tion. Two weeks before harvest, the percent reflectance positively correlated withyields from four separate studies. The reflectance data were not analyzed collectivelyacross all four studies because there were dramatic differences in yield betweenstudies. If percent reflectance data were collected periodically throughout thegrowing season in the four separate peanut studies <strong>and</strong> related to LAI, then the RIintegrated over all the observation dates may have allowed all the data to be analyzedtogether. Theoretically, this would demonstrate that RI as affected by late leafspotdefoliation <strong>and</strong> different environmental conditions could explain most of the yielddifferences. Additionally, if disease severity was rated each time the spectralreflectance was measured, then the effects of leafspot on spectral reflectance <strong>and</strong> LAIcould be correlated.Dudka 66 used a h<strong>and</strong>-held radiometer to measure the reflectance of soybeanswith varying levels of sclerotinia stem rot caused by Sclerotinia sclerotiorum.Disease incidence correlated positively with reflectance at 706 nm <strong>and</strong> negatively at760 nm. It was inferred that yield data negatively correlated the incidence of sclerotiniastem rot.The studies using the h<strong>and</strong>held radiometers demonstrate that remote sensing <strong>and</strong>image analysis have utility in quantifying the effects of disease on yield loss. Becausethe remote sensing was limited to a single finite point in time, the data collected onlycorrelated well with each study <strong>and</strong> the relationships could not be integrated acrossstudies. Instead, if the spectral measurements were collected over the entire growingseason <strong>and</strong> related to LAI, then the RI by the crop could be integrated <strong>and</strong> calculatedfor the entire season <strong>and</strong> correlated to yield. This would then allow data from differentstudies to be collectively analyzed.11.8 SUMMARYWhether a pest attacks the roots, stem, or leaves, the effects ultimately will manifestthemselves with a reduction in leaf area. The concept is simple, but often overlooked.Using Beer’s Law <strong>and</strong> LAI, if a crop had an LAI of six, it could lose one half the LAIbefore the plant would see a dramatic reduction in RI (Figure 11.1). High LAI providesprotection against loss biomass production <strong>and</strong> yield when leaves are destroyedby diseases or biotic stress, because of the relationship between LAI <strong>and</strong> RI. In theearly growth stages of an annual plant, the LAI is less than three, <strong>and</strong> the loss of LAIhas a significant effect on RI <strong>and</strong> net assimilate production (Figure 11.1). Early seasondisease epidemics that affect HLAI <strong>and</strong> RI may only delay the crop maturity, ifcontrol practices are implemented to stop the epidemic. Delayed maturity mightreduce crop yields if the incident radiation between the normal maturation time <strong>and</strong>the delayed time is dramatically less due to weather <strong>and</strong> angle of the sun. For this reasonit is important to quantify the severity of infestation <strong>and</strong> on what portion(s) of thecrop, to record the growth stage, <strong>and</strong> measure the LAI if the effects will be correlatedwith crop yields.Integrating RI <strong>and</strong> RUE over a growing season provides an accurate measurementof total biomass production of a crop as outlined by Monteith 22 <strong>and</strong>Goudriaan. 67 Differences in abiotic <strong>and</strong> biotic effects on the crop are then reflected
in HLAI, RI, <strong>and</strong> RUE, accounting for differences in net assimilation, biomass, <strong>and</strong>yield of the crop. With these known variables, data from different locations <strong>and</strong> yearscan be collectively analyzed <strong>and</strong> summarized. The major difficulty with this conceptis the length of time necessary to measure LAI data. 68 To help alleviate this problemin the future, limited LAI sampling could be integrated with remote sensing to savetime <strong>and</strong> resources.This approach should help us to better underst<strong>and</strong> how single or multiple bioticstresses affect the net biomass production of a crop. This would allow the creation ofmodels that would predict crop yields throughout the season, <strong>and</strong> be site specific,given historic environmental parameters. As the growing season progresses <strong>and</strong> theenvironmental conditions are updated into the model along with the relative RI <strong>and</strong>RUE, growth stage, predicted weather conditions, presence of pathogen, price ofcommodity, <strong>and</strong> cost of sprays, pest management decisions would be made as economicthresholds are reached.REFERENCES1. Gaunt, R. E., The relationship between plant disease severity <strong>and</strong> yield, Annu. Rev.Phytopathol., 33, 119, 1995.2. James, W. C., Assessment of plant diseases <strong>and</strong> losses, Annu. Rev. Phytopathol., 12, 27,1974.3. Chester, K. S., Plant disease losses: their appraisal <strong>and</strong> interpretation, Plant Dis. Rep.Suppl. 193, 189, 1950.4. Cook, R. J., Use of the term “crop loss,” Plant Dis., 69, 95, 1985.5. Stevenson, W. S., Management of early <strong>and</strong> late blight, in Potato Health Management,Rowe, R. C., Ed., APS Press, St. Paul, MN, 1993, chap. 16.6. Johnson, K. B., <strong>and</strong> Teng, P. S., Coupling a disease progress model for early blight to amodel of potato growth, Phytopathology, 80, 416, 1990.7. Backman, P. A., <strong>and</strong> Jacobi, J. C., Thresholds for plant-disease management, in EconomicThresholds for Integrated Pest Management, Higley, L. G., <strong>and</strong> Pedigo, L. P., Eds.,University of Nebraska Press, Lincoln, 1996, chap. 8.8. Nutter, F. W., Jr., Teng, P. S., <strong>and</strong> Royer, M. H., Terms <strong>and</strong> concepts for yield, crop losses<strong>and</strong> disease thresholds, Plant Dis., 77, 211, 1993.9. Nutter, F. W., Jr., Disease severity assessment training, in Exercises in Plant DiseaseEpidemiology, Francl, L. J., <strong>and</strong> Neher, D. A., Eds., APS Press, St. Paul, MN, 1997,chap. 1.10. Tomerlin, J. R., <strong>and</strong> Howell, T. A., DISTRAIN: A computer program for training peopleto estimate disease severity on cereal leaves, Plant Dis., 72, 455, 1988.11. Madden, L. V., <strong>and</strong> Nutter, F. W., Jr., Modeling crop losses at the field scale, Can. J. PlantPathol., 17, 124, 1995.12. Backman, P. A., <strong>and</strong> Crawford, M. A., Relationship between yield loss <strong>and</strong> severity ofearly <strong>and</strong> late leafspot diseases of peanut, Phytopathology, 74, 1101, 1984.13. Shaner, G., <strong>and</strong> Finney, R. E., The effect of nitrogen fertilization on the expression of slowmildewing resistance in Knox wheat, Phytopathology, 67, 1051, 1977.14. Broscious, S. C., Pataky, J. K., <strong>and</strong> Kirby, H. W., Quantitative relationships between yield<strong>and</strong> foliar diseases of alfalfa, Phytopathology, 77, 887, 1987.
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Biotic Stressand Yield Loss
