Wetness Duration Research Articles

Avaliação de sistemas de previsão para a septoriose do tomateiro tutorado em Caçador, SC, Brasil

A septoriose, causada pelo fungo Septoria lycopersici, é uma das mais importantes doenças do tomateiro tutorado em Caçador, SC, Brasil. A doença é geralmente controlada pela aplicação preventiva de fungicidas. Experimentos de campo foram realizados com o objetivo de avaliar sistemas de previsão dessa doença: um com base no sistema TomCast (10, 15 e 20 valores de severidade – VSD), outro pelo período de molhamento foliar (limiar ≥ 12 horas), ambos comparados com a aplicação semanal de fungicidas. O TomCast utiliza a duração do molhamento foliar e a temperatura média deste período para calcular o valor de severidade diário da doença (VSD). Não houve diferença significativa entre o tratamento semanal e os previsores em relação a produtividade, severidade final, área abaixo da curva do progresso da doença e taxa de infecção aparente (r). Entretanto, com o tratamento 20-VSD houve redução de 12,5 a 70% das pulverizações em relação ao tratamento semanal. Termos para indexação: Solanum lycopersicum; sistema de alerta; TomCast; Septoria lycopersici; método de controle

Comparison of wetness sensors and the development of a new sensor for apple scab prognosis

Apple scab prediction is based on the model of Mills which describes the risk of Venturia inaequalis infection using leaf wetness duration and air temperature data. The quality of prognosis relies on sensor quality. Six brands of commercially available leaf wetness sensors were compared at the Julius Kuehn-Institute (Germany) apple orchard from 2011 to 2013. Also a new wetness sensor was developed and optimized from 2009 to 2015 in cooperation with Thies Clima company. The Thies-wetness sensor was equipped with a glass–ceramic surface, an adjustable heating system to avoid dew and an adjustable cooling system to prolong wetness duration of sensor surface. Prototypes were tested in climate chamber before exposition in the orchard to achieve sensor settings with drying properties broadly similar to apple leaves. The market-ready prototype showed suitability for prognosis in field assays in primary seasons of 2015–2017 and maybe integrated into prognosis of apple scab without further modeling. The Thies-sensor was shown to be more reliable, uniform, sensitive and more suitable for forecasting than the purchased models.

Leaf wetness duration estimation and its influence on a soybean rust warning system

A limitation for widespread implementation of Asian soybean rust (ASR) warning system is the scarcity of leaf wetness duration (LWD) data. The objective of this study was to assess the feasibility of using LWD estimated by different empirical methods as input data for an ASR-warning system. The study was carried out with data from field experiments conducted in Ponta Grossa, Parana State, Campo Verde and Pedra Preta, both in Mato Grosso State, Brazil, throughout the 2014–15 and 2015–16 seasons. The estimated LWD values were used as input in an ASR-warning system. More reliable estimations of LWD were obtained using the Number of Hours with Relative Humidity above 90% (NHRH≥90%). The use of estimated LWD resulted in disease overestimation in Ponta Grossa, underestimation in Pedra Preta and moments of under and overestimation in Campo Verde. Analyzing the ASR-warning system with the more conservative threshold, five sprays per season were recommended for all sites and the mean fractions of correct estimates (θ1) in Ponta Grossa were higher (θ1 = 0.876) than those obtained in Pedra Preta (θ1 = 0.632) and Campo Verde (θ1 = 0.662). Otherwise, for the less conservative spray threshold, a reduction of one spray was observed in Ponta Grossa (θ1 = 0.912) when compared to Pedra Preta (θ1 = 0.826) and Campo Verde (θ1 = 0.767), where five sprays were still recommended. Thus, LWD estimated by NHRH≥90% has enough accuracy and precision for being used as input in the ASR-warning system in the most traditional soybean regions of Brazil.

Tree-ring δ18O based PDSI reconstruction in the Mt. Tianmu region since 1618 AD and its connection to the East Asian summer monsoon

