Impact of harvesting with burning and management of straw on the industrial quality and productivity of sugarcane

Aquino, Gisele Silva de; Medina, Cristiane de Conti; Menezes, Ayres de Oliveira; Pasini, Amarildo; Brito, Osmar Rodrigues; Cunha, Ana Carolina Benitez; JÃonior, Jaime Higino dos Santos; Kussaba, Deise Akemi Omori; Almeida, Luis Fernando

doi:10.5897/ajar2016.11014

Cited by 6 publications

(1 citation statement)

References 12 publications

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“…Over the past few years, studies have brought very relevant understanding about the impacts of straw removal management on soil quality [12,14,36,48], SOC accumulation [49,50], greenhouse gas emissions [51][52][53], plant growth and stalk yield [18,19,46,[54][55][56]. Despite this fact, future studies are essential to understand the long-term implications of straw removal management on soil and stalk yield.…”

Section: Effect Of Straw Removal On the Leaf-tissue Nutrient Concentrmentioning

confidence: 99%

Prediction of Sugarcane Yield Based on NDVI and Concentration of Leaf-Tissue Nutrients in Fields Managed with Straw Removal

et al. 2018

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The total or partial removal of sugarcane (Saccharum spp. L.) straw for bioenergy production may deplete soil quality and consequently affect negatively crop yield. Plants with lower yield potential may present lower concentration of leaf-tissue nutrients, which in turn changes light reflectance of canopy in different wavelengths. Therefore, vegetation indexes, such as the normalized difference vegetation index (NDVI) associated with concentration of leaf-tissue nutrients could be a useful tool for monitoring potential sugarcane yield changes under straw management. Two sites in São Paulo state, Brazil were utilized to evaluate the potential of NDVI for monitoring sugarcane yield changes imposed by different straw removal rates. The treatments were established with 0%, 25%, 50%, and 100% straw removal. The data used for the NDVI calculation was obtained using satellite images (CBERS-4) and hyperspectral sensor (FieldSpec Spectroradiometer, Malvern Panalytical, Almelo, Netherlands). Besides sugarcane yield, the concentration of the leaf-tissue nutrients (N, P, K, Ca, and S) were also determined. The NDVI efficiently predicted sugarcane yield under different rates of straw removal, with the highest performance achieved with NDVI derived from satellite images than hyperspectral sensor. In addition, leaf-tissue N and P concentrations were also important parameters to compose the prediction models of sugarcane yield. A prediction model approach based on data of NDVI and leaf-tissue nutrient concentrations may help the Brazilian sugarcane sector to monitor crop yield changes in areas intensively managed for bioenergy production.

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Section: Effect Of Straw Removal On the Leaf-tissue Nutrient Concentrmentioning

confidence: 99%

Prediction of Sugarcane Yield Based on NDVI and Concentration of Leaf-Tissue Nutrients in Fields Managed with Straw Removal

et al. 2018

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Prospects and challenges of conservation agriculture in Bangladesh for sustainable sugarcane cultivation

Tabriz

Kader

Rokonuzzaman

et al. 2021

Environ Dev Sustain

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Does the Partial Raw Cane System Present Possibilities to Increase Sugarcane Field Longevity in Clayey Soil?

et al. 2021

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Impact of harvesting with burning and management of straw on the industrial quality and productivity of sugarcane

Cited by 6 publications

References 12 publications

Prediction of Sugarcane Yield Based on NDVI and Concentration of Leaf-Tissue Nutrients in Fields Managed with Straw Removal

Prediction of Sugarcane Yield Based on NDVI and Concentration of Leaf-Tissue Nutrients in Fields Managed with Straw Removal

Prospects and challenges of conservation agriculture in Bangladesh for sustainable sugarcane cultivation

Does the Partial Raw Cane System Present Possibilities to Increase Sugarcane Field Longevity in Clayey Soil?

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