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Library of Congress Cataloging-in-P
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PrefaceThe idea for this book came
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EditorsRobert K. D. Peterson, Ph.D.
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ContentsChapter 1Illuminating the B
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1Illuminating the Black Box:The Rel
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increase plant tolerance, through p
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the action of a stressor on a plant
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The magnitude and duration of injur
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Plant part injuredrefers to the pla
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cific competition, while agricultur
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2Yield Loss and PestManagementLeon
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direct relationships between the ac
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In keeping with the theme of this b
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egressions. Actually, the title “
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REFERENCES1. Teng, P. S., Crop Loss
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3Techniques for EvaluatingYield Los
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number of species and stage of cutw
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especially if buried in soil, can d
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elationships for some pests. When m
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injury can be precisely controlled
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day. 81, 99 However, except for an
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the literature most likely are actu
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20. Ba-Angood, S. A., and Stewart,
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60. Stewart, J. G., McRae, K. B., a
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99. Shields, E. J., and Wyman, J. A
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4.3.3.1.3 Third generation European
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ing on the developmental stage at t
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4.2.2.1.2 Temperature stressPlant s
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chronic injury. Acute injury result
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ows, roadsides, or small grain fiel
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numbers are present. Stink bugs, Eu
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Oligonychus pratensis, feed on corn
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ECB2. 224.3.3.1.4 The impacts of Eu
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stalk borer, Papaipema nebris, is a
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period prolonged with sufficient co
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Arthropod injuries to developing ea
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esponses to herbivory have been obs
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Midwest, Purdue University CES and
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59. Bailey, W. C., and Pedigo, L. P
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5Phenological Disruptionand Yield L
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ity by animal consumers is the agro
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ously, structural components (e.g.,
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FIGURE 5.2 Generalized alfalfa grow
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601, 1972.9. Gordon, C. H., Derbysh
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do we know about how biotic stresso
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ing both large and small leaf veins
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population. Whole plants may respon
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temporally and spatially, are more
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some systems have allowed for a tra
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injury guilds would center on the f
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apple leaves, HortScience, 19, 815,
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7The Influence of Cultivarand Plant
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unit ground area, and it indicates
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without considering plant architect
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photosynthesis. Regardless of the n
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light interception. 45 Skeletonizin
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Light interception, which intrinsic
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var. Consequently, use of a single
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19. Jarosik, V., Phytoseiulus persi
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62. Caviness, C. E., Registration o
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8Drought Stress, Insects,and Yield
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humidity. Because the relative humi
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temperature and precipitation. Prop
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compared to well watered soybeans.
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Changes in plant hormones, such as
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plays a key role in promoting plant
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In soybeans, a leaf area index (LAI
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15. Schulze, E. D., Water and nutri
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52. Meyer W. S., and Walker, S., Le
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9The Impact of Herbivoryon Plants:
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conditions of stress are themselves
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are common, defenses to avoid herbi
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plant tissue, resulting in gall for
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found on cucumbers in polycultures
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compensatory response. Also, more v
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Costa Rica, and there are several g
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- Page 162 and 163: de Entomol., 38, 421, 1994.32. Kare
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- Page 168 and 169: 10Stephen C. WelterCONTENTSContrast
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- Page 184 and 185: 10. Kennedy, G. G., and Barbour, J.
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- Page 238 and 239: weeds, Weed Sci., 44, 856, 1996.79.
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influence of enhanced UV-B conditio
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Systems Approaches at the Field Lev