Abstract Previous studies on tree-ring stable oxygen isotopes (δ18O) in the monsoon region of China have rarely involved in variations of the East Asian summer monsoon (EASM) and its rainbelt. In this study, a tree-ring δ18O chronology of Cryptomeria fortune at Mt. Tianmu, located south of the Yangtze River lower reaches, was developed and applied to reconstruct the local June–October Palmer Drought Severity Index (PDSI6–10) during the 1618–2013 AD period. The reconstruction explains 40.5% of the observational PDSI6–10 variances during 1951–2013, captures the actual variation features at both high and low frequencies, largely represents the PDSI6–10 in the middle and lower reach regions of the Yangtze River and further south, and the reconstruction is well-compared with other existing proxies. The reconstruction reveals that the durations of 1620 s–1660 s, 1680 s–1700 s, 1810 s–1830 s, 1850 s, 1900 s–1940 s, and 1960 s were drought periods, while wet durations were 1730 s–1770 s, 1790 s–1800 s, 1860 s–1870 s, 1950 s, and 1980 s–1990 s. Based on the meteorological reanalysis data and new EASM definitions, the reconstructed PDSI6–10 correlates with the meiyu rainbelt precipitation and EASM intensity during May–June, which is when Mt. Tianmu is affected by the EASM rainbelt. The Mt. Tianmu tree-ring δ18O chronology exhibits significantly positive correlations with El Nino–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). The relationship of the tree-ring δ18O chronology with the PDO could be due to EASM associations, while it is not clear to explain the mechanism of ENSO connecting to the tree-ring oxygen isotope.

Improving the Performance of Vegetable Leaf Wetness Duration Models in Greenhouses Using Decision Tree Learning

Leaf wetness duration (LWD) is a key driving variable for peat and disease control in greenhouse management, and depends upon irrigation, rainfall, and dewfall. However, LWD measurement is often replaced by its estimation from other meteorological variables, with associated uncertainty due to the modelling approach used and its calibration. This study uses the decision learning tree method (DLT) for calibrating four LWD models—RH threshold model (RHM), the dew parameterization model (DPM), the classification and regression tree model (CART) and the neural network model (NNM)—whose performances in reproducing measured data are assessed using a large dataset. The relative importance of input variables in contributing to LWD estimation is also computed for the models tested. The LWD models were evaluated at two different greenhouse locations: in a Chinese (CN) greenhouse over three planting seasons (April 2014–October 2015) and in a Spanish (ES) greenhouse over four planting seasons (April 2016–February 2018). Based on multi-evaluation indicators, the models were given a ranking for their assessment capabilities during calibration (in the Spanish greenhouse from April 2016 to December 2016 and in the Chinese greenhouse from April 2014 to November 2014). The models were then evaluated on an independent set of data, and the obtained areas under the receiver operating characteristic curve (AUC) of the LWD models were over 0.73. Therein, the best LWD model in this case was the NNM, with positive predict values (PPVs) of 0.82 (SP) and 0.90 (CN), and mean absolute errors (MAEs) of 1.85 h (SP) and 1.30 h (CN). Consequently, the DLT can decrease LWD estimation error by calibrating the model threshold and choosing black box model input variables.

Original Epidemic Modeling for Plant Disease under Combined Effects of Wetness Duration and Temperature

This paper is concerned with the modeling and the fitting of an original epidemic model for plants disease. This model has the shape of a bump function which reflects the effect of the temperature and the wetness duration. Moreover, we provide a procedure that involves bounds constraints to fit the introduced model. In addition, our modelling accuracy and efficiency are evaluated for some reported studies in the literature. The simulation results are provided for the validation and in order to show the effectiveness of the proposed epidemic models for diverse plant infections reported in the literature.

Development of prediction models for the management of rapeseed-mustard diseases-Current scenario

An epidemic is the progress of disease in time and space. each epidemic has a structure whose temporal dynamics, and spatial patterns are jointly determined by the pathosystem characteristics, and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modelling. Knowledge of epidemiology and forecasting provides the basic information to develop efficient and workable plant disease control methods. The various weather variables such as temperature (T), relative humidity (RH), rainfall, wind velocity and direction, leaf wetness duration, and solar radiation influence different parameters of infection process, and disease development. Interaction between these weather variables (independent variables) and disease development (dependent variables) pave the way for the development of the prediction models. The average productivity of rapeseed-mustard, an important oil seed crop in India, is quite low due to infection by several diseases such as Alternaria blight (Alternaria brassicae) white rust (Albugo candida), downy mildew (Hyaloperonospora parasitica), powdery mildew (Erysiphe cruciferarum), and white or Sclerotinia stem rot (Sclerotinia sclerotiorum). These diseases are being managed through chemical fungicides, but the efficiency of control measures depends upon the interaction between pathogen and host, which is influenced by environmental factors. Prediction models developed for the management of important diseases of rapeseedmustard are discussed here. Development of alternaria blight is favoured by tmax of 20–25OC, tmin of 15OC, rhmor > 90% and rheve > 50%. For white rust, tave of >15OC and rh >65% with intermittent rains proved most effective for disease development. Similarly, for downy mildew, a T range of 15–20OC with high rh was considered optimal for its progress. Leaf wetness duration of 4–6 h at 20OC and 6–8 h at 15OC is essential to initiate the downy mildew infection. stag-head due to mixed infection of downy mildew and white rust is favoured by a t 20OC with high RH. A reduced period of sunshine (2–6 h/d) with rainfall up to 161 mm during flowering favours the stag-head formation. Powdery mildew development is favoured by t range of 16–28OC, mean rh 80%), Tmax up to 25OC and tmin of 5–12OC. Often prediction models developed at one location may not fit at other locations. It indicates that data need to be generated for a longer period and the model be tested at multilocations. For greater efficiency, the disease-forecasting models must be developed by taking into account the crop variety, the prevalence of a particular pathotype and the microclimatic factors.

