Historical crop yield losses due to plant diseases

2017 ◽  
pp. 171-182
Author(s):  
S. G. Borkar
2021 ◽  
Vol 11 (5) ◽  
pp. 2282
Author(s):  
Masudulla Khan ◽  
Azhar U. Khan ◽  
Mohd Abul Hasan ◽  
Krishna Kumar Yadav ◽  
Marina M. C. Pinto ◽  
...  

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.


2015 ◽  
Vol 33 (3) ◽  
pp. 607-614
Author(s):  
G. A. M. PEREIRA ◽  
L. H. BARCELLOS JR ◽  
D. V. SILVA ◽  
R. R. BRAGA ◽  
M. M. TEIXEIRA ◽  
...  

ABSTRACTInadequate herbicide application can result in failures in weed control and/or poisoning of the crops, resulting in yield losses. In this research were assessed the effects of the sprayer nozzle boom height in the distribution of the spray solution for weed control, influencing intoxication of beans and crop yield. Experiments were conducted in laboratory and field conditions. In laboratory, the performance of flat spray tip TT 11002 was assessed at heights 0.20, 0.30, 0.40 and 0.50 meters with respect to the target surface. In the field the same heights were assessed in applications of herbicides fomesafen, fluazifop-P-butyl and fomesafen + fluazifop-P-butyl. There was an inverse relationship between the height of the spray boom and the coefficients of variation of the patterns. The mixture better efficiency in a tank of fluazifop-P-butyl + fomesafen was obtained with the height of 0.50 m from the target. This treatment resulted in better weed control, lower poisoning of the bean plants and better crop yield rates.


2010 ◽  
Vol 11 (1) ◽  
pp. 5 ◽  
Author(s):  
Stephen R. Koenning ◽  
J. Allen Wrather

Research must focus on management of diseases that cause extensive losses, especially when funds for research are limited. Knowledge of the losses caused by various soybean diseases is essential when prioritizing research budgets. The objective of this project was to compile estimates of soybean yield potential losses caused by diseases for each soybean producing state in the United States from 2006 to 2009. This data is of special interest since the 4-year period summarized in this report, permits an examination of the impact of soybean rust that was first reported in the United States in 2004. Thus, in addition to the goal of providing this information to aid funding agencies and scientists in prioritizing research objectives and budgets, an examination of the impact of soybean rust on soybean yield losses relative to other diseases is warranted. Yield losses caused by individual diseases varied among states and years. Soybean cyst nematode caused more yield losses than any other disease during 2006 to 2009. Seedling diseases, Phytophthora root and stem rot, sudden death syndrome, Sclerotinia stem rot, and charcoal rot ranked in the top six of diseases that caused yield loss during these years. Soybean yield losses due to soybean rust and Sclerotinia stem rot varied greatly over years, especially when compared to other diseases. Accepted for publication 21 October 2010. Published 22 November 2010.


Weed Science ◽  
1995 ◽  
Vol 43 (3) ◽  
pp. 381-388 ◽  
Author(s):  
Roberte M. D. Makowski

The competitive ability of annual round-leaved mallow was determined in spring wheat and lentil at Indian Head and Regina, Saskatchewan, in 1985 and 1986 using paired quadrats. Significant biomass and seed yield loss occurred in three of four tests in lentil and two of three tests in spring wheat. Differences in numbers of wheat tillers produced between weedy and weed-free plots were found in three of four tests. A two-variable model comprised of early season crop density loss and round-leaved mallow biomass best accounted for the majority of variation in crop yield loss for both lentil and wheat, and tiller density loss in wheat. In 1985 at Indian Head, where no yield loss occurred for either wheat or lentil, round-leaved mallow had been seeded immediately before the crop. Greater yield losses occurred at Regina, in the presence of an older, well-established infestation. In the years and locations with the greatest crop yield losses, round-leaved mallow emerged before the crop causing poor crop emergence. At Regina in 1986, crop yield losses were more than 60% in wheat and 90 to 100% in lentil because of large differences in crop density between weed-free and weedy subplots. Round-leaved mallow exhibited great variability in growth, producing more biomass per plant, more capsules per plant, and more capsules per gram of biomass in the less competitive crop, lentil, than in wheat. Density and biomass of round-leaved mallow were not correlated; with a density of 200 plants m−2, round-leaved mallow biomass in wheat ranged from 100 to 500 g m−2; while in lentil, from 200 to as high as 1000 g m−2, approximately double the range found in wheat. The type of round-leaved mallow infestation (newly seeded or well-established) and environmental conditions (mainly early season precipitation) account for differences between sites and between years.


1974 ◽  
Vol 14 (70) ◽  
pp. 656 ◽  
Author(s):  
DJ Gilbey

The effect of doublegee (Emex australis) density on wheat yield was studied in a field trial. Percentage yield reduction (y) was related to doublegee plants m-2 at 1 week (x1) and 8 weeks (x2) after seeding thus: y = 10.3 + 0.24 x1 r = 0.78*** y = 5.6 + 0.44 x2 r = 0.86*** showing that estimates of doublegee density could be used for forecasting crop yield losses before it is too late to spray. No further yield loss occurred when x1 was greater than 120 plants metre-2. Doublegee seedling mortality that occurred during the seven weeks between plant counts was strongly related to the initial counts (x1) thus: r = 0.88***.


