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1.
J Econ Entomol ; 101(2): 546-54, 2008 Apr.
Article in English | MEDLINE | ID: mdl-18459423

ABSTRACT

Cry1Ac protoxin (the active insecticidal toxin in both Bollgard and Bollgard II cotton [Gossypium hirsutum L.]), and Cry2Ab2 toxin (the second insecticidal toxin in Bollgard II cotton) were bioassayed against five of the primary lepidopteran pests of cotton by using diet incorporation. Cry1Ac was the most toxic to Heliothis virescens (F.) and Pectinophora gossypiella (Saunders), demonstrated good activity against Helicoverpa zea (Boddie), and had negligible toxicity against Spodoptera exigua (Hübner) and Spodoptera frugiperda (J. E. Smith). Cry2Ab2 was the most toxic to P. gossypiella and least toxic to S. frugiperda. Cry2Ab2 was more toxic to S. exigua and S. frugiperda than Cry1Ac. Of the three insect species most sensitive to both Bacillus thuringiensis (Bt) proteins (including H. zea), P. gossypiella was only three-fold less sensitive to Cry2Ab2 than Cry1Ac, whereas H. virescens was 40-fold less sensitive to Cry2Ab2 compared with CrylAc. Cotton plants expressing Cry1Ac only and both Cry1Ac and Cry2Ab2 proteins were characterized for toxicity against H. zea and S.frugiperda larvae in the laboratory and H. zea larvae in an environmental chamber. In no-choice assays on excised squares from plants of different ages, second instar H. zea larvae were controlled by Cry1Ac/Cry2Ab2 cotton with mortality levels of 90% and greater at 5 d compared with 30-80% mortality for Cry1Ac-only cotton, depending on plant age. Similarly, feeding on leaf discs from Cry1Ac/Cry2Ab2 cotton resulted in mortality of second instars of S.frugiperda ranging from 69 to 93%, whereas exposure to Cry1Ac-only cotton yielded 20-69% mortality, depending on plant age. When cotton blooms were infested in situ in an environmental chamber with neonate H. zea larvae previously fed on synthetic diet for 0, 24, or 48 h, 7-d flower abortion levels for Cry1Ac-only cotton were 15, 41, and 63%, respectively, whereas for Cry1Ac/Cry2Ab2 cotton, flower abortion levels were 0, 0, and 5%, respectively. Cry1Ac and Cry2Ab2 concentrations were measured within various cotton tissues of Cry1Ac-only and Cry1Ac/Cry2Ab2 plants, respectively, by using enzyme-linked immunosorbent assay. Terminal leaves significantly expressed the highest, and large leaves, calyx, and bracts expressed significantly the lowest concentrations of Cry1Ac, respectively. Ovules expressed significantly the highest, and terminal leaves, large leaves, bracts, and calyx expressed significantly (P < 0.05) the lowest concentrations of Cry2Ab2. These results help explain the observed differences between Bollgard and Bollgard II mortality against the primary lepidopteran cotton pests, and they may lead to improved scouting and resistance management practices, and to more effective control of these pests with Bt transgenic crops in the future.


Subject(s)
Bacterial Proteins/genetics , Bacterial Proteins/pharmacology , Endotoxins/genetics , Endotoxins/pharmacology , Gossypium/genetics , Hemolysin Proteins/genetics , Hemolysin Proteins/pharmacology , Insect Control/methods , Insecticides/pharmacology , Lepidoptera/drug effects , Animals , Bacillus thuringiensis Toxins , Bacterial Proteins/metabolism , Bacterial Toxins , Endotoxins/metabolism , Gene Expression Regulation, Plant/physiology , Gossypium/metabolism , Hemolysin Proteins/metabolism , Larva/drug effects , Plant Leaves/metabolism , Plants, Genetically Modified
2.
Harv Bus Rev ; 79(5): 135-4, 166, 2001 May.
Article in English | MEDLINE | ID: mdl-11345910

ABSTRACT

Everyone knows that starting a business requires cash, and growing a business requires even more. But few people understand that a profitable company that tries to grow too fast can run out of cash even if its products are great successes. So a big challenge for managers of any growing concern is to strike the proper balance between consuming cash and generating it. Authors Neil Churchill and John Mullins offer a framework to help identify and manage the level of growth that a company's cash flow can support. They present a formula to calculate an organization's self-financeable growth (SFG) rate, taking into account three critical factors: a company's operating cash cycle--the amount of time the company's money is tied up in inventory and other current assets before customers pay for goods and services; the amount of cash needed to finance each dollar of sales; and the amount of cash generated by each dollar of sales. The authors offer a detailed hypothetical example that carefully considers these three factors; they then illustrate how a company can influence its SFG rate by carefully managing some combination of those factors--that is, some mix of speeding cash flow, reducing costs, and raising prices. They expand on the original example by showing how to include income taxes and depreciation; plan for asset replacement; and identify which one of multiple product lines holds the greatest growth potential. The authors also discuss how various kinds of businesses--manufacturing firms, importers, and service companies--differ greatly in their abilities to finance growth from internally generated funds.


Subject(s)
Commerce/organization & administration , Financial Management/methods , Organizational Objectives , Planning Techniques , Accounting , Commerce/economics , Efficiency, Organizational , United States
3.
Environ Monit Assess ; 5(2): 137-54, 1985 Jun.
Article in English | MEDLINE | ID: mdl-24257991

ABSTRACT

During the summer of 1982, the U.S. Environmental Protection Agency conducted a comprehensive multimedia environmental monitoring program in the vicinity of two secondary lead smelters and at one reference site in Dallas, Texas. This monitoring program included a major soils investigation with the collection and analysis of over 2700 soil samples. In addition, approximately 1000 blood and 840 house dust samples were collected and analyzed for their lead content.Utilizing geostatistics and the data obtained from a portion of the soil samples, isopleths of constant soil lead concentrations within each of the three monitoring sites were identified. Presented are the soil monitoring strategy and the geostatistical techniques selected for identifying the distributions of soil lead patterns at each of the three monitoring sites. In addition, the soil sampling and analytical methods used, the sample handling and preparation procedures, and the geostatistical results obtained are identified.

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