Automated Analysis of Aggregated Datasets to Identify Climatic Predictors of Botrytis Bunch Rot in Wine Grapes.

Botrytis bunch rot (BBR), caused by Botrytis cinerea, results in serious losses to wine-grape production in some seasons during the preharvest period. In order to predict seasons that are at risk from BBR, datasets consisting of 25 disease, weather and vine phenology variables were aggregated from 101 SiteYears across seven regions and nine growing seasons. Automated analyses were used to compare a range of statistical methods for their ability to predict BBR epidemics, including the Kruskal-Wallis test, logistic regression, receiver operating characteristic analysis, and skill-scores. Variables based on relative humidity and surface-wetness duration were significant and consistent predictors of BBR epidemics across the range of analyses applied. Variables integrating temperature and wetness duration, including the Bacchus and Broome models, also demonstrated high predictive ability; however, they did not outperform their constituent components in all analyses. Automation of data analyses was an effective way to compare a wide range of statistical methods and a large number of variables with minimal user input, following initial code development. Significant time was needed to check input data and software code, but a greater return on investment would occur should the analytical process be applied to new datasets, including those from other pathosystems.

Spatio-temporal aspects of brown eye spot and nutrients in irrigated coffee

Brown eye spot is one of the most common and important diseases of coffee in Brazil. Using geostatistics, this study evaluated the spatio-temporal aspects of the disease and how they relate to plant nutrition and soil fertility in plots irrigated by center pivot and drip irrigation. The experiments were conducted in Carmo do Rio Claro City, in southern Minas Gerais state, southeast Brazil. The sampling grid was georeferenced with 50 points in 17 ha and 52 points in 11 ha for center pivot and drip irrigation, respectively. Disease incidence was assessed at 60-day intervals from August 2012 to March 2015. Yield, plant mineral nutrition, and soil fertility were evaluated at each point annually. Weather data were obtained from climatological stations with sensors for temperature, relative humidity, wind velocity, leaf wetness duration, and total precipitation that were located inside and outside the coffee canopy in both experimental plots. Climate data were correlated with disease incidence. Disease progress curves were plotted, and semivariogram models were fitted for assessments with a high disease incidence over time. Then, the data were interpolated by ordinary kriging, and maps of disease, yield, and leaf nutrients (B, P, and K) were constructed. The average temperatures and accumulated rainfall rates were lower in periods of higher incidence, but relative humidity was high. All variables exhibited space-time variation in both plots. There was a correlation (p < 0.01) between disease incidence and leaf nutrients (B, K and P). The disease incidence in the center pivot and drip irrigation plots ranged from 0 to 23% and 0–25%, respectively, and varied over space, showing spatial dependence and the presence of disease foci with outward gradients. Areas with high intensity changed over planting years along with yield and nutrient availability.

Spatiotemporal trends of dryness/wetness duration and severity: The respective contribution of precipitation and temperature