Weed Science ◽  
1996 ◽  
Vol 44 (3) ◽  
pp. 545-554 ◽  
Author(s):  
David Chikoye ◽  
Leslie A. Hunt ◽  
Clarence J. Swanton

The influence of weeds on crop yield is not only dependent on weed-related factors such as density and time of emergence, but also on environmental and management factors that affect both the weed and crop through time. This study was undertaken to develop the first physiologically based dry bean model that would account for the influence of weed competition. The specific objective was to develop a model that would account for the influence of weed competition on crop yield, and to use this model to test the hypothesis that crop yield losses resulted from competition for photosynthetically active radiation (PAR). To this end, a model that simulated the growth and development of dry bean was developed. The model performed daily calculations and simulated the phenology, leaf area expansion, dry matter production and distribution, and grain yield of dry bean based on weather and management information, but assumed adequate water and nutrients. The model was calibrated without weed competition at two locations and yr, and for these situations, adequately described the growth and development of the crop. Simulations were then run for five common ragweed densities and two times of emergence. Common ragweed leaf area was read into the model from input files and used to simulate weed shading. Shading of the dry bean canopy by common ragweed accounted for about 50 to 70% of the yield losses observed in field studies when weeds emerged with the crop. Weed shading did not account for the yield reduction measured from weeds that emerged at the second trifoliate stage of crop growth. The agreement between model predictions and field studies was consistent with the hypothesis that competition for PAR was a principal factor in weed-crop interaction. The ability to account for differences in weed densities, management, and environmental conditions suggested that modeling was a useful tool for evaluating the interaction among weeds and crops.


2017 ◽  
Vol 11 ◽  
Author(s):  
Raghunath Subedi ◽  
Chiara Bertora ◽  
Laura Zavattaro ◽  
Carlo Grignani

Biochar (BC) from biomass waste pyrolysis has been widely studied due to its ability to increase carbon (C) sequestration, reduce greenhouse gas (GHG) emissions, and enhance both crop growth and soil quality. This review summarizes the current knowledge of BC production, characterization, and types, with a focus on its positive effects on crop yield and soil properties versus the unintended risks associated with these effects. Biochar-amended soils enhance crop growth and yield via several mechanisms: expanded plant nutrient and water availability through increased use efficiencies, improved soil quality, and suppression of soil and plant diseases. Yield response to BC has been shown to be more evident in acidic and sandy soils than in alkaline and fine-textured soils. Biochar composition and properties vary considerably with feedstock and pyrolysis conditions so much that its concentrations of toxic compounds and heavy metals can negatively impact crop and soil health. Consequently, more small-scale and greenhouse-sited studies are in process to investigate the role of BC/soil/crop types on crop growth, and the mechanisms by which they influence crop yield. Similarly, a need exists for long-term, field-scale studies on the effects (beneficial and harmful) of BC amendment on soil health and crop yields, so that production guidelines and quality standards may be developed for BCs derived from a range of feedstocks.


Plant Disease ◽  
2014 ◽  
Vol 98 (7) ◽  
pp. 864-875 ◽  
Author(s):  
E. J. Sikora ◽  
T. W. Allen ◽  
K. A. Wise ◽  
G. Bergstrom ◽  
C. A. Bradley ◽  
...  

Existing crop monitoring programs determine the incidence and distribution of plant diseases and pathogens and assess the damage caused within a crop production region. These programs have traditionally used observed or predicted disease and pathogen data and environmental information to prescribe management practices that minimize crop loss. Monitoring programs are especially important for crops with broad geographic distribution or for diseases that can cause rapid and great economic losses. Successful monitoring programs have been developed for several plant diseases, including downy mildew of cucurbits, Fusarium head blight of wheat, potato late blight, and rusts of cereal crops. A recent example of a successful disease-monitoring program for an economically important crop is the soybean rust (SBR) monitoring effort within North America. SBR, caused by the fungus Phakopsora pachyrhizi, was first identified in the continental United States in November 2004. SBR causes moderate to severe yield losses globally. The fungus produces foliar lesions on soybean (Glycine max) and other legume hosts. P. pachyrhizi diverts nutrients from the host to its own growth and reproduction. The lesions also reduce photosynthetic area. Uredinia rupture the host epidermis and diminish stomatal regulation of transpiration to cause tissue desiccation and premature defoliation. Severe soybean yield losses can occur if plants defoliate during the mid-reproductive growth stages. The rapid response to the threat of SBR in North America resulted in an unprecedented amount of information dissemination and the development of a real-time, publicly available monitoring and prediction system known as the Soybean Rust-Pest Information Platform for Extension and Education (SBR-PIPE). The objectives of this article are (i) to highlight the successful response effort to SBR in North America, and (ii) to introduce researchers to the quantity and type of data generated by SBR-PIPE. Data from this system may now be used to answer questions about the biology, ecology, and epidemiology of an important pathogen and disease of soybean.


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