EFFECTS OF BORON AND CALCIUM SPRAYS AND OF MULCH ON CRACKING OF ITALIAN PRUNE

1973 ◽  
Vol 53 (4) ◽  
pp. 827-831 ◽  
Author(s):  
R. A. CLINE ◽  
G. TEHRANI
Keyword(s):  
Soil Moisture ◽  
Fruit Development ◽  
Calcium Concentration ◽  
Foliar Application ◽  
Leaf Tissue ◽  
Weather Conditions ◽  
Prunus Domestica ◽  
Foliar Sprays ◽  
Wide Range ◽  
Fruit Surface

Cracking, a disorder of the fruit of Prunus domestica L., cult Italian (Fellenberg) (Italian prune), occurs on any part of the fruit surface and over a wide range of stage of fruit development. Several treatments were examined to reduce the extent of this disorder in five commercial orchards in the Niagara Peninsula of Ontario. Foliar application of calcium reduced the severity of cracking in several orchards. Cracking was related to the calcium concentration in the fruit but not in the leaf tissue. A mulch applied to conserve soil moisture, or foliar sprays of boron, or both, were unsuccessful in preventing this disorder. The severity of cracking varied from orchard to orchard and year to year and was not related to weather conditions.

scholarly journals Using Decagon EC-5sensors for monitoring soil moisture

2021 ◽  
Vol 4 (3) ◽  
pp. 1-9
Author(s):  
N. A. Shaporina ◽  
E. A. Sayb
Keyword(s):  
Soil Moisture ◽  
Soil Profile ◽  
Technical Specification ◽  
Moisture Flux ◽  
Weather Conditions ◽  
Forest Steppe ◽  
Research Station ◽  
Deep Soil ◽  
High Data ◽  
Wide Range

The aim of the study. To assess the possibilities of using the Decagon EC-5 sensor in research practice, especially under the conditions of its stationary installation; and to study with its help the dynamics of soil profile moistening and moisture migration under different weather conditions. Location and time of the study. The study was carried out on the territory of the Ust-Kamensky (forest-steppe) research station of the Institute of Soil Science and Agrochemistry of the Siberian Branch of the Russian Academy of Sciences (55.005507 N, 83.858635 E). The object of the study was the dark gray forest soil (Luvic Greyzemic Phaeozem). Five Decagon EC-5 sensors were installed at 9, 13, 18, 22 and 27cm depths in a small (30cm deep) soil pit and connected to the Em50 recorder. The necessary calibration was carried out beforehand. The sensors functioned from June 13 to July 7, 2017. Main results. The study showed that this device is suitable for a wide range of applications. According to the sensor readings, it was possible to trace the migration of moisture within the soil profile, as well as to differentiate it into gravitational and capillary water, as well as to establish the fact of precipitation with an accuracy of an hour and to calculate the precipitated amount. Statistical analysis of the obtained data showed low values of data variance and the coefficient of variation, which indicated high data homogeneity. The use of these sensors can improve the traditional flood method for determining the maximum soil water holding capacity. Moreover, detailed recording of soil moisture, provided by Decagon EC-5 sensors, in combination with Thermochron sensors for soil temperature recording, allows to study quantitative indicators of thermal gradient moisture flux at a new level. Conclusions. The study showed that Decagon EC-5 sensors comply with their technical specification and have good prospects for usage both in research and agricultural production. Provided its preliminary calibration and producing the calibration curves for the studied soils, the sensors allow quick and accurate measurement of the soil volumetric moisture content. The frequency and rate of sensor readings takes research on the dynamics and migration of moisture in soils to an entirely new level.

scholarly journals Application of Sentinel-1B Polarimetric Observations to Soil Moisture Retrieval Using Neural Networks: Case Study for Bare Siberian Chernozem Soil

