2016
DOI: 10.4025/actasciagron.v38i3.28599
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<b>A sampling plan and spatial distribution for site-specific control of <i>Sphenophorus levis</i> in sugarcane

Abstract: ABSTRACT. Sphenophorus levis has become a major pest of sugarcane plantations in Brazil, causing significant losses in productivity. Few studies have been conducted on the spatial distribution of this pest in the field, which is essential for the development of sampling plans. We aimed to characterize the spatial distribution of S. levis in sugarcane, defining a reliable, practical and feasible sampling plan, as well as generating application maps for production areas, allowing for comparison of the consumptio… Show more

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Cited by 9 publications
(14 citation statements)
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“…According to reported by Pavlu and Molin (2016), PNE does not mean necessarily that dataset presents a randomized pattern, but it may be a result of the large sampling grid sizes that prevented the detection of variability existing in the area. In addition, Soybean phenological scale as described by Ritchie et al (1985) and adapted by Yorinori (1996).…”
Section: Resultsmentioning
confidence: 99%
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“…According to reported by Pavlu and Molin (2016), PNE does not mean necessarily that dataset presents a randomized pattern, but it may be a result of the large sampling grid sizes that prevented the detection of variability existing in the area. In addition, Soybean phenological scale as described by Ritchie et al (1985) and adapted by Yorinori (1996).…”
Section: Resultsmentioning
confidence: 99%
“…The difficulty to determine a consistent pattern of pest spatial variability led Reay-Jones et al (2010) and Pavlu and Molin (2016) to conclude that a more efficient strategy to recognize the spatial distribution pattern of the bedbugs in cotton and Sphenophorus levis in sugarcane fields is indirectly through the mapping of pest damages caused to crops, since crop damages are irreversible and statics. However, this alternative is not feasible for soybean crop, because damages caused by bedbugs to grains cannot be identified visually in field, but they need to be analyzed in laboratory.…”
Section: Resultsmentioning
confidence: 99%
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