Machine learning for detection and prediction of crop diseases and pests: A comprehensive survey

Considering the population growth rate of recent years, a doubling of the current worldwide crop productivity is expected to be needed by 2050. Pests and diseases are a major obstacle to achieving this productivity outcome. Therefore, it is very important to develop efficient methods for the automatic detection, identification, and prediction of pests and diseases in agricultural crops. To perform such automation, Machine Learning (ML) techniques can be used to derive knowledge and relationships from the data that is being worked on. This paper presents a literature review on ML techniques used in the agricultural sector, focusing on the tasks of classification, detection, and prediction of diseases and pests, with an emphasis on tomato crops. This survey aims to contribute to the development of smart farming and precision agriculture by promoting the development of techniques that will allow farmers to decrease the use of pesticides and chemicals while preserving and improving their crop quality and production.info:eu-repo/semantics/publishedVersio

Insect detection in sticky trap images of tomato crops using machine learning

As climate change, biodiversity loss, and biological invaders are all on the rise, the significance of conservation and pest management initiatives cannot be stressed. Insect traps are frequently used in projects to discover and monitor insect populations, assign management and conservation strategies, and assess the effectiveness of treatment. This paper assesses the application of YOLOv5 for detecting insects in yellow sticky traps using images collected from insect traps in Portuguese tomato plantations, acquired under open field conditions. Furthermore, a sliding window approach was used to minimize insect detection duplicates in a non-complex way. This article also contributes to event forecasting in agriculture fields, such as diseases and pests outbreak, by obtaining insect related metrics that can be further analyzed and combined with other data extracted from the crop fields, contributing to smart farming and precision agriculture. The proposed method achieved good results when compared to related works, reaching 94.4% for mAP_0.5, with a precision and recall of 88% and 91%, respectively, using YOLOv5x.info:eu-repo/semantics/publishedVersio

DNA-based approaches for dairy products authentication: A review and perspectives

Background Food fraud has become an increasingly worldwide problem mainly driven by rapid innovation in the food sector and constantly changing consumer's choices. This led to an increased necessity to improve/establish reliable authentication processes, resulting in the replacement of protein-based techniques for dairy products authentication by higher sensitive and reproducible DNA-based methods. Most used molecular methods for dairy products authentication include PCR, Real-time PCR, multiplex PCR, and PCR-RFLP. Despite the several molecular methods available for species/breeds differentiation in dairy products, there is a need for the development of more efficient and reliable molecular tools. Scope and approach In this review, traditional and more recent DNA-based methods for dairy products authentication are discussed and analysed. Moreover, the increasingly important role of bioinformatic tools for analysis of large amount of data and for the development of DNA markers is also discussed. Key findings and conclusions DNA quality is one of the major factors affecting molecular-based dairy products authentication, which can be influenced by the manufacturing process, extraction method employed, chemical composition of the food matrix, among others. PCR-based methods continue to be the most important and successfully used for dairy products authentication. The DNA markers chosen for species/breed detection are an important factor for PCR success. Although there are several molecular methods for the detection of adulterant species, there is still an unmet demand for methods to detect adulterant breeds. Available public databases and bioinformatics revolutionized the analysis of large amount of data and will be pivotal for the development of effective DNA markers.This work was supported by the ProDOP Serra da Estrela (PDR2020-101-032096) funded by PDR2020 - Programa de Desenvolvimento Rural 2014–2020, Portugal 2020, European Agricultural Fund For Rural Development (EAFRD), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 and the MIT-Portugal Program (Ph.D. Grant PD/BD/128247/2016 to JTC).info:eu-repo/semantics/publishedVersio

