When do I want to know and why? Different demands on sugarcane yield predictions

Bocca, Felipe Ferreira; Rodrigues, Luiz Henrique Antunes; Arraes, Nilson Antonio Modesto

doi:10.1016/j.agsy.2014.11.008

Cited by 32 publications

(13 citation statements)

References 42 publications

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“…Monitoring sugarcane and its sucrose content during the growing season can provide essential information to several users, such as individual producers, sugarcane mills, or commodity traders (Abdel-Rahman and Ahmed, 2008). This is because monitoring and yield forecasting helps to evaluate production processes, adjust on-site management, and estimates the potential industrial production (Bocca et al, 2015). Currently, the most common method for yield estimation in the field is still based on historical records and expert knowledge (Shendryk et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Currently, the most common method for yield estimation in the field is still based on historical records and expert knowledge (Shendryk et al, 2021). Specialists estimate yield based on visual assessment, basing their estimation on knowledge, historical yield data, land characteristics, weather, and the manifestation of pests and diseases (Bocca et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Observing Sucrose Accumulation With Sentinel-1 Backscatter

Besten

Steele‐Dunne

Aouizerats³

et al. 2021

Front. Remote Sens.

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In this study the impact of sucrose accumulation in Sentinel-1 backscatter observations is presented and compared to Planet optical observations. Sugarcane yield data from a sugarcane plantation in Xinavane, Mozambique are used for this study. The database contains sugarcane yield of 387 fields over two seasons (2018-2019 and 2019-2020). The relation between sugarcane yield and Sentinel-1 VV and VH backscatter observation is analyzed by using the Normalized Difference Vegetation Index (NDVI) data as derived from Planet Scope optical imagery as a benchmark. The different satellite observations were compared over time to sugarcane yield to understand how the relation between the observations and yield evolves during the growing season. A negative correlation between yield and Cross Ratio (CR) from Sentinel-1 backscatter was found while a positive correlation between yield and Planet NDVI was observed. An additional modeling study on the dielectric properties of the crop revealed how the CR could be affected by sucrose accumulation during the growing season and supported the opposite correlations. The results shows CR contains information on sucrose content in the sugarcane plant. This sets a basis for further development of sucrose monitoring and prediction using a combination of radar and optical imagery.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Observing Sucrose Accumulation With Sentinel-1 Backscatter

Besten

Steele‐Dunne

Aouizerats³

et al. 2021

Front. Remote Sens.

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“…In addition to the choice of genotype (Bocca et al 2015;Jones et al 2015), it is appropriate to treat sugarcane with chemicals to more effectively release its soluble carbohydrates (sugars), which can increase its forage quality, promote fewer losses and reduce alcoholic fermentation, which reduces its consumption by animals. To this end, the best results have been obtained from the use of alkaline additives, such as sodium hydroxide (BoladoRodr ıguez et al 2016;Janke et al 2016), calcium hydroxide (Oliveira et al 2008;Pina et al 2009) and calcium oxide (CaO) (Padua et al 2014;Roth et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Nutritional profiles of three genotypes of sugarcane silage associated with calcium oxide

et al. 2017

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The objective of this study was to evaluate, based on chemical composition and in vitro dry matter (DM) digestibility, silages of different sugarcane genotypes after exposure to different doses of calcium oxide (CaO) and to identify that most appropriate dose for use in ruminant feed. The experiment was conducted using a completely randomized 3 9 4 factorial arrangement with three sugarcane genotypes ('IAC-862480', 'SP-791011' and 'CTC-3') and four levels of the additive CaO (0, 15, 30 and 45 g kg À1 ). A quadratic effect was observed (P < 0.05) for DM content in the silages of genotypes 'SP-791011' and 'CTC-3'. The organic matter content of genotypes 'SP-791011' and 'CTC-3' showed a negative linear effect that was associated with the addition of CaO, which promoted an increase in the mineral matter (MM) content in the silages. There was no effect (P > 0.05) of genotype or an interaction effect between genotype and CaO level on crude protein content in the silages. There was an interaction effect (P < 0.05) between genotype and CaO level on the level of neutral detergent fiber in the studied silages and the development of this interaction revealed a linear decrease in neutral detergent fiber in genotype IAC-86280 and a quadratic effect (P < 0.05) for genotypes 'SP-791011' and 'CTC-3'. Potentially degradable DM (pdDM) values showed a positive quadratic function with maxima at 34.8 g kg À1 CaO. The results obtained for potentially degradable neutral detergent fiber (pdNDF) showed that there was a negative linear effect for genotype 'SP-791011' and a quadratic effect with the maximum critical point for genotypes 'IAC-862480' and 'CTC-3'. Total DM losses decreased with levels of CaO. All genotypes evaluated showed potential for silage production. The addition of CaO in the ensiling of sugarcane at up to 45 g kg À1 reduces gas and effluent losses and increases the DM recovery of the silages.

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“…As previsões de rendimento utilizados para informar os planos orçamentários e de colheita são de suma importância uma vez que as ações sobre essas previsões afetam toda a cadeia produtiva, destacando a necessidade de um quadro de tomada de decisão que avaliam os efeitos das decisões nos processos subsequentes (BOCCA et al, 2015).…”

Section: A Organização Do Setorunclassified

Análise de indicadores de produtividade com aplicação de ferramentas de gestão da qualidade na manutenção de colhedoras de cana-de-açúcar

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When do I want to know and why? Different demands on sugarcane yield predictions

Cited by 32 publications

References 42 publications

Observing Sucrose Accumulation With Sentinel-1 Backscatter

Observing Sucrose Accumulation With Sentinel-1 Backscatter

Nutritional profiles of three genotypes of sugarcane silage associated with calcium oxide

Análise de indicadores de produtividade com aplicação de ferramentas de gestão da qualidade na manutenção de colhedoras de cana-de-açúcar

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