scholarly journals BIOLOGICAL FEATURES OF SPECIES OF PHYTOPATHOLOGICAL FUNGI AFFECTING TOMATOES (LYCOPERSICON ESCULENTUM MILL.) IN THE SOUTHERN REGION OF KAZAKHSTAN

THE BULLETIN ◽  
2021 ◽  
Vol 389 (1) ◽  
pp. 42-49
Author(s):  
G. Babaeva ◽  
N. Salybekova ◽  
A. Serzhanova ◽  
Esin Basim
Keyword(s):  
Late Blight ◽  
Early Blight ◽  
Tomato Fruit ◽  
Growth Period ◽  
Growing Season ◽  
Viral Diseases ◽  
Fruit Storage ◽  
Rural Districts ◽  
Open Ground ◽  
Phytopathogenic Microorganisms

The article considers studies designed to justify the types of pathogens of tomatoes that occur during vegetation and storage, and measures to combat them. The work was carried out in 2019 on a land plot near the rural districts of Babaykorgan, Zhuynek, and Issa of the Turkestan region. As it became known, the growth period of vegetable seedlings depends on the temperature of the soil. In our experience, the seed material was planted in the open ground in early April. The soil was very hot and moist. Depending on the culture and varietal characteristics, the sprouts appeared on 6-15 days after sowing. The results of phytopathological control showed that various varieties of all types of tomatoes were affected by phytopathogenic microorganisms. During the growing season, the most dangerous disease in tomato fruit was apical rot of the fruit, which led to a significant decrease in the yield. The leaves are widely developed early blight and verticillus. Late blight at the end of the growing season was observed in full on both leaves and fruits (developed during fruit storage). When growing tomato crops at two sites was dominated by late blight, early blight, verticillus, viral diseases and apical rot. Based on the results of phytopathological control, it can be concluded that the number of fungal diseases prevailed in plot 1, which is associated with frequent irrigation on this site, its shading and a large number of fruits on plants. Viral diseases prevailed in plot 2, which is explained by weeds clogging the plot.

Pichia kudriavzevii retards fungal decay by influencing the fungal community succession during cherry tomato fruit storage

2020 ◽  
Vol 88 ◽  
pp. 103404 ◽  
Author(s):  
Xia Liu ◽  
Yu Gao ◽  
Hongyuan Yang ◽  
Limei Li ◽  
Yishan Jiang ◽  
...  
Keyword(s):  
Fungal Community ◽  
Tomato Fruit ◽  
Community Succession ◽  
Cherry Tomato ◽  
Fungal Decay ◽  
Fruit Storage ◽  
Pichia Kudriavzevii

SPRAYING TOMATOES FOR THE CONTROL OF LEAF SPOT, EARLY BLIGHT AND LATE BLIGHT

1957 ◽  
Vol 37 (4) ◽  
pp. 385-391
Author(s):  
K. M. Graham ◽  
A. G. Donaldson
Keyword(s):  
Late Blight ◽  
Leaf Spot ◽  
Early Blight ◽  
Tomato Leaf

Tomato leaf spot, early blight, and late blight were controlled effectively in the Ottawa district by six applications of the fixed copper COCS 55 or of Manzate (maneb). The split schedule consisting of three sprays with Manzate, followed by three sprays with COCS 55, or the tank mixture of these two fungicides, gave results comparable to those obtained with each of them alone. Some of the fungicides tested showed a degree of specificity in the control of certain diseases.

scholarly journals Plant Disease Identification Using Shallow Convolutional Neural Network

Agronomy ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2388
Author(s):  
Sk Mahmudul Hassan ◽  
Michal Jasinski ◽  
Zbigniew Leonowicz ◽  
Elzbieta Jasinska ◽  
Arnab Kumar Maji
Keyword(s):  
Deep Learning ◽  
Late Blight ◽  
Early Blight ◽  
Gray Leaf Spot ◽  
Plant Diseases ◽  
Automated Identification ◽  
Average Accuracy ◽  
Proposed Model ◽  
Effective Manner ◽  
Tomato Diseases