SAMplus: adaptive optics at optical wavelengths for SOAR

Adaptive Optics (AO) is an innovative technique that substantially improves the optical performance of ground-based telescopes. The SOAR Adaptive Module (SAM) is a laser-assisted AO instrument, designed to compensate ground-layer atmospheric turbulence in near-IR and visible wavelengths over a large Field of View. Here we detail our proposal to upgrade SAM, dubbed SAMplus, that is focused on enhancing its performance in visible wavelengths and increasing the instrument reliability. As an illustration, for a seeing of 0.62 arcsec at 500 nm and a typical turbulence profile, current SAM improves the PSF FWHM to 0.40 arcsec, and with the upgrade we expect to deliver images with a FWHM of $\approx0.34$ arcsec -- up to 0.23 arcsec FWHM PSF under good seeing conditions. Such capabilities will be fully integrated with the latest SAM instruments, putting SOAR in an unique position as observatory facility.Comment: To appear in Proc. SPIE 10703 (Ground-based and Airborne Instrumentation for Astronomy VII; SPIEastro18

An open and parallel multiresolution framework using block-based adaptive grids

A numerical approach for solving evolutionary partial differential equations in two and three space dimensions on block-based adaptive grids is presented. The numerical discretization is based on high-order, central finite-differences and explicit time integration. Grid refinement and coarsening are triggered by multiresolution analysis, i.e. thresholding of wavelet coefficients, which allow controlling the precision of the adaptive approximation of the solution with respect to uniform grid computations. The implementation of the scheme is fully parallel using MPI with a hybrid data structure. Load balancing relies on space filling curves techniques. Validation tests for 2D advection equations allow to assess the precision and performance of the developed code. Computations of the compressible Navier-Stokes equations for a temporally developing 2D mixing layer illustrate the properties of the code for nonlinear multi-scale problems. The code is open source

Biotechnological production of xylitol: engineering industrial Saccharomyces cerevisiae for valorization of lignocellulosic biomass

The use of renewable biomass, such as lignocellulosic materials, for the production of biofuels and chemicals within a biorefinery scheme contributes to achieve a sustainable development. Xylitol has been identified as one of the top 12 value added chemicals to be obtained from biomass, and can be produced from hemicellulose-derived xylose through biotechnological processes [1]. In this work, xylitol was produced from xylose (using glucose as co-substrate for co-factor regeneration) in batch fermentations by the industrial Saccharomyces cerevisiae PE-2 strain (over)expressing (1) a wild type xylose reductase from Pichia spititis (XR); (2) a NADH-preferable xylose reductase mutant (mut-XR) from Pichia spititis and (3) the endogenous GRE3 gene which encodes for an unspecific aldose reductase (AR). Maximum yield (0.98 g g-1) was obtained by the strain overexpressing the GRE3 gene. Moreover, the recombinant strain PE-2-GRE3 showed significantly higher xylitol productivity than the laboratory strain, CENPK.113-5D overexpressing the same gene. This strain (PE-2-GRE3) was selected for bioconversion of 160 g L-1 of xylose in a fed-batch fermentation, which resulted in 149 g L-1 of xylitol concentration with a productivity of 1.2 g L-1 h-1. These results open new perspectives and opportunities for the valorisation of hemicellulosic hydrolysates through the production of xylitol within a biorefinery concept.info:eu-repo/semantics/publishedVersio

Integrated versus non-integrated perspectives of auditors concerning the new ISO 9001 revision

The process of integration of management systems is being unfolded by a great deal of companies nowadays. A crucial feature of it relates with the audit function and the integrated perceptions of the auditors. This issue is of utmost importance if one takes into account the remarkable effort developed by ISO in the last revisions (2015) of the ISO 9001 and ISO 14001 standards aiming at the standards integration by adopting a common high level structure, identical core context, and common terms and common definitions. The available drafts of the new ISO 45001 standard suggest the same effort. This paper aims, within a global research study on ISO 9001:2015, to report the integrated versus non-integrated perspectives of auditors concerning the new ISO 9001 revision based on the results from a survey conducted among IRCA auditors. It is intended specifically to assess if the perceptions from the auditors holding several certifications are different of those from the auditors that hold solely the QMS certification. Results suggest that the auditors holding several certifications foreseen more benefits from this new revision, i.e., auditors with a wider integrated perspective rate systematically higher the different dimensions assessed in this survey.The authors would like to thank to all the responding auditors for their great collaboration and will pursue this study by applying more powerful statistical tools and adding a time perspective by replicating the survey in the future. This study had the financial support of FCT-Fundacao para a Ciencia e Tecnologia of Portugal under the project UID/CEC/00319/2013. Pedro Domingues is supported by FCT Post-Doc Grant Reference SFRH/BPD/103322/2014.info:eu-repo/semantics/publishedVersio