This study explores the respective contributions of precipitation and temperature variability to the trends of the duration and severity of the dryness/wetness, and takes the Pearl River basin (PRB) in the southern China as a study example. The Standardized Precipitation Evapotranspiration Index (SPEI), which uses the monthly precipitation and temperature as input variables, was calculated based on the monthly precipitation and temperature records of 42 meteorological gauges during 1960–2015 in the PRB. The run theory was then applied to extract the dryness/wetness characteristics including the drought duration and severity and the wetting duration and severity. In addition, a simple algorithm for quantifying the respective contribution of the precipitation and temperature variability to the dryness/wetness trends was proposed; the algorithm determines the changes in the slope's magnitude (linear regression) for the dryness/wetness characteristics that were identified from different SPEI scenarios (i.e. the precipitation and temperature groups of observed, one of them detrended, and both detrended) using the run theory method. Our results showed that the increasing trends of drought duration and severity were more apparent in the northwestern areas with high elevation (>1000 m) than the southeastern areas with low elevation (<500 m), whereas the change trends of the wetness duration and severity exhibited opposite results. The variability of the precipitation and temperature played different roles in the trends of the dryness/wetness characteristics; the effects of the temperature changes on these trends were larger than the effects of the precipitation changes, i.e., an increase in the temperature clearly affected the change trends of duration and severity for the dryness/wetness. In the PRB, a slight increase in the average precipitation resulted in decreases in the trends of drought duration and severity of 9.89% and 19.63% respectively and increases in the trends of wetting duration and severity of 1.59% and 11.52%. However, a marked increase in the average temperature resulted in increases in the trends of drought duration, drought severity, wetting duration, and wetting severity of 48.38%, 55.16%, 46.21%, and 34.40%, respectively. Thus, in light of global warming, the government should focus more attention on the evolution of the dryness/wetness characteristics because increases in severe drought occurrences and flood severities and secondary disasters may result in more severe losses.

How Does Botrytis cinerea Infect Red Raspberry?

Botrytis cinerea, causal agent of gray mold, is one of the most important pathogens affecting raspberry in the U.S. Pacific Northwest and worldwide. Fungicides are currently applied to control the disease starting from 5 to 10% bloom and continuing on a calendar basis throughout the season rather than according to inoculum level or infection risk primarily because the disease cycle on red raspberry is poorly understood. Botrytis cinerea was isolated from raspberry flowers and fruit sampled at seven developmental stages during each of 2015 and 2016 in a northwestern Washington raspberry field untreated with fungicides. Incidence of colonization of flowers was low (15% of total sampled flowers), but increased as fruit developed, and peaked in mature fruit (67% of total sampled fruit). In the early stages of flower development, B. cinerea recovery was greatest from the carpel (80% of carpels colonized) compared with other floral organs. As fruit matured, additional floral parts were colonized by B. cinerea, possibly facilitating secondary internal or external infections of mature fruit. Average weekly minimum air temperature, average weekly night air temperature, cumulative rain, average weekly leaf wetness percentage, and duration of leaf wetness >90% were significantly positively correlated with B. cinerea colonization of raspberry in NW Washington during two seasons of this study. Our data does not support the hypothesis that the bloom period is the critical window for B. cinerea colonization of red raspberry and suggest that later colonization of developing fruit may be more important for gray mold development on raspberry. The outcomes of this research provide useful information for improvement of gray mold disease management strategies for red raspberry in NW Washington and elsewhere.

Severity of Septoria Leaf Spot and Sunflower Yield Due to Leaf Wetness Duration

The objective of this study was to evaluate the effect of leaf wetness on the severity of septoria leaf spot in sunflower. The experiments were performed in two sowing dates in November and January in Santa Maria, RS. Sunflower inoculation was carried out with the Septoria helianthi isolate, with subsequent assessment of disease severity, progress and cypsela yield. The treatments were composed of different periods of 0, 8, 12, 16, 20, 24, 28 and 32 hours of artificially applied leaf wetness. Variables influencing the disease were observed during the cycle, such as mean air temperature, mean relative air humidity and daily-accumulated rainfall. The greater the leaf wetness the greater the severity and the area under the disease progress curve. Meantime, the healthy leaf area duration has an inverse relation with leaf wetness duration. The yield also decreases with greater leaf wetness duration and the yield reduction reaches 100% in the plants exposed to the longer leaf wetness periods.

Moisture behavior of weathered wood surfaces during cyclic wetting: measurements and modeling

The effects of weathering on the in-service moisture behavior of wood have received only limited attention so far, with much focus being on the effect of photodegradation on the hydrophobicity of the wood surface. The objective of the present study was to examine the effect of weathering surfaces on the overall moisture behavior of wood specimens exposed to short-term cyclic spraying, with special emphasis on the surface conditions involved. Specimens cut from eight different species including hardwoods and softwoods were weathered for 8 years and continuously monitored during a single-sided cyclic spraying together with a set of axially matched controls. After each spray cycle, the duration of surface wetness was evaluated by resistance moisture sensors as well as an optical approach (colorimetric) based on time-lapse images. The moisture content in the core was monitored simultaneously by use of resistance moisture sensors. The optical method correlated well with the electrical resistance measurements and provided a simple and practical measure of the areal distribution of the surface wetness. The results showed specimens with a weathered surface to sustain a wet surface for about twice the duration of their axially matched control. A considerable, albeit smaller, effect was also observed deeper in the core. By adapting the length of the wet period on the exposed boundary, the corresponding response at the core of the Norway spruce specimens was reproduced numerically.

