An electronic leaf wetness recorder

1972 ◽  
Vol 78 (1) ◽  
pp. 29-32 ◽  
Author(s):  
K. Schurer ◽  
A. F. Wal
Keyword(s):  
Leaf Wetness

scholarly journals Comparison of Three Fungicide Spray Advisories for Lettuce Downy Mildew

Plant Disease ◽  
2001 ◽  
Vol 85 (8) ◽  
pp. 895-900 ◽  
Author(s):  
B. M. Wu ◽  
K. V. Subbarao ◽  
A. H. C. van Bruggen ◽  
S. T. Koike
Keyword(s):  
Downy Mildew ◽  
Drip Irrigation ◽  
Leaf Wetness ◽  
Lettuce Downy Mildew ◽  
Advisory System ◽  
System 2 ◽  
Forecasting System ◽  
Low Incidence ◽  
System 1 ◽  
First Time

Lettuce growers in coastal California have relied mainly on protective fungicide sprays to control downy mildew. Thus, timing of sprays before infection is critical for optimal results. A leaf-wetness-driven, infection-based advisory system, previously developed, did not always perform satisfactorily. In this study, the advisory system was modified by incorporating a pathogen survival component (system 1) or both survival and sporulation components (system 2). These systems were then evaluated in commercial lettuce fields in coastal California during 1996-1998. Three or four treatments were carried out in each field: (i) no spray; (ii) sprays as scheduled by the growers; (iii) sprays following modified system 1; and (iv) sprays following the original advisory system (1996) or modified system 2 (1998). Downy mildew incidence was evaluated every 2 to 9 days. In fields with drip irrigation, the number of fungicide applications was reduced by one or two regardless of the advisory system used compared to the grower's calendar-based schedule, although one unnecessary spray was recommended in 1996 at Soledad and 1997 at Salinas. Under all three systems, disease levels were low (incidence <25% and about 1 lesion per plant) for fields with drip irrigation, but not for fields with sprinklers (incidence up to 100% and 5 to 10 lesions per plant). For the first time, we established that survival and sporulation components are not needed for a lettuce downy mildew forecasting system. Instead, a threshold with a shorter period of morning leaf wetness and high temperatures were found to have potential for improving forecasting efficiency.

The impact of light quality and leaf wetness on photosynthesis in north-west Andean tropical montane cloud forest

2005 ◽  
Vol 21 (5) ◽  
pp. 549-557 ◽  
Author(s):  
Matthew Guy Letts ◽  
Mark Mulligan
Keyword(s):  
Cloud Forest ◽  
Net Photosynthesis ◽  
Leaf Wetness ◽  
Total Solar Radiation ◽  
Wet Season ◽  
Lowland Rain Forest ◽  
North West ◽  
Montane Cloud Forest ◽  
The Impact ◽  
Trees And Shrubs

Photosynthesis was limited by low-intensity photosynthetically active radiation (PAR) and leaf wetness in a lower montane cloud forest (LMCF) of Cauca, Colombia. Mean PAR intensity remained below the saturation level for leaf-scale net photosynthesis (Pn) throughout the solar day during the wet season and for most of the solar day during the dry season. PAR represented a smaller fraction of total solar radiation (K↓) in LMCF than in lowland rain forest (LRF). In LMCF trees and shrubs, mean PAR-saturated Pn ranged from 4.3–10.6 μmol C m−2 s−1 at 1450 m, and from 3.5–10.2 μmol C m−2 s−1 at 2150 m. Pn was reduced by abaxial wetness in leaves of some trees and shrubs, and eliminated in others. This study indicates that persistent cloudiness and interception of cloud water by leaves limit LMCF productivity.

scholarly journals Influence of Environment on Atmospheric Concentrations of Peronospora antirrhini Sporangia in Field-Grown Snapdragon

Plant Disease ◽  
2005 ◽  
Vol 89 (10) ◽  
pp. 1060-1066 ◽  
Author(s):  
J. M. Byrne ◽  
M. K. Hausbeck ◽  
L. E. Sconyers
Keyword(s):  
Average Length ◽  
Pathogen Resistance ◽  
Management Program ◽  
Leaf Wetness ◽  
Environmental Cues ◽  
Total Rainfall ◽  
Growing Seasons ◽  
Positive Correlations ◽  
Total Spore Count ◽  
Atmospheric Concentrations

