Economic case study of ABCD cane management practices in the Burdekin River Irrigation Area (BRIA) region

A case study was undertaken to determine the economic impact of a change in management class as detailed in the A, B, C and D management class framework. This document focuses on the implications of changing from D to C, C to B and B to A class management in the Burdekin River irrigation area (BRIA) and if the change is worthwhile from an economic perspective. This report provides a guide to the economic impact that may be expected when undertaking a particular change in farming practices and will ultimately lead to more informed decisions being made by key industry stakeholders. It is recognised that these management classes have certain limitations and in many cases the grouping of practices may not be reflective of the real situation. The economic case study is based on the A, B, C and D management class framework for water quality improvement developed in 2007/2008 for the Burdekin natural resource management region. The framework for the Burdekin is currently being updated to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics. As part of the project specification, sugarcane crop production data for the BRIA was provided by the APSIM model. The information obtained from the APSIM crop modelling programme included sugarcane yields and legume grain yield (legume grain yield only applies to A class management practice). Because of the complexity involved in the economic calculations, a combination of the FEAT, PiRisk and a custom made spreadsheet was used for the economic analysis. Figures calculated in the FEAT program were transferred to the custom made spreadsheet to develop a discounted cash flow analysis. The marginal cash flow differences for each farming system were simulated over a 5-year and 10-year planning horizon to determine the net present value of changing across different management practices. PiRisk was used to test uncertain parameters in the economic analysis and the potential risk associated with a change in value.

Economic case study of ABCD cane management practices in the Burdekin Delta region.

A case study was undertaken to determine the economic impact of a change in management class as detailed in the A, B, C and D management class framework. This document focuses on the implications of changing from D to C, C to B and B to A class management in the Burdekin Delta region and if the change is worthwhile from an economic perspective. This report provides a guide to the economic impact that may be expected when undertaking a particular change in farming practices and will ultimately lead to more informed decisions being made by key industry stakeholders. It is recognised that these management classes have certain limitations and in many cases the grouping of practices may not be reflective of the real situation. The economic case study is based on the A, B, C and D management class framework for water quality improvement developed in 2007/2008 for the Burdekin natural resource management region. The framework for the Burdekin is currently being updated to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics. As part of the project specification, sugarcane crop production data for the Burdekin Delta region was provided by the APSIM model. The information obtained from the APSIM crop modelling programme included sugarcane yields and legume grain yield (legume grain yield only applies to A class management practice). Because of the complexity involved in the economic calculations, a combination of the FEAT, PiRisk and a custom made spreadsheet was used for the economic analysis. Figures calculated in the FEAT program were transferred to the custom made spreadsheet to develop a discounted cash flow analysis. The marginal cash flow differences for each farming system were simulated over a 5-year and 10-year planning horizon to determine the Net Present Value of changing across different management practices. PiRisk was used to test uncertain parameters in the economic analysis and the potential risk associated with a change in value.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

Sewage sludge as nitrogen and phosphorus source for cane-plant and first ratoon crops

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of Mahanarva fimbriolata (Stål) (Hemiptera: Cercopidae) injury on the quality of cane juice

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fermentation and epiphytic microflora dynamics in sugar cane silage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Windrowing and prismatic baling of sugar cane vegetal residues: Some operational parameters and energetic efficiency

