Binomial Sequential Sampling Plans for Cereal Aphids (Homoptera: Aphididae) in Spring Wheat

1997 ◽  
Vol 90 (4) ◽  
pp. 967-975 ◽  
Author(s):  
Philip J. Boeve ◽  
Michael J. Weiss
Keyword(s):  
Spring Wheat ◽  
Sequential Sampling ◽  
Cereal Aphids ◽  
Sampling Plans

SPATIAL DISTRIBUTION AND SAMPLING PLANS WITH FIXED LEVELS OF PRECISION FOR CEREAL APHIDS (HOMOPTERA: APHIDIDAE) INFESTING SPRING WHEAT

1998 ◽  
Vol 130 (1) ◽  
pp. 67-77 ◽  
Author(s):  
Philip J. Boeve ◽  
Michael Weiss
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Spring Wheat ◽  
Rhopalosiphum Padi ◽  
Aphid Population ◽  
Management Decision ◽  
Cereal Aphids ◽  
Sampling Plans ◽  
Taylor’S Power Law ◽  
Taylor's Power Law

AbstractThree cereal aphids, Rhopalosiphum padi (L.), Schizaphis graminum (Rondani), and Sitobion avenae (F.), invade wheat fields in the northern Great Plains each spring, and populations occasionally reach economic levels. The first objective of this study was to describe the spatial distribution of three species of cereal aphids infesting hard red spring wheat (Triticum aestivum L.). The second objective was to develop two sampling plans for cereal aphids using individual stems as the sampling unit, a sampling plan with fixed levels of precision and a sequential sampling decision plan based on total numbers of aphids present. Aphid population estimates were collected from 47 eastern North Dakota spring wheat fields during 1993–1995. The number of aphids per stem were counted on 100–350 stems per field. Taylor’s power law and Iwao’s patchiness regression were used to analyze the spatial distribution of the aphids. Rhopalosiphum padi and S. avenae exhibited an aggregated distribution, whereas S. graminum was distributed randomly in the field. Taylor’s power law provided a better fit to the data than Iwao’s patchiness regression. Sample size requirements for precision levels of 0.10, 0.15, and 0.25 were estimated with Taylor’s regression coefficients. Required sample sizes increased with decreased aphid populations and increased levels of precision. The two sampling plans presented should be useful for research on cereal aphid population dynamics and pest management decision making in spring wheat.

scholarly journals Sequential Sampling for Estimation and Classification of the Incidence of Hop Powdery Mildew II: Cone Sampling

Plant Disease ◽  
2007 ◽  
Vol 91 (8) ◽  
pp. 1013-1020 ◽  
Author(s):  
David H. Gent ◽  
William W. Turechek ◽  
Walter F. Mahaffee
Keyword(s):  
Powdery Mildew ◽  
Binomial Distribution ◽  
Disease Incidence ◽  
Sequential Sampling ◽  
Model Construction ◽  
Data Sets ◽  
Data Set ◽  
Sampling Plans ◽  
Simulated Sampling

Sequential sampling models for estimation and classification of the incidence of powdery mildew (caused by Podosphaera macularis) on hop (Humulus lupulus) cones were developed using parameter estimates of the binary power law derived from the analysis of 221 transect data sets (model construction data set) collected from 41 hop yards sampled in Oregon and Washington from 2000 to 2005. Stop lines, models that determine when sufficient information has been collected to estimate mean disease incidence and stop sampling, for sequential estimation were validated by bootstrap simulation using a subset of 21 model construction data sets and simulated sampling of an additional 13 model construction data sets. Achieved coefficient of variation (C) approached the prespecified C as the estimated disease incidence, [Formula: see text], increased, although achieving a C of 0.1 was not possible for data sets in which [Formula: see text] < 0.03 with the number of sampling units evaluated in this study. The 95% confidence interval of the median difference between [Formula: see text] of each yard (achieved by sequential sampling) and the true p of the original data set included 0 for all 21 data sets evaluated at levels of C of 0.1 and 0.2. For sequential classification, operating characteristic (OC) and average sample number (ASN) curves of the sequential sampling plans obtained by bootstrap analysis and simulated sampling were similar to the OC and ASN values determined by Monte Carlo simulation. Correct decisions of whether disease incidence was above or below prespecified thresholds (pt) were made for 84.6 or 100% of the data sets during simulated sampling when stop lines were determined assuming a binomial or beta-binomial distribution of disease incidence, respectively. However, the higher proportion of correct decisions obtained by assuming a beta-binomial distribution of disease incidence required, on average, sampling 3.9 more plants per sampling round to classify disease incidence compared with the binomial distribution. Use of these sequential sampling plans may aid growers in deciding the order in which to harvest hop yards to minimize the risk of a condition called “cone early maturity” caused by late-season infection of cones by P. macularis. Also, sequential sampling could aid in research efforts, such as efficacy trials, where many hop cones are assessed to determine disease incidence.

Trophic interactions between three species of cereal aphid (Hemiptera: Aphididae) and spring wheat (Poaceae): implications for pest management

2007 ◽  
Vol 139 (6) ◽  
pp. 850-863 ◽  
Author(s):  
Samuel M. Migui ◽  
Robert J. Lamb
Keyword(s):  
Spring Wheat ◽  
Trophic Interactions ◽  
Plant Biomass ◽  
Rhopalosiphum Padi ◽  
Aphid Species ◽  
Economic Damage ◽  
Cereal Aphids ◽  
Cereal Aphid ◽  
Economic Thresholds ◽  
Specific Impact

AbstractThe susceptibilities of genetically diverse Canadian spring wheats, Triticum aestivum L. and Triticum durum Desf., to three aphid species, Rhopalosiphum padi (L.), Sitobion avenae (Fabricius), and Schizaphis graminum (Rondani), were investigated. Trophic interactions measured as changes in biomass of aphids and wheat plants were used to quantify levels of resistance, components of resistance, and impact of aphids on yield. Plants in field cages were infested with small numbers of aphids for 21 days at heading. These plants were usually more suitable for the development of S. avenae and S. graminum than of R. padi. Partial resistance, measured as seed production by infested plants as a proportion of that by a control, varied from 11% to 59% for different aphid species and wheat classes when all wheat plants were infested at the same stage. Cultivars within wheat classes responded similarly to each of the aphid species. None of the wheat cultivars showed agriculturally effective levels of antibiosis. The specific impact of each aphid species and wheat class varied from 5 to 15 mg of plant biomass lost for each milligram of biomass gained by the aphids. Canadian Western Red Spring wheat had a lower specific impact and therefore was more tolerant to aphids than the other two classes, but not tolerant enough to avoid economic damage at the aphid densities observed. Plants did not compensate for feeding damage after aphid feeding ceased, based on the higher specific impacts observed for mature plants than for plants that were heading. The interactions between aphids and plants show that current economic thresholds probably underestimate the damage caused by cereal aphids to Canadian spring wheat.

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