Hourly concentrations of airborne sporangia of Peronospora antirrhini at a commercial snapdragon farm were investigated over three growing seasons to determine the influence of the environment on their occurrence and concentration. Hourly concentrations of sporangia of P. antirrhini were estimated using a Burkard volumetric spore sampler. Atmospheric sporangial concentrations followed a diurnal pattern and were greatest during 0500 to 1200 h. Minimum daily temperatures <10.0°C appeared to have a moderate limiting effect on atmospheric sporangial concentrations, whereas temperatures <6.0°C had more severe limiting effects. Maximum daily temperatures ≥30.0°C limited concentrations of atmospheric sporangia. Long dew periods (≥6 h) were associated with relatively large sporangia releases. On 69 days (1999 to 2001), the total number of sporangia trapped was >100/m3/day, and the average length of leaf wetness duration prior to these releases was 11 h. Consecutive days with short leaf wetness periods were associated with low atmospheric sporangial concentrations. Significant positive correlations (P = 0.0502 and P = 0.0174) were found between total rainfall and total spore count for both research plots in 2000. Information gained from this study will contribute to the development of a disease management program that utilizes environmental cues to prompt fungicide applications, thus increasing the efficiency of fungicide programs and delaying the development of pathogen resistance.

scholarly journals Investigation of Botrytis Cinerea Risk Forecasting Model of Strawberry in Lithuania

2013 ◽  
Vol 67 (2) ◽  
pp. 195-198 ◽  
Author(s):  
Neringa Rasiukevičiūtė ◽  
Alma Valiuškaitė ◽  
Elena Survilienė-Radzevičė ◽  
Skaidrė Supronienė
Keyword(s):  
Disease Management ◽  
Botrytis Cinerea ◽  
Air Temperature ◽  
Grey Mould ◽  
Management Systems ◽  
Forecasting Model ◽  
Leaf Wetness ◽  
Risk Of Infection ◽  
Risk Forecasting ◽  
Risk Probability

Grey mould, caused by Botrytis cinerea Pers.:Fr. is one of the most important strawberry diseases in Lithuania, like in other countries, where strawberries are grown. The efficiency of different disease management systems were analyzed at the Institute of Horticulture in 2010-2011. The B. cinerea risk probability at various regions of Lithuania was analyzed according to iMETOS ®sm grey mould risk forecasting model. Strawberry grey mould risk forecasting model indicates the risk of infection periods on the basis of the interaction between air temperature and leaf wetness duration. The model calculates how favourable is the period for the risk of infection. In periods where the risk is consistent (more than three days), higher than 60 points, a spray against grey mould should be applied. iMETOS®sm grey mould risk forecasting model gives the opportunity to optimize the usage of fungicides and reduce the number of applications and allows more efficient, ecologically and economically accepted control of strawberries grey mould.

scholarly journals Estimating leaf wetness duration over turfgrass, and in a 'Niagara Rosada' vineyard, in a subtropical environment

2008 ◽  
Vol 65 (spe) ◽  
pp. 10-17 ◽  
Author(s):  
Jorge Lulu ◽  
Paulo Cesar Sentelhas ◽  
Mário José Pedro Júnior ◽  
José Ricardo Macedo Pezzopane ◽  
Gabriel Constantino Blain
Keyword(s):  
High Accuracy ◽  
Training System ◽  
Dew Point ◽  
Classification And Regression Tree ◽  
Leaf Wetness ◽  
Good Precision ◽  
Weather Station ◽  
Leaf Wetness Duration ◽  
Confidence Index ◽  
Niagara Rosada