Effects of Temperature and Moisture on the Infection and Development of Apple Fruit Rot Caused by Phytophthora cactorum.

Phytophthora fruit rot, caused by Phytophthora cactorum, is an important disease of apple in China, often causing more than 50% fruit rot in rainy years. We examined the effects of temperature and moisture on the development of the disease and effects of the variables on zoospore release and germination, infection, and lesion development. In vitro, a temperature range of 5 to 20°C had no significant effects on zoospore release dynamics but did significantly affect the quantities of released zoospores. The largest quantity of zoospores was released at 9.9°C according to a fitted model. Zoosporangia released zoospores within 15 min at the test temperatures (0 to 20°C), which peaked at the fourth hour. Zoospores germinated in vitro, requiring free water, at temperatures from 5 to 35°C. The optimum germination temperature was 25.1°C according to a fitted model. The minimum wetness duration required for zoospores to complete the infection process and induce visible lesions on Fuji fruit was 0.40 h at the optimal temperature of 23.0°C according to the fitted model, whereas observed values were 4.5, 1.5, 0.5, 1.5 and 8.5 h at 10, 15, 20, 25, and 30°C, respectively. The number of zoospore infections on fruit at various temperatures and wetness durations were well fitted by the modified Weibull model; based on the model, the optimal temperature for zoospore infections was 23.0°C. Young apple fruit infected by zoospores developed visible lesions from 10 to 30°C, with a predicted optimum of 23.5°C; no lesions developed at 5 or 35°C. The shortest incubation period of the disease was 4 days. These results can be used to develop disease forecasting models for improved fungicide control.

Cercospora leaf spot in Toona ciliata: Epidemiology and infection process of Cercospora cf. alchemillicola

AbstractThe biology of Cercospora leaf spot (Cercospora cf. alchemillicola) of Toona ciliata was examined in terms of the effects of temperature and duration of foliage wetting on the progress of disease and the mechanism of pathogen infection. To evaluate the effect of temperature on mycelial growth, cercosporin production and conidial germination, experiments were conducted in a 4 × 5 factorial design, with four isolates (HR01, HR02, HR03 and CML3059) at five temperatures (15, 19, 23, 26 and 30°C). The area under the disease progress curve (AUDPC) was calculated in a 3 × 5 factorial design at three temperatures (20, 23 and 29°C) and five leaf wetness durations (0, 12, 24, 48 and 72 hr). Penetration of C. cf. alchemillicola into leaves was examined by scanning electron microscopy. Maximum mycelial growth of all isolates occurred at 24.8°C. HR02 and HR01 produced higher quantities of cercosporin compared with CML3059 and HR03. Temperatures between 21.6 and 23.0°C favoured production of the toxin among isolates. Higher conidial germination rates occurred in isolates HR02 and HR01 compared with other isolates, with optimum germination occurring at 24.2–26.3°C. A leaf wetting period of 72 hr at 23.3°C gave the highest AUDPC value. No hyphal penetration was observed through natural openings. However, germ tubes grew inside wounds on the leaf epidermis. In addition, Phyllachora balansae (cause of tar spot) opened fissures on the leaf epidermis, thus creating wounds enabling C. cf. alchemillicola to infect.

Molecular characterisation of downy mildew caused by Perofascia lepidii on garden cress and conditions favouring disease development

Seed propagation of garden cress (Lepidium sativum) on organic farms can be compromised by downy mildew disease, which can develop rapidly, especially when relative humidity levels are high. The causative pathogen is thought to be Perofascia lepidii, particularly in Germany, although similar symptoms can be induced by the other oomycetes Hyaloperonospora sp. and Albugo lepidii. Here, a species-specific PCR assay was developed to allow the rapid discrimination of P. lepidii from these other oomycete pathogens. To control the downy mildew disease on garden cress, knowledge about conditions favouring the disease development is required. Thus, we studied the effect of temperature on sporangia germination in vitro and evaluated the impact of inoculum density, the effect of post-inoculation temperature and the duration of leaf wetness on disease development. P. lepidii sporangia germinated most freely in vitro when air temperatures were in the range of 5–10 °C, while a post-inoculation temperature range of 15–25 °C was optimal for disease development. A positive relationship between the duration of leaf wetness and disease severity was observed within less than 1 h after inoculation.