Various plant diseases are major threats to agriculture. For timely control of different plant diseases in effective manner, automated identification of diseases are highly beneficial. So far, different techniques have been used to identify the diseases in plants. Deep learning is among the most widely used techniques in recent times due to its impressive results. In this work, we have proposed two methods namely shallow VGG with RF and shallow VGG with Xgboost to identify the diseases. The proposed model is compared with other hand-crafted and deep learning-based approaches. The experiments are carried on three different plants namely corn, potato, and tomato. The considered diseases in corns are Blight, Common rust, and Gray leaf spot, diseases in potatoes are early blight and late blight, and tomato diseases are bacterial spot, early blight, and late blight. The result shows that our implemented shallow VGG with Xgboost model outperforms different deep learning models in terms of accuracy, precision, recall, f1-score, and specificity. Shallow Visual Geometric Group (VGG) with Xgboost gives the highest accuracy rate of 94.47% in corn, 98.74% in potato, and 93.91% in the tomato dataset. The models are also tested with field images of potato, corn, and tomato. Even in field image the average accuracy obtained using shallow VGG with Xgboost are 94.22%, 97.36%, and 93.14%, respectively.

scholarly journals Fungicide Spray Programs for Defender, A New Potato Cultivar with Resistance to Late Blight and Early Blight

Plant Disease ◽  
2007 ◽  
Vol 91 (10) ◽  
pp. 1327-1336 ◽  
Author(s):  
W. R. Stevenson ◽  
R. V. James ◽  
Debra Ann Inglis ◽  
Dennis A. Johnson ◽  
R. Thomas Schotzko ◽  
...  
Keyword(s):  
Late Blight ◽  
Early Blight ◽  
Total Yield ◽  
Development Program ◽  
Potato Cultivar ◽  
Field Tests ◽  
Field Resistance ◽  
Russet Burbank ◽  
Ranger Russet ◽  
Progress Curve

Defender (A90586-11) is a new late blight-resistant potato cultivar which was released from the Tri-State Potato Variety Development Program in 2004. Conventional and reduced fungicide spray programs were compared on Defender and Russet Burbank (3 years) and Ranger Russet (1 year) in Wisconsin experimental field trials. Useful levels of field resistance to both late blight and early blight were observed in Defender in the absence of fungicide sprays and reduced fungicide input programs. Disease progressed slowest on Defender regardless of fungicide program, relative to Russet Burbank and Ranger Russet. Organic, conventional, and reduced fungicide spray programs also were compared on Defender and Russet Burbank in experimental greenhouse and field tests in Washington. Fungicide spray programs performed similarly on both Defender and Russet Burbank; however, area under the disease progress curve values for no-fungicide treatments were either three times (greenhouse) or six times (field) lower on Defender compared with Russet Burbank. Regardless of the fungicide program, total yield was higher for Defender than Russet Burbank. Mean economic returns associated with Defender also were higher than for Russet Burbank ($6,196 versus $4,388/ha). Fungicide and nonfungicide treatment programs generated similar returns on Defender whereas conventional and reduced fungicide programs generated comparable but higher returns than the nonfungicide program on Russet Burbank.

Production and survival of tillers of wheat and their contribution to yield

1974 ◽  
Vol 83 (1) ◽  
pp. 117-124 ◽  
Author(s):  
H. M. Ishag ◽  
M. B. Taha
Keyword(s):  
Grain Yield ◽  
Air Temperature ◽  
High Mortality ◽  
Growth Period ◽  
Dry Weight ◽  
Growing Season ◽  
Sowing Date ◽  
Wheat Cultivars ◽  
Nitrogen Application ◽  
True Leaf

SUMMARYThe effect of sowing date and nitrogen on tillering patterns, survival and contribution of reproductive tillers to grain yield of standard and Mexican wheat cultivars were studied for two seasons.Maximum number of tillers/plant, 3·2–4·5, was observed after 40 and 27 days from sowing for 1970–1 and 1971–2 respectively. The number of ears/plant was 1·4 at the end of the growing season. Varieties differed in tillering, and LRN10 and Giza 155 produced more reproductive tillers than Falchetto and Mexipak. Nitrogen application increased tillering efficiency, i.e. ratio of fertile to total tillers produced. Only 26% of tillers appearing in the axil of the first true leaf (T1) and 10% of tillers in the axil of the second true leaf (T2) survived to produce ears. The high mortality of tillers was attributed to high air temperature prevailing during the growth period (33 °C by day; 18 °C by night). Eared tillers did not die and were self supporting because of the photosynthesis by the ear.Grain weight/tiller was positively correlated with tiller dry weight at heading, r= 0·76–0·96. Main shoots contributed about 81% of the total grain yield and 19% came from T1 and T2 tillers.