Leaf wetness duration (LWD) is a key parameter in agrometeorology because it is related to plant disease occurrence. As LWD is seldomly measured in a standard weather station it must be estimated to run warning systems for schedule chemical disease control. The objective of the present study was to estimate LWD over turfgrass considering different models with data from a standard weather station, and to evaluate the correlation between estimated LWD over turfgrass and LWD measured in a 'Niagara Rosada' vineyard, cultivated in a hedgerow training system, in Jundiaí, São Paulo State, Brazil. The wetness sensors inside the vineyard were located at the top of the plants, deployed at an inclination angle of 45º and oriented southwest, with three replications. The methods used to estimate LWD were: number of hours with relative humidity above 90% (NHRH > 90%), dew point depression (DPD), classification and regression tree (CART) and Penman-Monteith (PM). The CART model had the best performance to estimate LWD over turfgrass, with a good precision (R² = 0.82) and a high accuracy (d = 0.94), resulting in a good confidence index (c = 0.85). The results from this model also presented a good correlation with measured LWD inside the vineyard, with a good precision (R² = 0.87) and a high accuracy (d = 0.96), resulting in a high confidence index (c = 0.93), showing that LWD in a 'Niagara Rosada' vineyard can be estimated with data from a standard weather station.

scholarly journals Rust and leaf spot diseases on American elderberry plants

2017 ◽  
Author(s):  
◽  
Kaley Hensel
Keyword(s):  
Leaf Spot ◽  
Dry Weight ◽  
Growing Season ◽  
Significant Loss ◽  
Leaf Wetness ◽  
Conservative Estimate ◽  
Sambucus Nigra ◽  
Shoot Dry Weight ◽  
Harvest Dates ◽  
High Level

Elderberry rust (Puccinia sambuci Schewin.) Arthur (=P. bolleyana) and leaf spot diseases are frequently found in commercial American elderberry (Sambucus nigra L. subsp. canadensis L.) plantings throughout the growing season in Missouri. Thus, studies were conducted to ascertain if rust infections affect plant growth, fruiting, or berry puree quality. Rust symptoms were observed in early April at 9 to 18[degrees] C, [greater than or equal to] 3 h leaf wetness, and [greater than or equal to] 85% relative humidity. When young, potted elderberry plants averaged 3 to 6 rust pustules/plant, vegetative growth was not adversely affected. However, field-grown elderberry plants heavily infected with rust (137 pustules/cane) lost nearly twice as many leaves as controls during the growing season, indicating rust-induced defoliation. Shoot dry weight of these heavily infected canes was also 32% less than that of controls. First and last harvest dates were advanced by the high level of rust infection on 'Wyldewood' elderberry canes, but not by low pustules numbers ([less than] 6 pustules/plant) on 'Bob Gordon' or 'Ozark' plants. Similarly, berry yields were not significantly different at low infection levels, even though rust-infected 'Bob Gordon' plants had a 31% reduction in yield with an estimated $440/ha loss of income. Heavily-infected 'Wyldewood' canes had a significant loss in berry yield (47%) and potential income ($2,295/ha), assuming a conservative estimate of five canes/plan. In another study, Colletotrichum was isolated from elderberry leaf spot lesions and identified before subsequent re-inoculation of elderberry plants with this pathogen. Three species of Colletotrichum (C. salicis Funkel, C. kahawae subsp. ciggaro Wollenw., and C. aenigma C.M. Tian and Z. Li) were putatively identified as being casual agents of leaf spot indicating the diversity of species within this genus on elderberry plants.

scholarly journals Measurement and modelling of the dynamics of NH<sub>3</sub> surface-atmosphere exchange over the Amazonian rainforest

2020 ◽  
Author(s):  
Robbie Ramsay ◽  
Chiara F. Di Marco ◽  
Mathew R. Heal ◽  
Matthias Sörgel ◽  
Paulo Artaxo ◽  
...  
Keyword(s):  
Tropical Rainforest ◽  
Pearson Correlation ◽  
Single Layer ◽  
Vapour Pressure Deficit ◽  
Compensation Point ◽  
Leaf Wetness ◽  
Regional Modelling ◽  
Surface Exchange ◽  
A Value ◽  
Amazonian Rainforest

