BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

153 related articles for article (PubMed ID: 24260408)

  • 1. Ecoinformatics can reveal yield gaps associated with crop-pest interactions: a proof-of-concept.
    Rosenheim JA; Meisner MH
    PLoS One; 2013; 8(11):e80518. PubMed ID: 24260408
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Landscape crop composition effects on cotton yield, Lygus hesperus densities and pesticide use.
    Meisner MH; Zaviezo T; Rosenheim JA
    Pest Manag Sci; 2017 Jan; 73(1):232-239. PubMed ID: 27063001
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Ecoinformatics reveals effects of crop rotational histories on cotton yield.
    Meisner MH; Rosenheim JA
    PLoS One; 2014; 9(1):e85710. PubMed ID: 24465657
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Costs of Lygus herbivory on cotton associated with farmer decision-making: an ecoinformatics approach.
    Rosenheim JA
    J Econ Entomol; 2013 Jun; 106(3):1286-93. PubMed ID: 23865193
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluating the Quality of Ecoinformatics Data Derived From Commercial Agriculture: A Repeatability Analysis of Pest Density Estimates.
    Rosenheim JA
    J Econ Entomol; 2021 Aug; 114(4):1842-1846. PubMed ID: 34180525
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Ecoinformatics for integrated pest management: expanding the applied insect ecologist's tool-kit.
    Rosenheim JA; Parsa S; Forbes AA; Krimmel WA; Law YH; Segoli M; Segoli M; Sivakoff FS; Zaviezo T; Gross K
    J Econ Entomol; 2011 Apr; 104(2):331-42. PubMed ID: 21510177
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Leveraging satellite observations to reveal ecological drivers of pest densities across landscapes.
    Emery SE; Rosenheim JA; Chaplin-Kramer R; Sharp R; Karp DS
    Sci Total Environ; 2024 May; 924():171591. PubMed ID: 38485019
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Impact of Lygus spp. (Hemiptera: Miridae) on damage, yield and quality of lesquerella (Physaria fendleri), a potential new oil-seed crop.
    Naranjo SE; Ellsworth PC; Dierig DA
    J Econ Entomol; 2011 Oct; 104(5):1575-83. PubMed ID: 22066187
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Control Failures Following Insecticide Applications in Commercial Agriculture: How Often Do They Occur? A Case Study of Lygus hesperus (Hemiptera: Miridae) Control in Cotton.
    Rosenheim JA
    J Econ Entomol; 2021 Jun; 114(3):1415-1419. PubMed ID: 33860308
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Effects of local and landscape factors on population dynamics of a cotton pest.
    Carrière Y; Goodell PB; Ellers-Kirk C; Larocque G; Dutilleul P; Naranjo SE; Ellsworth PC
    PLoS One; 2012; 7(6):e39862. PubMed ID: 22768147
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Better outcomes for pest pressure, insecticide use, and yield in less intensive agricultural landscapes.
    Gagic V; Holding M; Venables WN; Hulthen AD; Schellhorn NA
    Proc Natl Acad Sci U S A; 2021 Mar; 118(12):. PubMed ID: 33731476
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pest management strategies in traditional agriculture: an African perspective.
    Abate T; van Huis A; Ampofo JK
    Annu Rev Entomol; 2000; 45():631-59. PubMed ID: 10761592
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessment of crop damage by rodent pests from experimental barley crop fields in Farta District, South Gondar, Ethiopia.
    Wondifraw BT; Tamene MY; Simegn AB
    PLoS One; 2021; 16(8):e0255372. PubMed ID: 34383810
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Design of a Reconfigurable Crop Scouting Vehicle for Row Crop Navigation: A Proof-of-Concept Study.
    Schmitz A; Badgujar C; Mansur H; Flippo D; McCornack B; Sharda A
    Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015960
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Quantifying secondary pest outbreaks in cotton and their monetary cost with causal-inference statistics.
    Gross K; Rosenheim JA
    Ecol Appl; 2011 Oct; 21(7):2770-80. PubMed ID: 22073658
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting Nut Damage at Harvest Using Different in-Season Density Estimates of Amyelois Transitella: Analysis of Data from Commercial Almond Production.
    Rosenheim JA; Higbee BS; Ackerman JD; Meisner MH
    J Econ Entomol; 2017 Dec; 110(6):2692-2698. PubMed ID: 29029235
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The causes and consequences of pest population variability in agricultural landscapes.
    Paredes D; Rosenheim JA; Karp DS
    Ecol Appl; 2022 Jul; 32(5):e2607. PubMed ID: 35366039
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Explaining Andean potato weevils in relation to local and landscape features: a facilitated ecoinformatics approach.
    Parsa S; Ccanto R; Olivera E; Scurrah M; Alcázar J; Rosenheim JA
    PLoS One; 2012; 7(5):e36533. PubMed ID: 22693551
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Field evaluation of a Helicoverpa zea (Lepidoptera: Noctuidae) damage simulation model: effects of irrigation, H. zea density, and time of damage on cotton yield.
    Chilcutt CF; Wilson LT; Lascano RJ
    J Econ Entomol; 2003 Aug; 96(4):1174-83. PubMed ID: 14503589
    [TBL] [Abstract][Full Text] [Related]  

  • 20. LANDSCAPE CHANGES IN A LOWLAND IN BENIN: ECOLOGICAL IMPACT ON PESTS AND NATURAL ENEMIES.
    Boucher A; Silvie P; Menozzi P; Adda C; Auzoux S; Jean J; Huat J
    Commun Agric Appl Biol Sci; 2015; 80(2):79-89. PubMed ID: 27145573
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.