Integrated approach for selecting efficient Saccharomyces cerevisiae for industrial lignocellulosic fermentations: importance of yeast chassis linked to process conditions

In this work, four robust yeast chassis isolated from industrial environments were engineered with the same xylose metabolic pathway. The recombinant strains were physiologically characterized in synthetic xylose and xylose-glucose medium, on non-detoxified hemicellulosic hydrolysates of fast-growing hardwoods (Eucalyptus and Paulownia) and agricultural residues (corn cob and wheat straw) and on Eucalyptus hydrolysate at different temperatures. Results show that the co-consumption of xylose-glucose was dependent on the yeast background. Moreover, heterogeneous results were obtained among different hydrolysates and temperatures for each individual strain pointing to the importance of designing from the very beginning a tailor-made yeast considering the specific raw material and process.The authors acknowledge the financial support from the Strategic Project of UID/BIO/04469/2013 CEB Unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 – Programa Operacional Regional do Norte

Multi-feedstock biorefinery concept: Valorization of winery wastes by engineered yeast

The wine industry produces significant amounts of by-products and residues that are not properly managed, posing an environmental problem. Grape must surplus, vine shoots, and wine lees have the potential to be used as renewable resources for the production of energy and chemicals. Metabolic engineering efforts have established Saccharomyces cerevisiae as an efficient microbial cell factory for biorefineries. Current biorefineries designed for producing multiple products often rely on just one feedstock, but the bioeconomy would clearly benefit if these biorefineries could efficiently convert multiple feedstocks. Moreover, to reduce the environmental impact of fossil fuel consumption and maximize production economics, a biorefinery should be capable to supplement the manufacture of biofuel with the production of high-value products. This study proposes an integrated approach for the valorization of diverse wastes resulting from winemaking processes through the biosynthesis of xylitol and ethanol. Using genetically modified S. cerevisiae strains, the xylose-rich hemicellulosic fraction of hydrothermally pretreated vine shoots was converted into xylitol, and the cellulosic fraction was used to produce bioethanol. In addition, grape must, enriched in sugars, was efficiently used as a low-cost source for yeast propagation. The production of xylitol was optimized, in a Simultaneous Saccharification and Fermentation process configuration, by adjusting the inoculum size and enzyme loading. Furthermore, a yeast strain displaying cellulases in the cell surface was applied for the production of bioethanol from the glucan-rich cellulosic. With the addition of grape must and/or wine lees, high ethanol concentrations were reached, which are crucial for the economic feasibility of distillation. This integrated multi-feedstock valorization provides a synergistic alternative for converting a range of winery wastes and by-products into biofuel and an added-value chemical while decreasing waste released to the environment.info:eu-repo/semantics/publishedVersio

Xylose fermentation efficiency of industrial Saccharomyces cerevisiae yeast with separate or combined xylose reductase/xylitol dehydrogenase and xylose isomerase pathways

Xylose isomerase (XI) and xylose reductase/xylitol dehydrogenase (XR/XDH) pathways have been extensively used to confer xylose assimilation capacity to Saccharomyces cerevisiae and tackle one of the major bottlenecks in the attainment of economically viable lignocellulosic ethanol production. Nevertheless, there is a lack of studies comparing the efficiency of those pathways both separately and combined. In this work, the XI and/or XR/XDH pathways were introduced into two robust industrial S. cerevisiae strains, evaluated in synthetic media and corn cob hemicellulosic hydrolysate and the results were correlated with the differential enzyme activities found in the xylose-pathway engineered strains.This study was supported by the Portuguese Foundation for Science and Technology (FCT, Portugal) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), the MIT-Portugal Program (Ph.D. Grant PD/BD/128247/2016 to Joana T. Cunha), the BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte, the MultiBiorefinery project (POCI-01–0145FEDER-016403) and the Biomass and Bioenergy Research Infrastructure (PINFRA/22059/2016).info:eu-repo/semantics/publishedVersio