Factors influencing the airborne sporangia concentration of Phytophthora infestans and its relationship with potato disease severity

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGForecasting systems are widely used to predict the application of fungicides for managing late blight. However, airborne inoculum has rarely been included in these forecasting systems. Monitoring the sporangia in crop environments may offer an opportunity to improve late blight forecast systems by integrating pathogen pressure. Hence, this experiment aiming to analyze relationships between weather based risk systems and sporangia levels in the atmosphere of potato crops. The experiments were conducted during two growing seasons in a potato field. During the study, the concentration of Phytophthora infestans in the air, the weather conditions, the phenology of cultivars and r-AUPDC during the crop cycle were recorded. The weather-based risk of late blight was estimated using infection pressure (IP) and the daily risk value (DRV) based on hourly relative humidity (RH) and temperature (T). The effect of weather parameters on sporangia levels was analyzed. IP and DRV showed a strong positive correlation with sporangia concentration, standing out the pronounced effect of RH on the sporangia levels. Analysis of the hourly sporangia concentration within a day showed an increase in the sporangia concentration from 9 h to 18 h. This increase in sporangia was linked to an increase in T, spore release, and a decrease in RH. Our results identified a T of 10 ◦C and RH of 80% as the minimum threshold for significant sporangia concentration in the air. However, maximum sporangia level was found in the air at 88% (average relative humidity) and 17 ◦C (average temperature). Finally, the effect of weekly P. infestans sporangia was observed on cultivars with different susceptibility to late blight.Ministerio de Educación, Cultura y Deporte | Ref. FPU 17/0026

Importance of meteorological parameters and airborne conidia to predict risk of alternaria on a potato crop ambient using machine learning algorithms

Secondary infections of early blight during potato crop season are conditioned by aerial inoculum. However, although aerobiological studies have focused on understanding the key factors that influence the spore concentration in the air, less work has been carried out to predict when critical concentrations of conidia occur. Therefore, the goals of this study were to understand the key weather variables that affect the hourly and daily conidia dispersal of Alternaria solani and A. alternata in a potato field, and to use these weather factors in different machine learning (ML) algorithms to predict the daily conidia levels. This study showed that conidia per hour in a day is influenced by the weather conditions that characterize the hour, but not the hour of the day. Specifically, the relative humidity and solar radiation were the most relevant weather parameters influencing the conidia concentration in the air and both in a linear model explained 98% of the variation of this concentration per hour. Moreover, the dew point temperature three days before was the weather variable with the strongest effect on conidia per day. An improved prediction of Alternaria conidia level was achieved via ML algorithms when the conidia of previous days is considered in the analysis. Among the ML algorithms applied, the CART model with an accuracy of 86% were the best to predict daily conidia level.Ministerio de Educación, Cultura y Deportes | Ref. FPU 17/0026

Rapid estimation of potato quality parameters by a portable near-infrared spectroscopy device

The aim of the present work was to determine the main quality parameters on tuber potato using a portable near-infrared spectroscopy device (MicroNIR). Potato tubers protected by the Protected Geographical Indication (PGI “Patata de Galicia”, Spain) were analyzed both using chemical methods of reference and also using the NIR methodology for the determination of important parameters for tuber commercialization, such as dry matter and reducing sugars. MicroNIR technology allows for the attainment/estimation of dry matter and reducing sugars in the warehouses by directly measuring the tubers without a chemical treatment and destruction of samples. The principal component analysis and modified partial least squares regression method were used to develop the NIR calibration model. The best determination coefficients obtained for dry matter and reducing sugars were of 0.72 and 0.55, respectively, and with acceptable standard errors of cross-validation. Near-infrared spectroscopy was established as an effective tool to obtain prediction equations of these potato quality parameters. At the same time, the efficiency of portable devices for taking instantaneous measurements of crucial quality parameters is useful for potato processors.Xunta de Galicia | Ref. FEADER 2017/045BMinisterio de Educación, Cultura y Deporte | Ref. FPU 17/0026

Changes in the morphological characteristics of potato plants attributed to seasonal variability

The development of a potato crop differs according to the environmental conditions and growing season of an area. Periods of high temperatures and drought have been frequent in recent years, and this has affected crops worldwide. The effect of meteorological factors on the plant morphology of potato cultivars growing in A Limia was analyzed for three consecutive years. The crop cycle with the highest temperatures and least accumulated rainfall (2016) showed plants with a higher number of leaflets, which were shorter in length. The crop cycle (2014) with a lower temperature and more rainfall had the tallest plants, the highest degree of flowering, fewer pairs of leaflets and the highest length of the floral peduncle. Kennebec and Fontane were the varieties that showed the least variability in morphological characteristics during the seasons analyzed. Considering the meteorological and morphological data, a principal component analysis was carried out, which explained 80.1% of the variance of the data. Spearman rank correlations showed higher significant coefficients between the temperature and foliar characteristics. The leaf size of plants was estimated using a multiple linear regression analysis, which included the mean temperature, explaining 64% of the variability of the data.Xunta de Galicia | Ref. 2014/2020-FEADE