2021 ◽  
Vol 13 (17) ◽  
pp. 3480
Author(s):  
Konstantin Muzalevskiy ◽  
Anatoly Zeyliger
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Surface Roughness ◽  
Soil Moisture ◽  
Soil Surface ◽  
Weather Conditions ◽  
Agricultural Field ◽  
Wide Range ◽  
Soil Surface Roughness ◽  
The Relationship

Sentinel-1 is currently the only synthetic-aperture radar, which radar measurements of the earth’s surface to be carried out, regardless of weather conditions, with high resolution up to 5–40 m and high periodicity from several to 12 days. Sentinel-1 creates a technological platform for the development of new globally remote sensing algorithms of soil moisture, not only for hydrological and climatic model applications, but also on a single field scale for individual farms in precision farming systems used. In this paper, the potential of soil moisture remote sensing using polarimetric Sentinel-1B backscattering observations was studied. As a test site, the fallow agricultural field with bare soil near the Minino village (56.0865°N, 92.6772°E), Krasnoyarsk region, the Russian Federation, was chosen. The relationship between the cross-polarized ratio, reflectivity, and the soil surface roughness established Oh used as a basis for developing the algorithm of soil moisture retrieval with neural networks (NNs) computational model. Two NNs is used as a universal regression technique to establish the relationship between scattering anisotropy, entropy and backscattering coefficients measured by the Sentinel-1B on the one hand and reflectivity on the other. Finally, the soil moisture was found from the soil reflectivity in solving the inverse problem using the Mironov dielectric model. During the field campaign from 21 May to 25 August 2020, it was shown that the proposed approach allows us to predict soil moisture values in the layer thickness of 0.00–0.05 m with the root-mean-square error and determination coefficient not worse than 3% and 0.726, respectively. The validity of the proposed approach needs additional verification on a wider dataset using soils of different textures, a wide range of variations in soil surface roughness, and moisture.

scholarly journals Ontogenetic Changes in Calcium Concentration and Content in Pickling Cucumber Fruit as Influenced by Genotype and Environment

1990 ◽  
Vol 115 (4) ◽  
pp. 555-558 ◽  
Author(s):  
Cheryl Ann Engelkes ◽  
Irvin Widders ◽  
Hugh Price
Keyword(s):  
Environmental Conditions ◽  
Fruit Development ◽  
Calcium Concentration ◽  
Accumulation Rate ◽  
Leaf Tissue ◽  
Dry Weight ◽  
Ontogenetic Changes ◽  
Fresh Weight ◽  
Pickling Cucumber ◽  
Cucumber Fruit

A field experiment was conducted to quantify the ontogenetic changes in Ca concentration and content of pickling cucumber fruits as influenced by environmental conditions and genotype. Pericarp tissue Ca concentrations (1.1% to 0.7% of dry weight) were higher but declined less rapidly during fruit development than endocarp concentrations (0.8% to 0.2% of dry weight). About 90% of net fruit Ca content accumulated within the pericarp of ≈150 g fresh weight fruit, the rest in the endocarp. The rate of Ca accumulation was highly variable during fruit ontogeny but was closely correlated with growth rate (grams fresh weight/day). Environmental conditions had the largest effect on Ca accumulation rate. Fruit tissue Ca concentrations were affected both by genotype and the cultural environment, especially at the later stages of fruit development. Calcium concentrations (1.5 to ≈3.0% of dry weight) in fully expanded leaf tissue were higher than in rapidly growing fruit tissues on the same plants.

Vulnerability of sweet cherry cultivars to continuous periods of spring frosts in Plovdiv, Bulgaria

2020 ◽  
Vol 12 (4) ◽  
pp. 348-352
Author(s):  
S. Malchev ◽  
S. Savchovska
Keyword(s):  
Sweet Cherry ◽  
Weather Conditions ◽  
Frost Damage ◽  
Cold Weather ◽  
Bud Burst ◽  
Intermediate Group ◽  
Air Temperatures ◽  
Wide Range ◽  
Group Form ◽  
Sweet Cherry Cultivars