Abstract. Local and regional modelling of NH3 surface exchange is required to quantify nitrogen deposition to, and emissions from, the biosphere. However, measurements and model parameterisations for many remote ecosystems – such as tropical rainforest – remain sparse. Using one month of hourly measurements of NH3 fluxes and meteorological parameters over a remote Amazon rainforest site (Amazon Tall Tower Observatory, ATTO), six model parameterisations based on a bi-directional, single-layer, canopy compensation point resistance model were developed to simulate observations of NH3 surface exchange. Canopy resistance was linked to either relative humidity at the canopy level (RHz′0), vapour pressure deficit, or a parameter value based on leaf wetness measurements. The ratio of apoplastic NH4+ to H+ concentration, Γs, during this campaign was inferred to be 38.5 ± 15.8. The parameterisation that reproduced the observed net exchange of NH3 most accurately was the model that used a cuticular resistance (Rw) parameterisation based on leaf wetness measurements and a value of Γs = 50 (Pearson correlation r = 0.71). Conversely, the model that performed the worst at replicating measured NH3 fluxes used an Rw value modelled using (RHz′0) and the inferred value of Γs = 38.5 (r = 0.45). The results indicate that a single layer, canopy compensation point model is appropriate for simulating NH3 fluxes from tropical rainforest during the Amazonian dry season, and confirmed that a direct measurement of (a non-binary) leaf wetness parameter improves the ability to estimate Rw. Current inferential methods for determining Γs were noted as having difficulties in the humid conditions present at a rainforest site.

scholarly journals A Computer-Controlled Environmental Chamber for the Study of Aerial Fungal Spore Release

1997 ◽  
Vol 87 (10) ◽  
pp. 1078-1084 ◽  
Author(s):  
T. R. Gottwald ◽  
T. M. Trocine ◽  
L. W. Timmer
Keyword(s):  
Data Acquisition ◽  
Environmental Conditions ◽  
Venturia Inaequalis ◽  
Data Acquisition System ◽  
Environmental Data ◽  
Acquisition System ◽  
Leaf Wetness ◽  
Environmental Chamber ◽  
Spore Trap ◽  
Spore Release

An environmental chamber was designed to study aerial release of spores of ascomycetes and hyphomycetes, based on a device developed by C. M. Leach. Relative humidity (RH), temperature, red (660 nm) and infrared (880 nm) light, leaf wetness, wind speed, vibration, and rain events are controlled and monitored within the chamber via an RTC-HC11 real-time controller and data-acquisition system. A BASIC11 computer program is uploaded to and controls the system. The program requests values for environmental parameters that change through time according to user specifications. The controller interacts with a stepper motor, solenoids, and relay switches via a feedback system based on data received from solid-state RH, temperature, and leaf-wetness sensors. The data-acquisition system records environmental data from the chamber in RAM (random access memory) that can be downloaded to a personal computer for correlation with spore-release data. Spores released from fungal specimens on plant tissues and cultures placed in the chamber and subjected to the desired environmental conditions are collected on a continuous volumetric spore trap at an exhaust port from the chamber. The performance of the device was examined by measuring spore release of Mycosphaerella citri, Alternaria solani, and Venturia inaequalis under various environmental conditions.

An Automated Optimize Utilization of Water and Crop Monitoring in Agriculture Using IoT

2021 ◽  
pp. 37-45
Author(s):  
Ajith Krishna R ◽  
◽  
◽  
◽  
Ankit Kumar ◽  
...  
Keyword(s):  
Soil Analysis ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Leaf Wetness ◽  
Productivity Analysis ◽  
Factors Affecting ◽  
Crop Monitoring ◽  
Different Types ◽  
Smart Agriculture ◽  
Climate Analysis

Agriculture is the primary occupation in our country for ages. But now due to migration of people from rural to urban there is hindrance in agriculture. So, to overcome this problem we go for smart agriculture techniques using IoT. This paper includes various features like GPS based remote controlled monitoring, moisture & temperature sensing, intruders scaring, security, leaf wetness and proper irrigation facilities. It makes use of wireless sensor networks for noting the soil properties and environmental factors continuously. Various sensor nodes are deployed at different locations in the farm. Controlling these parameters are through any remote device or internet services and the operations are performed by interfacing sensors, Wi-Fi, camera with microcontroller. This concept is created as a product and given to the farmer’s welfare. AI Solution for Farmers perform soil analysis, climate analysis, and productivity analysis using linear regression. It helps farmers to understand about the crop to be sown as well as the factors affecting their productivity with the help of different types of graphs and tables. Farmers need not to do anything on the application as it is highly interactive as by using speech API.

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