scholarly journals Early Blight Control in Potato Using Disease-Orientated Threshold Values

Plant Disease ◽  
2012 ◽  
Vol 96 (1) ◽  
pp. 124-130 ◽  
Author(s):  
J. H. Leiminger ◽  
H. Hausladen
Keyword(s):  
Early Blight ◽  
Disease Incidence ◽  
Growing Season ◽  
Potato Production ◽  
Economic Damage ◽  
Optimal Timing ◽  
Threshold Values ◽  
Fungicide Application ◽  
Disease Threshold ◽  
Starch Yield

Epidemics of early blight caused by Alternaria spp. can cause significant economic damage to potato production if not adequately controlled. In order to improve control of Alternaria spp. in potato, studies were conducted to identify the optimal fungicide strategy and, if possible, to reduce the number of fungicide applications per growing season. Therefore, a disease-threshold-based framework was tested to define the optimal timing of fungicide application. The initiation and subsequent applications of fungicides were based on increases in disease incidence or severity. Adequate disease control was achieved by a three-time application with azoxystrobin, given that the applications were carried out at pivotal times in the epidemic. Targeted applications of fungicides reduced the number of sprayings required to protect starch yield. Results indicate that early blight can be effectively managed by using fungicide application thresholds based on disease progress.

scholarly journals Dependence of the content of ascorbic acid in apples at the beginning and at the end of storage on the hydrothermal conditions of the growing season

2020 ◽  
pp. 24-31
Author(s):  
A. L. Nikitin ◽  
M. A. Makarkina
Keyword(s):  
Ascorbic Acid ◽  
Calculated Data ◽  
Growing Season ◽  
Thermal Coefficient ◽  
Hydrothermal Conditions ◽  
Fruit Storage ◽  
Hydrothermal Coefficient ◽  
Fruit Maturity ◽  
Calendar Dates

The degree of fruit maturity varies from year to year, depending on hydrothermal conditions, and therefore it is impossible to focus only on the calendar dates of harvesting due to their seasonal changes. The keeping capacity and quality of apples have variety specificity and depend, among other factors, on the meteorological conditions of the growing season. The analysis of the quantitative content of ascorbic acid (AA) in the fruits of five new columnar scab immune apple varieties – Vostorg, Zvezda Efira, Poezia, Priokskoye and Sozvezdiye at the beginning and at the end of storage in different years (2012, 2014, 2016, 2018) showed the closest dependence of this parameter on the conditions of humidification of the active growing season (hydro-thermal coefficient (HTC)). The dependence of the AA content in fruits on the hydrothermal coefficient was approximated by the second-order parabola equation. Certain regularity was revealed in the content of AA in fruits depending on HTC. The parabolic curve, reflecting the maximum calculated AA content, increases to maximum values at HTC – 0.85-0.90 at the beginning of fruit storage and 0.79-0.89 at the end of storage. Under droughty conditions, the dependence curve decreases. The comparison of the experimental data with calculated data showed that the correlation relations between them had values from 0.61 to 0.88 at the beginning of storage and 0.40-0.99 at the end. The calculated data can be interpolated, and it makes sense to use HTC as one of the predictor parameters of fruit quality during harvesting and potential keeping capacity of fruits.

scholarly journals Factors affecting the development of Phytophthora infestans on a tomato in the open ground

2020 ◽  
pp. 112-115
Author(s):  
I. Yu. Kondratyeva ◽  
L. K. Gurkina
Keyword(s):  
Late Blight ◽  
Phytophthora Infestans ◽  
Air Temperature ◽  
High Resistance ◽  
Factors Affecting ◽  
Open Ground ◽  
Low Humidity ◽  
Source Resistance ◽  
Increasing Temperature