Describing the pollen content in the gastrointestinal tract of Vespa velutina larvae

Vespa velutina is an invasive species that exhibits flexible social behavior, which may have contributed to its introduction in several European countries. It is important to understand its behavior in order to combat the effects of its introduction in different areas. This implies knowing the resources that it uses during its biological cycle. Hornets require protein resources taken from insects and organic matter as well as carbohydrates as an energy source to fly and also to forage for food and nest-building materials. The gastrointestinal tract of adults and larvae contains a wide variety of pollen types. The identification of this pollen in larvae collected from nests could offer information about the plant species that V. velutina visits as a foraging place. The main objective of this research was to study the pollen content in the gastrointestinal tract of larvae. Patterns of pollen content and pollen diversity were established according to the nest type, altitude, season, and location in the nest comb. The abundance of pollen types such as Eucalyptus, Castanea, Foeniculum vulgare, Hedera helix, Taraxacum officinale, Echium, or Cytisus pollen type stands out in many of the samples.Simple Summary: The yellow-legged hornet is an invasive species from southeast Asia that has turned the European beekeeping sector upside down. The spread of this species has been advancing in recent years, and today, several European countries are threatened by Vespa velutina. The need to study its behavior is urgent given the increasingly evident economic and environmental impacts. In this regard, there is little information about the feeding habits and the resources it uses during the life cycle. Like other Hymenoptera, hornets require carbohydrates and proteins as their primary nutrients. Sugary secretions such as floral nectar, honeydew, or fruit juices are the main sources of carbohydrates but the protein intake is provided by the consumption of a diverse diet of insects such as the honey bee. There is scarce information on the presence of pollen grains in the gastrointestinal content of larvae other than secondary contamination from hunting. This content could represent the surrounding flora of its habitat that is used as a resource. Therefore, the objective of this study was to describe the main pollen types present in the gastrointestinal system of larvae taken from V. velutina nests.Fundación Centro de Estudos Eurorrexionais Galicia - Norte de Portugal | Ref. EAPA_800/2018-Atlantic-POSitiveXunta de Galicia | Ref. ED481D-2022-02

Estimation of the risk of early blight disease during the vegetative development of the potato crop and its storage

