The performance of three types of leaf-wetness recorders

Lomas, J.; Shashoua, Y.

doi:10.1016/0002-1571(70)90012-9

Cited by 14 publications

(8 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The 'general rule' that leaves are wet when RH at screen height is >90% could not be applied in this study. Lomas and Shashoura [1970] and Thompson [1981] have had similar experiences with 85% and 90% criteria, respectively. We can agree with the former authors, that accurate measurements are best taken within the crop, but where appropriate instruments are lacking an estimate of leaf wetness duration from standard weather station data is an alternative.…”

Section: Discussionmentioning

confidence: 99%

“…The relationship between macro-and microclimate, particularly for leaf wetness, has been addressed in different ways [Smith, 1962;Wallin, 1963;Lomas and Shashoura, 1970;Crowe et al, 1978;Gillespie and Sutton, 1979;Hackel, 1980Hackel, , 1984Gillespie, 1982a, 1982b;Royle and Butler, 1986;Huber, 1988;1992] and with different results and conclusions. A 'general rule' states that the canopy will be wet when relative humidity at screen height is >90% [Smith, 1956;Thompson, 1981;Sutton et al, 1984;Friesland and SchrOdter, 1988;Campbell and Madden, 1990], although its limitations are not denied.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The relationship of leaf wetness duration and disease progress of glume blotch, caused byStagonospora nodorum, in winter wheat to standard weather data

1996

View full text Add to dashboard Cite

Almost 50% of the variation in leaf wetness duration can be explained by maximum and minimum temperatures, rainfall and hours with relative humidity above 90% on a daily basis. All of these parameters can be estimated from a standard weather station. If variables related to wind are added the level of explanation increases to 69-76%. Leaf wetness duration explained up to 42% of the rate of disease increase (RDI) for S. nodorum. Leaf wetness duration was accumulated over a 5-day 'window' period and correlated with rate of disease increase after a 7-day 'lag' period. Standard weather variables could explain 20-34% of the disease increase. The relevance of these statistical models to disease prediction is discussed.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The relationship of leaf wetness duration and disease progress of glume blotch, caused byStagonospora nodorum, in winter wheat to standard weather data

1996

View full text Add to dashboard Cite

show abstract

“…Many types of instruments have been constructed for the measurement of surface wetness (Weiss 1990), which has contributed to a lack of standardization in measurement and definition of terms, as previously noted. Until the 1970s, mechanical sensors (Hirst, 1954;Lomas & Shashoua, 1970;Wallin, 1963) were widely used, but they have been largely replaced with electronic types (Schurer & Van Der Wal, 1972). The U.S. National Weather Service was one of the first organizations to use an etched circuit board that has become one of the most widely used sensor designs (Davis & Hughes, 1970).…”

Section: Sensorsmentioning

confidence: 99%

“…Peltier cooled dew point sensors can be an inexpensive and reliable method to determine relative humidity (Bailey, 1999;Griffieon et al, 1992;Vancauwenberghe et al, 1996), although dirt deposits on the mirror surface may compromise their performance (Griffieon et al, 1992). Vincelli and Lorbeer (1988) found that relative humidity could be used to estimate missing surface wetness data; however, several other studies have shown there is a relatively poor correlation between periods of high humidity and surface wetness (Francl & Panigrahi, 1997;Lomas & Shashoua, 1970;Wallin, 1963). The use of high relative humidity instead of surface wetness may result in an overestimation of plant disease risk (Jones et al, 1980).…”

Section: Sensorsmentioning

confidence: 99%

Estimating Surface Wetness on Plants

Magarey

Seem

Weiss

et al. 2015

Agronomy Monographs

View full text Add to dashboard Cite

“…Estes dispositivos são tipicamente muito rudimentares e provêem pouca informação útil, dado que apresenta uma correlação muito baixa com a duração do orvalho (GETZ, 1991). Os instrumentos de molhamento foliar mecânicos foram utilizados intensivamente para medidas de DPM até 1970(LOMAS, 1965LOMAS;SHASHOUA, 1970) e, apesar de suas limitações, estes sensores vem sendo usados até recentemente em vários locais (ZANGVIL, 1996).…”

Section: Tipos De Sensores De Molhamentounclassified

Duração do período de molhamento em vinhedo de 'Niagara Rosada' e sua relação com a ocorrência de míldio (Plasmopara viticola)

Lulu¹

View full text Add to dashboard Cite

Leaf wetness duration in a 'Niagara Rosada' vineyard and its relationships with downy mildew (Plasmopara viticola) occurrence Nowadays, the 'Niagara Rosada' grapevine is the most cultivated table grape variety in the State of São Paulo, Brazil. However, yield and production cost of this grapevine have been affected by fungal diseases, mainly downy mildew, caused by Plasmopara viticola fungus. For controlling this disease, producers have been applied an excessive number of sprays with fungicides. Among the meteorological variables that influence the occurrence of fungal plant diseases, leaf wetness duration (LWD) is one of the most important. The wetness presence on plant surface provides the water required by the phatogens to germinate and to infect leaf tissues. Aiming to subsidize the plant disease warning systems, which has as purpose to rationalize the use of fungicides in the vineyards, the objectives of the present study were: to determine the canopy position of the 'Niagara Rosada' table grape with longer LWD and its correlation with measured standard LWD over turfgrass; 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 the vineyard; and to correlate downy mildew occurrence in the vineyard, without chemical control, with measured LWD at the vineyard (canopy position with longer LWD), with estimated LWD in standard condition over turfgrass for the best model, and with other meteorological variables. LWD was measured in standard condition over turfgrass and in four different canopy positions of the vineyard: at the top of the plants, with sensors facing southwest and northeast (Top-SW and Top-NE), and at the grape bunches height, with sensors facing southwest and northeast (Bottom-SW and Bottom-NE). The downy mildew epidemiology during the grapevine cycle was evaluated without chemical control, using scores ranging from 0 to 4, with nine severity levels, for leaves and bunches of grapevine. When the spatial variability of LWD was studied, no significant difference was observed between the top (1.6 m) and the bottom (1.0 m) of the canopy and also between the southwest and northeast face of the plants. The analysis of the relationship between standard LWD over turfgrass and crop LWD in different positions of the grape canopy showed a define correlation (R 2 = 0.88). Among the LWD estimative methods, CART was the one with the best performance to estimate LWD over turfgrass. The results from this model also presented a good correlation with measured LWD inside the vineyard, showing that LWD can be estimated for this crop with data from a nearby standard weather station. For the downy mildew modeling, LWD also present the best correlations with disease severity in the 'Niagara Rosada' vineyard, showing the great importance of this variable for fungal diseases occurrence in this crop.

show abstract

The performance of three types of leaf-wetness recorders

Cited by 14 publications

References 6 publications

The relationship of leaf wetness duration and disease progress of glume blotch, caused byStagonospora nodorum, in winter wheat to standard weather data

The relationship of leaf wetness duration and disease progress of glume blotch, caused byStagonospora nodorum, in winter wheat to standard weather data

Estimating Surface Wetness on Plants

Duração do período de molhamento em vinhedo de 'Niagara Rosada' e sua relação com a ocorrência de míldio (Plasmopara viticola)

Contact Info

Product

Resources

About