Relevance and methods. For the Non-chernozem zone, the main factor for the active development of late blight is the low air temperature and its sharp fluctuations during the day, contributing to the formation of increased air humidity and drip-liquid moisture on the plants. In the Moscow region, the causative agent of late blight is manifested almost annually. Populations of Phytophthora infestans are represented by the To and T1 races. Epiphytotic development was observed periodically (1977-1979, 1982, 1986, 1996-1999, 2000, 2001, 2003-2004, 2008-2009, 2013, 2014, 2015, 2016, 2017, 2019) and was provided by the virulent T1 race. Observations showed that epiphytotic situations arose in those years when the minimum air temperature was below long-term average values, and relative humidity and precipitation exceeded them. With a deviation from the norm in the direction of increasing temperature, decreasing rainfall and relatively low humidity, years were observed with a depressive (1992, 1994) or moderate development of the disease (1980, 1981, 1983, 1985, 1987-1991, 2002, 2005-2007, 2010-2012, 2018). Results. As a result of breeding work, a Grot tomato-tolerant tomato variety was obtained, on the basis of which varieties with high resistance Grand, Dubok, Gnom, Chelnok, Patris, Geya, Zolushka, Perst, Severyanka, Blagodatny were obtained. In the general collection of VIR as a source resistance to leaf spot pathogens were registered: Geya (v.k. 14839), Slavyanka (v.k. 14840), Patrice (v.k. 14841), Rossiyanka (v.k. 14842), Krepysh (v.k. 14843), Sibiryachka (v.k. 14444) and line 1079-94 (v.k. 14845) donors, in addition to their high resistance to late blight, have excellent economic characteristics.

scholarly journals Leaf Disease Identification using Convolution Neural Network (CNN)

2020 ◽  
Vol 9 (9) ◽  
pp. 477-481
Keyword(s):  
Neural Network ◽  
Late Blight ◽  
Tomato Plant ◽  
Extraction Methods ◽  
Plant Diseases ◽  
Viral Diseases ◽  
Leaf Disease ◽  
Proposed Model ◽  
Reliable Performance ◽  
First Time

The tomato plant is the most broadly cultivated produce in India. As the Convolutional Neural Network (CNN) which comes under the field of image classification is performing the progressive work, thus using an approach of deep learning which mainly centers on achieving high accuracy of leaf disease of the tomato plant. Therefore, the main objective of this paper is to acquire more reliable performance in the identification of diseases. Amidst various plant diseases that affect leaf comprise of Late blight, bacterial and viral diseases have been chosen to differentiate infected leaves from that of the healthy leaves includes Late blight, bacterial and viral diseases. As we know, none of the other method has been proposed earlier which helps in detecting plant leaf diseases for the first time. Hence the proposed model is designed in such a way that it effectively identifies specific diseases that affect leaves of tomato plants through the use of a dataset containing about 4000 leaf images. CNN achieves an overall accuracy of 96% without implementing any pre-processing and feature extraction methods.

scholarly journals Response of Cell Division and Cell Expansion to Local Fruit Heating in Tomato Fruit

2012 ◽  
Vol 137 (5) ◽  
pp. 294-301 ◽  
Author(s):  
Julienne Fanwoua ◽  
Pieter de Visser ◽  
Ep Heuvelink ◽  
Gerco Angenent ◽  
Xinyou Yin ◽  
...  
Keyword(s):  
Cell Expansion ◽  
Tomato Fruit ◽  
Fruit Size ◽  
Growth Period ◽  
Cell Number ◽  
Fruit Growth ◽  
Growth Responses ◽  
Direction Parallel ◽  
Cell Divisions ◽  
Fruit Skin

To improve our understanding of fruit growth responses to temperature, it is important to analyze temperature effects on underlying fruit cellular processes. This study aimed at analyzing the response of tomato (Solanum lycopersicum) fruit size to heating as affected by changes in cell number and cell expansion in different directions. Individual trusses were enclosed into cuvettes and heating was applied either only during the first 7 days after anthesis (DAA), from 7 DAA until fruit maturity (breaker stage), or both. Fruit size and histological characteristics in the pericarp were measured. Heating fruit shortened fruit growth period and reduced final fruit size. Reduction in final fruit size of early-heated fruit was mainly associated with reduction in final pericarp cell volume. Early heating increased the number of cell layers in the pericarp but did not affect the total number of pericarp cells. These results indicate that in the tomato pericarp, periclinal cell divisions respond differently to temperature than anticlinal or randomly oriented cell divisions. Late heating only decreased pericarp thickness significantly. Continuously heating fruit reduced anticlinal cell expansion (direction perpendicular to fruit skin) more than periclinal cell expansion (direction parallel to fruit skin). This study emphasizes the need to measure cell expansion in more than one dimension in histological studies of fruit.

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