El plan de trabajo incluye las siguientes actividades: - Seguimiento fenológico y de la sintomatología de la enfermedad de tizón temprano durante el ciclo de cultivo de la patata. - Control aerobiológico de la presencia de inóculo inicial de Alternaria en la atmósfera del campo de cultivo. - Evaluación de diferentes modelos de predicción de riesgo del tizón temprano y su posterior validación para las condiciones climáticas de A Limia. - Ajuste de los modelos de predicción para Alternaria con el objetivo de minimizar el uso de productos fitosanitarios de cara a una agricultura más sostenible. - Aplicación de técnicas multivariantes para el tratamiento de los datos meteorológicos, fenológicos y aerobiológicos. -Evaluación de la calidad del tubérculo durante su almacenaje y optimización de métodos de conservación. El estudio se realizará en A Limia, comarca pionera en Galicia en la comercialización y distribución de la patata. Año 2018 El trabajo se iniciará con la selección de parcelas para el seguimiento en campo del patógeno de la patata y de las naves de almacenamiento. El plan de trabajo incluye: Registro de las condiciones meteorológicas del cultivo. Registro de la progresión del ciclo fenológico de las plantas de patata. Estudio aerobiológico del ambiente del cultivo en la parcela seleccionada. Seguimiento de los tubérculos en las condiciones de conservación en el almacén. Tareas formativas Formación en aspectos relacionados con la morfología y fenología de las variedades. Formación de NIR. Año 2019 Registro de las condiciones meteorológicas del cultivo. Registro de la progresión del ciclo fenológico de las plantas de patata. Estudio aerobiológico del ambiente del cultivo en la parcela seleccionada. Seguimiento de los tubérculos en las condiciones de conservación en el almacén. Informatización de los datos obtenidos en el ciclo de cultivo anterior y su tratamiento. Selección de modelos de pronóstico y testaje. Informe de resultados. Tareas formativas Curso de introducción al análisis estadístico multivariante. Curso de Sistemas de Información Geográfica. Participación en actividades docentes formativas. Año 2020 Se llevarán a cabo las actividades del año anterior durante el correspondiente ciclo de cultivo. Además se redactarán documentos científicos de los resultados obtenidos. Tareas formativas Formación en aspectos relacionados con la redacción de documentos científicos. Participación en actividades docentes formativas. Año 2021 Seguimiento en campo, al igual que años anteriores. No se continuará con el seguimiento en almacenes. Además se redactará la memoria final de Tesis Doctoral.O plan de traballo inclúe as seguintes actividades: - Seguimento fenolóxico e da sintomatoloxía da enfermidade causada por Alternaria durante o ciclo de cultivo da pataca. - Control aerobiolóxico da presenza de inóculo inicial de Alternaria na atmosfera do campo de cultivo. - Avaliación de diferentes modelos de predición de risco da alternariose e a súa posterior validación para as condicións climáticas da Limia. - Axuste dos modelos de predición para a Alternaria co obxectivo de minimizar o uso de produtos fitosanitarios e así traballar por unha agricultura máis sostible. - Aplicación de técnicas multivariantes para o tratamento dos datos meteorolóxicos, fenolóxicos e aerobiolóxicos. -Avaliación da calidade do tubérculo durante a súa almacenaxe e optimización dos métodos de conservación. O estudo realizarase na Limia, comarca pioneira en Galicia na comercialización e distribución da pataca. Ano 2018 O traballo iniciarase coa selección de parcelas para o seguimento en campo do patóxeno da pataca e das naves de almacenamento. Durante o primeiro ano realizarase: Rexistro das condicións meteorolóxicas do cultivo. Rexistro da progresión do ciclo fenolóxico das plantas de pataca. Estudo aerobiolóxico do ambiente do cultivo na parcela seleccionada. Seguimento dos tubérculos nas condicións de conservación no almacén. Informe de resultados. Tarefas formativas Formación en aspectos relacionados coa morfoloxía e fenoloxía das variedades. Formación de NIR. Ano 2019 Rexistro das condicións meteorolóxicas do cultivo. Rexistro da progresión do ciclo fenolóxico das plantas de pataca. Estudo aerobiolóxico do ambiente do cultivo na parcela seleccionada. Seguimento dos tubérculos nas condicións de conservación no almacén. Informatización dos datos obtidos no ciclo de cultivo anterior e o seu tratamento. Selección de modelos de prognóstico e testaxe. Informe de resultados. Tarefas formativas Curso de introdución á análise estatística multivariante. Curso de Sistemas de Información Xeográfica. Participación en actividades docentes formativas. Ano 2020 Levaranse a cabo as actividades do ano anterior durante o correspondente ciclo de cultivo. Ademais redactaranse documentos científicos a partir dos resultados obtidos. Tarefas formativas Formación en aspectos relacionados coa redacción de documentos científicos. Participación en actividades docentes formativas. Ano 2021 Continúase co seguemento e mostraxe en campo, seguindo o protocolo dos anos anteriores. Non se continuará co seguemento en almacéns. Ademais redactarase a memoria final de Tese Doutoral.The work plan includes the following activities: - Phenological monitoring and symptomatology of early blight disease during the potato growing cycle. - Aerobiological control of the presence of initial Alternaria inoculum in the atmosphere of the culture field. - Evaluation of different risk prediction models of early blight and its subsequent validation for the climatic conditions of A Limia. - Adjustment of the prediction models for Alternaria with the objective of minimizing the use of phytosanitary products for a more sustainable agriculture. - Application of multivariate techniques for the treatment of meteorological, phenological and aerobiological data. -Evaluation of tuber quality during storage and optimization of conservation methods. The study will be conducted in A Limia, a pioneer region in Galicia in the marketing and distribution of potatoes. Year 2018 The work will begin with the selection of plots for field monitoring of the potato pathogen and storage sheds. The work plan includes: Registration of the weather conditions of the crop. Record of the progression of the phenological cycle of potato plants. Aerobiological study of the cultivation environment in the selected plot. Tracking of tubers under storage conditions in the warehouse. Formative tasks Training in aspects related to the morphology and phenology of the varieties. NIR training. Year 2019 Registration of the weather conditions of the crop. Record of the progression of the phenological cycle of potato plants. Aerobiological study of the cultivation environment in the selected plot. Tracking of tubers under storage conditions in the warehouse. Computerization of the data obtained in the previous crop cycle and its treatment. Selection of forecast and test models. Results report. Formative tasks Introductory course in multivariate statistical analysis. Course on Geographic Information Systems. Participation in educational teaching activities. Year 2020 The activities of the previous year will be carried out during the corresponding crop cycle. In addition, scientific documents of the results obtained will be written. Formative tasks Training in aspects related to the writing of scientific documents. Participation in educational teaching activities. Year 2021 Follow-up in the field, just like previous years. Store tracking will not continue. In addition, the final report of the Doctoral Thesis will be written.Ministerio de Universidades | Ref. FPU 17/0026

Suitability of early blight forecasting systems for detecting first symptoms in potato crops of NW Spain

