Spatial distribution and sampling plan of the phytophagous stink bug complex in different soybean production systems

2018 ◽  
Vol 143 (3) ◽  
pp. 236-249
Author(s):  
Marcos Gino Fernandes ◽  
Eduardo Neves Costa ◽  
Leonardo Hiroito Cavada ◽  
Thiago Alexandre Mota ◽  
Paulo Rogério Beltramin da Fonseca
Keyword(s):  
Spatial Distribution ◽  
Production Systems ◽  
Sampling Plan ◽  
Stink Bug ◽  
Soybean Production

scholarly journals Flood Risk and Adaptation Strategies for Soybean Production Systems on the Flood-Prone Pampas under Climate Change

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1187
Author(s):  
Wouter Julius Smolenaars ◽  
Spyridon Paparrizos ◽  
Saskia Werners ◽  
Fulco Ludwig
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Risk Perceptions ◽  
Production Systems ◽  
Adaptation Strategies ◽  
Flood Events ◽  
Climate Data ◽  
Soybean Production ◽  
Drying Trend ◽  
Sowing Season

In recent decades, multiple flood events have had a devastating impact on soybean production in Argentina. Recent advances suggest that the frequency and intensity of destructive flood events on the Argentinian Pampas will increase under pressure from climate change. This paper provides bottom-up insight into the flood risk for soybean production systems under climate change and the suitability of adaptation strategies in two of the most flood-prone areas of the Pampas region. The flood risk perceptions of soybean producers were explored through interviews, translated into climatic indicators and then studied using a multi-model climate data analysis. Soybean producers perceived the present flood risk for rural accessibility to be of the highest concern, especially during the harvest and sowing seasons when heavy machinery needs to reach soybean lots. An analysis of climatic change projections found a rising trend in annual and harvest precipitation and a slight drying trend during the sowing season. This indicates that the flood risk for harvest accessibility may increase under climate change. Several adaptation strategies were identified that can systemically address flood risks, but these require collaborative action and cannot be undertaken by individual producers. The results suggest that if cooperative adaptation efforts are not made in the short term, the continued increase in flood risk may force soybean producers in the case study locations to shift away from soybean towards more robust land uses.

scholarly journals Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 157-172
Author(s):  
Shankar G. Shanmugam ◽  
Normie W. Buehring ◽  
Jon D. Prevost ◽  
William L. Kingery
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
Community Composition ◽  
Production System ◽  
Soil Microbial Community ◽  
Production Systems ◽  
Bacterial Community Composition ◽  
Soybean Production ◽  
Soil Microbial ◽  
Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

scholarly journals Within-Field Spatial Distribution of Stink Bug (Hemiptera: Pentatomidae)-Induced Boll Injury in Commercial Cotton Fields of the Southeastern United States

2014 ◽  
Vol 43 (3) ◽  
pp. 744-752 ◽  
Author(s):  
Ishakh Pulakkatu-Thodi ◽  
Dominic D. Reisig ◽  
Jeremy K. Greene ◽  
Francis P. F. Reay-Jones ◽  
Michael D. Toews
Keyword(s):  
United States ◽  
Spatial Distribution ◽  
Southeastern United States ◽  
Stink Bug ◽  
Cotton Fields

scholarly journals Spatial distribution, temporal stability, and yield loss estimates for annual grasses and common ragweed (Ambrosia artimisiifolia) in a corn/soybean production field over nine years

Weed Science ◽  
2006 ◽  
Vol 54 (02) ◽  
pp. 380-390 ◽  
Author(s):  
Sharon A. Clay ◽  
Bruce Kreutner ◽  
David E. Clay ◽  
Cheryl Reese ◽  
Jonathan Kleinjan ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Weed Management ◽  
Yield Loss ◽  
Temporal Stability ◽  
Grid Cell ◽  
Specific Information ◽  
Common Ragweed ◽  
Soybean Production ◽  
Time Space ◽  
Annual Grasses

