Gesunde Pflanzen

, Volume 69, Issue 2, pp 73–81 | Cite as

A Geometrical Model to Predict the Spatial Expansion of Sorghum Halepense in Maize Fields

  • D. Andújar
  • X. Rodriguez
  • V. Rueda-Ayala
  • C. San Martín
  • A. Ribeiro
  • C. Fernández-Quintanilla
  • J. Dorado
Original Article
  • 98 Downloads

Abstract

New technologies, such as Differential Global Positioning Systems (DGPS) and Geographic Information Systems (GIS), may be useful in order to create models to predict the spatio-temporal behaviour of weeds. The aim of this study was to generate a geometric model able to predict the patch expansion of S. halepense, a problematic perennial weed in maize crops in Central Spain. From previous infestation maps, the model describes new possible spreading areas for the upcoming growing season, and therefore, herbicide treatments can be planned on time. Two different experiments were implemented, in which initial patch density and size were examined. Patches of different size (1, 10 and 100 m2) and density (4, 20 and 100 shoots m−2), were established. These patches were visually identified, their perimeter defined and their density characterized, during three growing seasons (from 2008 to 2010 campaigns). According to this information different descriptors were built: (1) area and density of each patch; (2) the relative growth in width and length, according to space and time and compared with previous years; and (3) the increased density ratio, calculated in relation of patch size and distance to previous patch in the new infestation areas of expansion. All these descriptors were added to the model in order to predict the patch expansion in the last studied season (i. e., 2010) using previous maps (i. e., season 2008 and 2009). The model uses geometrical assimilation to predict, and two expansion assumptions were considered: (a) a conservative approach based on triangular geometry; and (b) a rectangular geometry which maximizes the simulated infested area. The results were compared with the ground truth map created in 2010. Each method showed weaknesses and strengths. The triangular approach minimized the infested area, mainly in the small patches, and therefore it could predict the expansion of previously established patches, but not the emergence of new ones. In contrast, the rectangular approach simulated the position of new foci, maximizing the infested area. Therefore, although a substantial reduction of herbicides is possible using both models, a final decision must be taken individually for each field.

Keywords

Triangular modeling Rectangular modeling Weed infestation Tillage Site-specific weed management (SSWM) 

Ein geometrisches Modell zur Vorhersage der räumlichen Ausbreitung von Sorghum Halepense in Maisfeldern

Zusammenfassung

Technologien wie Differential Global Positioning Systems (DGPS) und Geographische Informationssysteme (GIS) können nützlich sein, um Modelle zur Vorhersage des räumlich-zeitlichen Verhaltens von Unkräutern zu erstellen. Das Ziel dieser Studie war, ein geometrisches Modell zu erzeugen, das in der Lage ist, die Erweiterung von S. Halepense-Nestern vorherzusagen – ein problematisches mehrjähriges Unkraut in Maispflanzen in Mittelspanien. Aus früheren Befallskarten beschreibt das Modell neue mögliche Verbreitungsgebiete für die kommende Vegetationsperiode, und daher können die Herbizidbehandlungen rechtzeitig geplant werden. Zwei Experimente wurden durchgeführt, bei denen die Anfangsdichte und die Größe der Nester untersucht wurden; Nester unterschiedlicher Größe (1, 10 und 100 m2) und Dichte (4, 20 und 100 Triebe m−2) wurden eingerichtet. Diese Nester wurden während drei Wachstumsperioden visuell identifiziert, ihr Umfang und ihre Dichte charakterisiert (Kampagnen von 2008 bis 2010). Gemäß dieser Information wurden verschiedene Deskriptoren gebaut: (1) Fläche und Dichte jedes Nestes; (2) das relative Wachstum in Breite und Länge, je nach Raum und Zeit, und im Vergleich zu den früheren Jahren; und (3) das erhöhte Dichteverhältnis, berechnet in Bezug auf Nestgröße und Abstand zu vorherigen Nestern in den neuen Befallsgebieten. Alle diese Deskriptoren wurden dem Modell hinzugefügt, um die Nesterexpansion in der letzten untersuchten Saison (d. h. 2010) vorherzusagen, mithilfe von früheren Karten (d. h. Saison 2008 und 2009). Das Modell verwendet eine geometrische Angleichung zur Vorhersage und es wurden zwei Expansionsannahmen in Betracht gezogen: (a) ein konservativer Ansatz basierend auf der Dreiecksgeometrie; und (b) eine rechteckige Geometrie, die den simulierten befallenen Bereich maximiert. Die Ergebnisse wurden mit der im Jahr 2010 erstellten Ground Truth Karte verglichen. Jedes Verfahren zeigte Schwächen und Stärken. Das Dreiecks-Vorgehen minimierte das verunkrautete Gebiet, vor allem in den kleinen Nestern, so dass es zwar die Ausbreitung der bereits etablierten Nester vorhersagen könnte, aber nicht das Auftauchen neuer. Im Gegensatz dazu simulierte das Rechtwinklige-Vorgehen die Position neuer Herde, wodurch die befallene Fläche maximiert wurde. Obwohl eine wesentliche Reduktion von Herbiziden bei beiden Modellen möglich ist, muss eine endgültige Entscheidung für jedes Feld individuell getroffen werden.

Schlüsselwörter

Dreieckige-Modellbildung Rechtwinklige-Modellbildung Verunkrautung Bodenbearbeitung Teilflächen spezifische Unkrautbehandlung 

Notes

Funding

The Spanish Ministry of Economy and Competitiveness has provided support for this research via project AGL2014-52465-C4-3.

Conflict of interest

D. Andújar, X. Rodriguez, V. Rueda-Ayala, C. SanMartín, A. Ribeiro, C. Fernández-Quintanilla, and J. Dorado declare that they have no competing interests.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • D. Andújar
    • 1
  • X. Rodriguez
    • 1
  • V. Rueda-Ayala
    • 2
  • C. San Martín
    • 1
  • A. Ribeiro
    • 3
  • C. Fernández-Quintanilla
    • 1
  • J. Dorado
    • 1
  1. 1.Institute of Agricultural SciencesCSICMadridSpain
  2. 2.NIBIOKlepp StasjonNorway
  3. 3.Centre for Automation and RoboticsCSIC-UPMMadridSpain

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