Abstract. The periods with continuous freezing air temperatures reported during the spring of 2020 (13 incidents) affected a wide range of local and introduced sweet cherry cultivars in the region of Plovdiv. They vary from -0.6°C on March 02 to -4.9°C on March 16-17. The duration of influence of the lowest temperatures is 6 and 12 hours between March 16 and 17. The inspection of fruit buds and flowers was conducted twice (on March 26 and April 08) at different phenological stages after continuous waves of cold weather conditions alternated with high temperatures. During the phenological phase ‘bud burst’ (tight cluster or BBCH 55) some of the flowers in the buds did not develop further making the damage hardly detectable. The most damaged are hybrid El.28-21 (95.00%), ‘Van’ (91.89%) and ‘Bing’ (89.41%) and from the next group ‘Lapins’ (85.98%) and ‘Rosita’ (83.33%). A larger intermediate group form ‘Kossara’ (81.67%), ‘Rozalina’ (76.00%), ‘Sunburst’ (75.00%), ‘Bigarreau Burlat’ (69.11%) and ‘Kuklenska belitza’ (66.67%). Candidate-cultivar El.17-90 ‘Asparuh’ has the lowest frost damage values of 55.00% and El.17-37 ‘Tzvetina’ with damage of 50.60%.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Modeling of Yield Losses Caused by Potato Late Blight on Eight Cultivars with Different Levels of Resistance to Phytophthora infestans

Plant Disease ◽  
2012 ◽  
Vol 96 (7) ◽  
pp. 935-942 ◽  
Author(s):  
Toky Rakotonindraina ◽  
Jean-Éric Chauvin ◽  
Roland Pellé ◽  
Robert Faivre ◽  
Catherine Chatot ◽  
...  
Keyword(s):  
Late Blight ◽  
Phytophthora Infestans ◽  
Relative Yield ◽  
Weather Conditions ◽  
Potato Late Blight ◽  
Yield Losses ◽  
Predictive Quality ◽  
Wide Range ◽  
Cultivar Susceptibility

The Shtienberg model for predicting yield loss caused by Phytophthora infestans in potato was developed and parameterized in the 1990s in North America. The predictive quality of this model was evaluated in France for a wide range of epidemics under different soil and weather conditions and on cultivars different than those used to estimate its parameters. A field experiment was carried out in 2006, 2007, 2008, and 2009 in Brittany, western France to assess late blight severity and yield losses. The dynamics of late blight were monitored on eight cultivars with varying types and levels of resistance. The model correctly predicted relative yield losses (efficiency = 0.80, root mean square error of prediction = 13.25%, and bias = –0.36%) as a function of weather and the observed disease dynamics for a wide range of late blight epidemics. In addition to the evaluation of the predictive quality of the model, this article provides a dataset that describes the development of various late blight epidemics on potato as a function of weather conditions, fungicide regimes, and cultivar susceptibility. Following this evaluation, the Shtienberg model can be used with confidence in research and development programs to better manage potato late blight in France.

A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

2008 ◽  
Vol 88 (5) ◽  
pp. 761-774 ◽  
Author(s):  
J. A. P. Pollacco
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Bulk Density ◽  
Soil Texture ◽  
The United States ◽  
Pedotransfer Functions ◽  
Pedotransfer Function ◽  
Data Set ◽  
Wide Range ◽  
Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

Effect of foliar application of chelated copper and manganese on yield components and fibre properties of Egyptian cotton (Gossypium barbadense)

1993 ◽  
Vol 121 (2) ◽  
pp. 193-198 ◽  
Author(s):  
Z. M. Sawan ◽  
M. H. Mahmoud ◽  
B. R. Gregg
Keyword(s):  
Yield Components ◽  
Agricultural Research ◽  
Foliar Application ◽  
Field Studies ◽  
Gossypium Barbadense ◽  
Research Centre ◽  
Fibre Properties ◽  
Foliar Sprays ◽  
Egyptian Cotton ◽  
Cotton Cultivar

