Sucrose accumulation in sugarcane is influenced by temperature and genotype through the carbon source - sink balance

Inman-Bamber, N. G.; Bonnett, G. D.; Spillman, M. F.; Hewitt, M. H.; Glassop, Donna

doi:10.1071/cp09262

Cited by 35 publications

(22 citation statements)

References 21 publications

(41 reference statements)

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“…In sugarcane, upward flow to shoot growth centers was considerably more temperature sensitive than downward flow into mature culms (Hartt 1965), a response accounting for increased sucrose accumulation (Inman-Bamber et al 2010). Interestingly, estimates of Q 10 values for translocation out of leaf blades and down stems of 1.1 to 1.7 are suggestive of physiochemical-driven transport processes (Hartt 1965).…”

Section: Temperature Influences At Both Extremesmentioning

confidence: 99%

Phloem Transport of Resources

Grof¹,

Byrt²,

Patrick³

2013

Sugarcane: Physiology, Biochemistry, and Functional Biology

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This chapter reviews the principles and concepts of resource transport in the phloem in general and then moves to describe the physiology of phloem translocation in sugarcane. The movement of resources through the phloem is interpreted through the Münch pressure flow hypothesis. The phloem transport rate is determined by magnitudes of pressure differences between the source and sink ends of the pathway and the phloem sap concentration of each transported nutrient. Phloem rate is regulated by loading and unloading activities, sink hydrostatic pressures, and hydraulic conductivities of plasmodesmata interconnecting sieve element/companion cell complexes with phloem parenchyma cells. A description of the leaf structural framework in sugarcane is provided and the phloem pathways in sugarcane are dissected from loading of collection phloem in source leaves, transit through transport phloem, to release phloem where resources are unloaded into growth and storage sinks. Phloem conductivities in sugarcane, mechanisms of loading and unloading of solutes, and the environmental effects on phloem translocation are considered.

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Section: Temperature Influences At Both Extremesmentioning

confidence: 99%

Phloem Transport of Resources

Grof¹,

Byrt²,

Patrick³

2013

Sugarcane: Physiology, Biochemistry, and Functional Biology

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“…Disruption of the planting and harvesting schedule can have long-term effects over several seasons as growers attempt to return to schedules that have proven successful in the past. Temperature range is also known to be a good predictor of sucrose content (Kingston 2002) because low night temperatures discourage stalk (cane) and leaf growth, in favor of sucrose accumulation (Inman-Bamber et al 2010). We chose sugarcane yield as the target for our predictive model because of its importance in determining nitrogen requirements for the crop.…”

Section: Regression Random Forestmentioning

confidence: 99%

“…We chose sugarcane yield as the target for our predictive model because of its importance in determining nitrogen requirements for the crop. Low night temperatures would affect cane yield adversely (Inman-Bamber et al 2010).…”

Section: Regression Random Forestmentioning

confidence: 99%

Accurate prediction of sugarcane yield using a random forest algorithm

Everingham

Sexton

Skocaj

et al. 2016

Agron. Sustain. Dev.

249

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Foreknowledge about sugarcane crop size can help industry members make more informed decisions. There exists many different combinations of climate variables, seasonal climate prediction indices, and crop model outputs that could prove useful in explaining sugarcane crop size. A data mining method like random forests can cope with generating a prediction model when the search space of predictor variables is large. Research that has investigated the accuracy of random forests to explain annual variation in sugarcane productivity and the suitability of predictor variables generated from crop models coupled with observed climate and seasonal climate prediction indices is limited. Simulated biomass from the APSIM (Agricultural Production Systems sIMulator) sugarcane crop model, seasonal climate prediction indices and observed rainfall, maximum and minimum temperature, and radiation were supplied as inputs to a random forest classifier and a random forest regression model to explain annual variation in regional sugarcane yields at Tully, in northeastern Australia. Prediction models were generated on 1 September in the year before harvest, and then on 1 January and 1 March in the year of harvest, which typically runs from June to November. Our results indicated that in 86.36 % of years, it was possible to determine as early as September in the year before harvest if production would be above the median. This accuracy improved to 95.45 % by January in the year of harvest. The R-squared of the random forest regression model gradually improved from 66.76 to 79.21 % from September in the year before harvest through to March in the same year of harvest. All three sets of variables-(i) simulated biomass indices, (ii) observed climate, and (iii) seasonal climate prediction indices-were typically featured in the models at various stages. Better crop predictions allows farmers to improve their nitrogen management to meet the demands of the new crop, mill managers could better plan the mill's labor requirements and maintenance scheduling activities, and marketers can more confidently manage the forward sale and storage of the crop. Hence, accurate yield forecasts can improve industry sustainability by delivering better environmental and economic outcomes.

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“…For example, as a typical tropical and subtropical plant, sugarcane responds to chilling temperatures with dramatic alterations in photosynthesis, which is by far the most explored process in sugarcane for obvious reasons. For instance, under chilling temperature conditions, the photosynthetic rate is severely reduced (Inman-Bamber et al 2010). Furthermore, earlier studies carried out on leaves of a coldsensitive cultivar (Badila) revealed that important photosynthetic enzymes can be affected by chilling temperatures (10°C) such as decreased sucrose phosphate synthase (Du and Nose 2002), NADP-malate dehydrogenase and pyruvate orthophosphate dikinase activities (Du et al 1999), indicating a fundamental role of these enzymes when sugarcane is subjected to low temperatures.…”

Section: Temperature Stressmentioning

confidence: 97%

Sugarcane Under Pressure: An Overview of Biochemical and Physiological Studies of Abiotic Stress

Azevedo

Carvalho

Cicarelli

et al. 2011

Tropical Plant Biol.

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Sugarcane is now an extremely important crop, particularly in tropical countries. Its use for sugar and ethanol production is critical and cultivated area and biomass yield are increasing. Environmental pollution by anthropogenic activities is perhaps one of the most disturbing problems the world is facing and the cultivation of crops is subjected to this pollution, which may result in drastic effects on crop production. Curiously, the literature on the study of abiotic stresses on sugarcane is very limited, indicating that there is far more research to be done and investigations on this topic need to be prioritized. In this article, we have tried to focus on four key abiotic stresses, drought, temperature, salt and toxic metals, to which sugarcane is most likely to be subjected and reviewed the scarce current literature on the subject.

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Sucrose accumulation in sugarcane is influenced by temperature and genotype through the carbon source - sink balance

Cited by 35 publications

References 21 publications

Phloem Transport of Resources

Phloem Transport of Resources

Accurate prediction of sugarcane yield using a random forest algorithm

Sugarcane Under Pressure: An Overview of Biochemical and Physiological Studies of Abiotic Stress

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