal cameras.

IRimage aims at increasing throughput, accuracy and reproducibility of results obtained from thermal images, especially those produced with affordable, consumer-oriented cameras. IRimage processes thermal images, extracting raw data and calculating temperature values with an open and fully documented algorithm, making this data available for further processing using image analysis software. It also allows the making of reproducible measurements of the temperature of objects in a series of images, and produce visual outputs (images and videos) suitable for scientific reporting.

Assessing the Efficiency of Phenotyping Early Traits in a Greenhouse Automated Platform for Predicting Drought Tolerance of Soybean in the Field.

Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes.

Biomass Allocation Patterns Are Linked to Genotypic Differences in Whole-Plant Transpiration Efficiency in Sunflower.

Increased transpiration efficiency (the ratio of biomass to water transpired, TE) could lead to increased drought tolerance under some water deficit scenarios. Intrinsic (i.e.

GlyPh: a low-cost platform for phenotyping plant growth and water use.

Breeding drought-tolerant crop varieties with higher water use efficiency could help maintain food supply to a growing population and save valuable water resources. Fast and accurate phenotyping is currently a bottleneck in the process towards attaining this goal, as available plant phenotyping platforms have an excessive cost for many research institutes or breeding companies. Here we describe a simple and low-cost, automatic platform for high-throughput measurement of plant water use and growth and present its utilisation to assess the drought tolerance of two soybean genotypes.

Genetic variability for leaf growth rate and duration under water deficit in sunflower: analysis of responses at cell, organ, and plant level.

Plants under water deficit reduce leaf growth, thereby reducing transpiration rate at the expense of reduced photosynthesis. The objective of this work was to analyse the response of leaf growth to water deficit in several sunflower genotypes in order to identify and quantitatively describe sources of genetic variability for this trait that could be used to develop crop varieties adapted to specific scenarios. The genetic variability of the response of leaf growth to water deficit was assessed among 18 sunflower (Helianthus annuus L.

Rewatering plants after a long water-deficit treatment reveals that leaf epidermal cells retain their ability to expand after the leaf has apparently reached its final size.

Background And Aims: Leaves expand during a given period of time until they reach their final size and form, which is called determinate growth. Duration of leaf expansion is stable when expressed in thermal-time and in the absence of stress, and consequently it is often proposed that it is controlled by a robust programme at the plant scale. The usual hypothesis is that growth cessation occurs when cell expansion becomes limited by an irreversible tightening of cell wall, and that leaf size is fixed once cell expansion ceases.