Effects of wetness duration, inoculum concentration and temperature on the development of Alternaria blight on transplants of sweet potato

ISHS Acta Horticulturae 1204: VII International Symposium on Seed, Transplant and Stand Establishment of Horticultural Crops - SEST2016.

Modelling some aspects of the monocyclic phase of Stemphylium vesicarium, the pathogen causing purple spot on asparagus (Asparagus officinalis L.)

The monocyclic phase of Stemphylium vesicarium is part of its life cycle and a possible factor for forecasting and the integrated control of purple spot on asparagus. The purpose of the study was to model the flight, germination and germ tube growth of ascospores as basis for the development of a forecasting system. During 2014–2016, the flight period was determined by spore traps. The ascospores flew between March and early July, but most were released in early May. The cumulative percentage of trapped ascospores depending on the daily summed temperature (base 5 °C) on rainy days starting from February 1st was described best by a Chapman Richards function. The germination and germ tube length of ascospores depending on leaf wetness duration and temperature were investigated in laboratory trials. Ascospores germinated rapidly in a wide temperature range. The fitted Chapman Richards function with a temperature-dependent capacity and rate described germination adequately with a calculated optimal temperature of 31.0 °C. The germ tube length was modelled by a combined generalised beta-linear function and it was optimal at 30.4 °C with a narrow temperature range of 25–35 °C for values close to the optimum length. Therefore, the infection process is restricted more severely by the germ tube length than by germination. The ascospore flight is often finished before the end of the harvest, so fungicide treatments during the monocyclic phase might be ineffective in many production sites in Germany. The situation could be different for shorter harvest periods and in non-harvested young plants.

Effects of leaf wetness duration and temperature on infection of Prunus by Xanthomonas arboricola pv. pruni.

Xanthomonas arboricola pv. pruni is the causal agent of bacterial spot disease of stone fruits and almond. The bacterium is distributed throughout the major stone-fruit-producing areas of the World and is considered a quarantine organism in the European Union according to the Council Directive 2000/29/EC, and by the European and Mediterranean Plant Protection Organization. The effect of leaf wetness duration and temperature on infection of Prunus by X. arboricola pv. pruni was determined in controlled environment experiments. Potted plants of the peach-almond hybrid GF-677 were inoculated with bacterial suspensions and exposed to combinations of six leaf wetness durations (from 0 to 24 h) and seven fixed temperatures (from 5 to 35°C) during the infection period. Then, plants were transferred to a biosafety greenhouse, removed from bags, and incubated at optimal conditions for disease development. Although leaf wetness was required for infection of Prunus by X. arboricola pv. pruni, temperature had a greater effect than leaf wetness duration on disease severity. The combined effect of wetness duration and temperature on disease severity was quantified using a modification of the Weibull equation proposed by Duthie. The reduced-form of Duthie’s model obtained by nonlinear regression analysis fitted well to data (R = 0.87 and R2adj = 0.85), and all parameters were significantly different from 0. The estimated optimal temperature for infection by X. arboricola pv. pruni was 28.9°C. Wetness periods longer than 10 h at temperatures close to 20°C, or 5 h at temperatures between 25 and 35°C were necessary to cause high disease severity. The predictive capacity of the model was evaluated using an additional set of data obtained from new wetness duration-temperature combinations. In 92% of the events the observed severity agreed with the predicted level of infection risk. The risk chart derived from the reduced form of Duthie’s model can be used to estimate the potential risk for infection of Prunus by X. arboricola pv. pruni based on observed or forecasted temperature and wetness duration.

Introduction to Electrochemical Impedance Spectroscopy as a Measurement Method for the Wetting Degree of Lithium-Ion Cells

In the production process chain of lithium-ion battery cells, the filling, consisting of dosing and wetting steps, of the cell and its components with electrolyte liquid is eminent for the final product quality and costs. To reduce the unnecessary wetting duration between filling and formation, and thereby the production costs, a measurement method for the wetting progress is necessary. In this paper, electrochemical impedance spectroscopy (EIS) as a well-established technique is used for the first time to quantify the wetting degree of batteries during cell production. The experimental data of the EIS acquired during the dosing and subsequent wetting process is correlated to images recorded by in situ neutron radiography. Results show that the impedance of the battery cells strongly depends on the wetting degree of the cell assembly and can thus be used to determine the fully wetted state enabling faster processing.