Weeds generally occur in patches in production fields. Are these patches spatially and temporally stable? Do management recommendations change on the basis of these data? The population density and location of annual grass weeds and common ragweed were examined in a 65-ha corn/soybean production field from 1995 to 2004. Yearly treatment recommendations were developed from field means, medians, and kriging grid cell densities, using the hyperbolic yield loss (YL) equation and published incremental YL values (I), maximum YL values (A), and YL limits of 5, 10, or 15%. Mean plant densities ranged from 12 to 131 annual grasses m−2and < 1 to 37 common ragweed m−2. Median weed densities ranged from 0 to 40 annual grasses m−2and were 0 for common ragweed. The grassIvalues used to estimate corn YL were 0.1 and 2% and treatment was recommended in only 1 yr when the highIvalue and either the mean or median density was used. The grassIvalues used for soybean were 0.7 and 10% and estimated YL was over 10% all years, regardless ofIvalue. The common ragweedIvalues were 4.5 and 6% for corn and 5.1 and 15.6% for soybean. On the basis of mean densities, fieldwide treatment would have been recommended in 6 of 9 yr but in no years when the median density was used. Recommendations on the basis of grid cell weed density and kriging ranged from > 80% of the field treated for grass weeds in 3 of 4 yr in soybean to < 20% of the field treated for common ragweed in 2002 and 2004 (corn). Grass patches were more stable in time, space, and density than common ragweed patches. Population densities and spatial distribution generally were variable enough so that site-specific information within this field would improve weed management decisions.

scholarly journals SPATIAL DISTRIBUTION AND SEQUENTIAL SAMPLING OF Brevipalpus phoenicis IN CITRUS

2016 ◽  
Vol 38 (4) ◽  
Author(s):  
WALTER MALDONADO JR ◽  
JOSÉ CARLOS BARBOSA ◽  
MARÍLIA GREGOLIN COSTA ◽  
PAULO CÉSAR TIBURCIO GONÇALVES ◽  
TIAGO ROBERTO DOS SANTOS
Keyword(s):  
Spatial Distribution ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Sequential Sampling ◽  
Sampling Plan ◽  
Goodness Of Fit Test ◽  
Control Plan ◽  
Sequential Sampling Plan ◽  
Brevipalpus Phoenicis

ABSTRACT Among the pests of citrus, one of the most important is the red and black flat mite Brevipalpus phoenicis (Geijskes), which transmits the Citrus leprosis virus C (CiLV-C).When a rational pest control plan is adopted, it is important to determine the correct timing for carrying out the control plan. Making this decision demands constant follow-up of the culture through periodic sampling where knowledge about the spatial distribution of the pest is a fundamental part to improve sampling and control decisions. The objective of this work was to study the spatial distribution pattern and build a sequential sampling plan for the pest. The data used were gathered from two blocks of Valencia sweet orange on a farm in São Paulo State, Brazil, by 40 inspectors trained for the data collection. The following aggregation indices were calculated: variance/ mean ratio, Morisita index, Green’s coefficient, and k parameter of the negative binomial distribution. The data were tested for fit with Poisson and negative binomial distributions using the chi-square goodness of fit test. The sequential sampling was developed using Wald’s Sequential Probability Ratio Test and validated through simulations. We concluded that the spatial distribution of B. phoenicis is aggregated, its behavior best fitted to the negative binomial distribution and we built and validated a sequential sampling plan for control decision-making.

Utility of Interseeded Winter Cereal Rye in Organic Soybean Production Systems

2004 ◽  
Vol 96 (1) ◽  
pp. 281 ◽  
Author(s):  
Kurt D. Thelen ◽  
Dale R. Mutch ◽  
Todd E. Martin
Keyword(s):  
Production Systems ◽  
Winter Cereal ◽  
Soybean Production ◽  
Cereal Rye

Yield Gaps and Yield Relationships in Central U.S. Soybean Production Systems

2014 ◽  
Vol 106 (2) ◽  
pp. 560-566 ◽  
Author(s):  
D. B. Egli ◽  
J. L. Hatfield
Keyword(s):  
Production Systems ◽  
Soybean Production ◽  
Yield Gaps
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