SUMMARYA decline in supplies of organic manures and the increased use of chemical fertilizers has led to a decrease in the micronutrient content of the soil, with attendant effects on yield.Field studies were conducted in 1986 and 1987 at the Giza Agricultural Research Centre, Egypt, to determine the effect of Cu-EDTA and Mn-EDTA foliar sprays on growth, mineral content, yield components and fibre properties of the Egyptian cotton cultivar Giza 75 (Gossypium barbadense L.).All combinations used significantly increased the uptake of Cu and Mn and the dry matter yield. The earliness of harvest and the value of yield components were all increased by the application of Cu or Mn; 25 mg/1 of both Cu and Mn gave the highest values. Lint percentage and fibre properties were not significantly affected.This study indicated that the yield of cotton, grown under otherwise standard conditions, may be increased by foliar sprays of Cu-EDTA and Mn-EDTA combined.

scholarly journals Impact of Foliar Application of Amino Acids on Total Phenols, Phenolic Acids Content of Different Mints Varieties under the Field Condition

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 599
Author(s):  
Živilė Tarasevičienė ◽  
Aloyzas Velička ◽  
Aurelija Paulauskienė
Keyword(s):  
Amino Acids ◽  
Phenolic Compounds ◽  
Phenolic Acids ◽  
Foliar Application ◽  
Mentha Piperita ◽  
Total Phenolic ◽  
Total Phenol Content ◽  
Individual Response ◽  
Total Phenols ◽  
Wide Range

Phenolic compounds have a number of benefits to human health and can be used as preventive compounds for the development of some chronic diseases. Mentha plants are not only a good source of essential oils, but also contain significant levels of wide range of phenolic compounds. The aim of this research was to investigate the possibility to increase phenols content in Mentha plants under the foliar application with L-phenylalanine, L-tryptophan, L-tyrosine at two concentrations (100 mg L−1 and 200 mg L−1) and to create preconditions for using this plant for even more diverse purposes. Quantitative and qualitative analyses of phenols in mints were performed by HPLC method. Foliar application of amino acids increased the total phenol content from 1.22 to 3.51 times depending on the treatment and mint variety. The most pronounced foliar application to total phenols content was tryptophane especially in Mentha piperita “Swiss”. Mentha piperita “Swiss” was affected most by foliar application and the amount of total phenolic acids depending on the treatment ranged from 159.25 to 664.03 mg 100 g−1 (DW), respectively, non-sprayed and sprayed with tryptophane 100 mg L−1. Our results suggest that the biophenol content varies according to such factors as foliar application and variety, and every single mint variety has individual response to different applications of amino acids.

scholarly journals A Review of Detection and Removal of Raindrops in Automotive Vision Systems

2021 ◽  
Vol 7 (3) ◽  
pp. 52
Author(s):  
Yazan Hamzeh ◽  
Samir A. Rawashdeh
Keyword(s):  
Detrimental Effect ◽  
Weather Conditions ◽  
Traffic Sign ◽  
Survey Paper ◽  
Sign Recognition ◽  
Adverse Weather Conditions ◽  
Wide Range ◽  
Adverse Weather ◽  
Protective Cover

Research on the effect of adverse weather conditions on the performance of vision-based algorithms for automotive tasks has had significant interest. It is generally accepted that adverse weather conditions reduce the quality of captured images and have a detrimental effect on the performance of algorithms that rely on these images. Rain is a common and significant source of image quality degradation. Adherent rain on a vehicle’s windshield in the camera’s field of view causes distortion that affects a wide range of essential automotive perception tasks, such as object recognition, traffic sign recognition, localization, mapping, and other advanced driver assist systems (ADAS) and self-driving features. As rain is a common occurrence and as these systems are safety-critical, algorithm reliability in the presence of rain and potential countermeasures must be well understood. This survey paper describes the main techniques for detecting and removing adherent raindrops from images that accumulate on the protective cover of cameras.

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