In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later.Ministerio de Educación, Cultura y Deportes | Ref. FPU 17/0026

Modification of the TOMCAST model with aerobiological data for management of potato early blight

The present study focuses on establishing thresholds of weather variables for predict early blight in potato crops. For this, the TOMCAST model was adjusted using weather variables and Alternaria conidia levels (mainly A. solani and A. alternata) during six growing seasons in A Limia (Northwest Spain). TOMCAST for the effective management of early blight considers leaf wetness and air temperature to calculate daily severity values (DSVs). Spearman correlations between temperature (minimum and average), mean temperature during leaf wetness period and Alternaria concentration showed the highest positive significant coefficients (0.386, 0.230 and 0.372, respectively; p < 0.01). Specifically, Alternaria levels higher than 50 spores/m3 were found the days with air mean temperature above 18 °C, more than 7 h of leaf wetness. Leaf wetness was decisive to estimate the concentration of Alternaria, resulting in a significant linear regression model (R2 = 0.41; p < 0.001). TOMCAST was adapted to the area, considering 10 °C the minimum threshold for the mean value of temperature during the wet period and 10–15 accumulated disease severity values (DSV). Using TOMCAST, it was possible to predict the first Alternaria peak in most of potato growing seasons. Combining aerobiological and meteorological data to control fungal diseases during crops are a useful tool for sustainable agriculture.Xunta de Galicia | Ref. Rural Development Programme 2014/2020-FEADEREspaña. Ministerio de Educación, Cultura y Deporte | Ref. FPU 17/0026

Prediction of physicochemical properties in honeys with portable near-infrared (microNIR) spectroscopy combined with multivariate data processing

There is an increase in the consumption of natural foods with healthy benefits such as honey. The physicochemical composition contributes to the particularities of honey that differ depending on the botanical origin. Botanical and geographical declaration protects consumers from possible fraud and ensures the quality of the product. The objective of this study was to develop prediction models using a portable near-Infrared (MicroNIR) Spectroscopy to contribute to authenticate honeys from Northwest Spain. Based on reference physicochemical analyses of honey, prediction equations using principal components analysis and partial least square regression were developed. Statistical descriptors were good for moisture, hydroxymethylfurfural (HMF), color (Pfund, L and b* coordinates of CIELab) and flavonoids (RSQ > 0.75; RPD > 2.0), and acceptable for electrical conductivity (EC), pH and phenols (RSQ > 0.61; RDP > 1.5). Linear discriminant analysis correctly classified the 88.1% of honeys based on physicochemical parameters and botanical origin (heather, chestnut, eucalyptus, blackberry, honeydew, multifloral). Estimation of quality and physicochemical properties of honey with NIR-spectra data and chemometrics proves to be a powerful tool to fulfil quality goals of this bee product. Results supported that the portable spectroscopy devices provided an effective tool for the apicultural sector to rapid in-situ classification and authentication of honey.Xunta de Galicia | Ref. 2014/2020-FEADER 2018/054

Looking for a sustainable potato crop. Field assessment of early blight management

Potato crops are susceptible to numerous field diseases causing significant losses in the quality and tuber yield. Control measures have a negative impact in soil and water resources affecting also farmers’ health and food security. Hence, a more sustainable agriculture management is a need to preserve ecosystems. Therefore, the objective of this study was to evaluate the response of nine potato cultivars (Fleur Bleue, Frisia, Fontane, Louisa, Agria, Daifla, Red Pontiac, Kennebec and Desiree) against early blight using a Decision Support Systems (DSS) in a potato-producing area from Northwest Spain. The experimental design was established using control plots and sprayed plots with fungicide according to a disease risk model adapted to the geographical region (DSS plots). Disease rating and severity were evaluated in field from the appearance of the first symptoms to final of senescence and the area under disease progress curve (AUDPC and r-AUDPC) was calculated. Aerobiological monitoring of main Alternaria species responsible potato early blight (Alternaria solani and Alternaria alternata) and the most vulnerable phenological stages were also considered. The susceptibility of the potato cultivars was analyzed based on the weather, severity of the disease and tuber yields. Specifically, temperature and leaf wetness were the meteorological variables that most influenced on the concentration of Alternaria. Conidia accounted for the previous week was the variable that most influenced in development of symptoms measured by AUDPC in natural conditions. Yields in the cultivars of DSS plots were higher than in control plots. Therefore, alternative pest management strategies, and specifically, Decision Support Systems for pest assessment are crucial for sustainable potato production. In this sense, the integration of particular information on disease resistance of commercial cultivars, phenological development of plant, or fungal particles surrounding the crop atmosphere could support these systems for better adjustment without compromising tuber yield and environment.Financiado para publicación en acceso aberto: Universidade de Vigo/CISU