It was evaluated the energetic efficiency and operational parameters of a windrowing and prismatic baling, both from CASE NEW HOLLAND® operations in sugarcane vegetal residues (green leaves, dry leaves and tops) picked mechanically in green cane. The area belongs to COSTA PINTO MILL (COSAN® Group) which was harvested mechanically by combines in the State of Sao Paulo, Brazil. The geographic location of the area is: Latitude 22°40'30S, Longitude 47°36'38W and Altitude of 605m. The variety was RB 82-5336, planted in 1.40m row spacing, with 78t.ha-1 yield. The vegetal residues analysis obtained 69.93% of leaves, 21.44% of stalks fractions, 2.27% of tops and 6.36% of total strange matter. The vegetal residues values were: gross heat of 18.43MJ.kg-1, low heat of 17.00MJ.kg'1 and useful heat of 12.94MJ.kg-1. The vegetal residues average energetic potential was 342.48GJ.ha-1. The treatments were simple, double and triple windrowing. The use of the rake and prismatic baler to pick up the residues was viable. The simple windrowing treatment presented the best results: effective capacity of 83.06t.ha-1, fuel consumption of 0.18L.t -1 and 99.95% of positive energetic efficiency. The bales obtained in the treatment of triple windrowing presented the largest specific mass average of 221.11kg.m-3. The soil amount in the bales increased with successive windrowing. The baling operation in the triple windrowing treatment obtained better results, presenting the effective capacities of 20.29t.h -1 and 1.45ha.h-1 and fuel consumption of for baled in 1.37L.t-1. The high total energetic efficiency of 99.53% indicates that is technically viable the withdrawal of the vegetal residues.

Windrowing and cylindrical baling of sugar cane vegetal residues: Some operational parameters and energetic efficiency

The objective of this study was to analyze the sugar cane vegetal residues collection, as well as determining its energetic potential, using a rake and cylindrical baler, both from NEW HOLLAND® under two different windrowing process (simple and double). The field tests were carried out in an area that belongs to COSTA PINTO MILL (COSAN® Group) in the city of Piracicaba, Sao Paulo State, Brazil. The geographic location of the area is: Latitude 22°4030'S, Longitude 47°3633'W and altitude of 605m. From the trash analysis, before the baling, the following average results were obtained: 69.93% of leaves; 2.27% of stalks fractions; 21.44% of tops and 6.36% of total strange matter. The estimated residues yield was 27.01 tons.ha -1 with a gross heat of 18.43 MJ.kg-1, low heat of 17.01 MJ.kg-1, useful heat of 13.32 MJ.kg-1, average moisture of 20.76% and an energetic potential of 494,875.09 MJ.ha-1. In the windrowing operations (simple and double) the averages of the 5 out of 13 analyzed variable presented differences between them in a 1% level of significance in the Tukey Test. The averages comparison of the results for bale's specific mass and the effective capacities (ton.h-1) e (ha.h-1) had been significant at a 5% level in the Tukey Test. The comparisons of the averages for the results had been significant to 1% level. The strange matter averages of the bales did not differed between them.

Comparative field test between two sugar cane (Saccharum spp.) harvesters under two different operational conditions in Brazil

The sugar cane crop is one of the main products in Brazil and according to several authors can generate, besides the industrialized stalks, an amount of crop residues from the order of 15 to 30 % in weight of the aerial part of the plants, depending on the field conditions. The sugar cane area in Brazil is around 5.5×106 hectares, with an amount of 400.106 tons of stalks, with stalks yield of 72 tons.ha-1. This study took place in a sugar cane plot (Latitude 22°46'S, Longitude 47°23'W and 600m of altitude) with 3% of slope, located in São Paulo State. The sugar cane variety was SP 80-1816, in its forth cut, 11 months old and with a planted row spacing of 1.40 m. By other side, several sugar mills are bringing the crop residue to their patio to produce energy with the bagasse. One choice is to bring the crop residue at the same moment with the stalks, avoiding the next operation of baling it. The objective of this study was to analyze some operational parameters of two different sugar cane harvesters under the same field conditions, which was divided in four treatments: T1 = CAMECO CHT2500B operating normally; T2 = CAMECO CHT2500B operating without the cleaning system; T3 = CASE 7700 operating normally; T4 = CASE 7700 operating without the cleaning system. The results obtained were: Table presented CEB = Gross effective capacity; CEL = Net effective capacity. The conclusion is that under normal operation the CASE harvester worked better then CAMECO in the parameters CEL stalks and Manipulation efficiency. And without the cleaning system operating CASE also worked better in the parameters of CEB raw material, CEB stalks, CEL raw material and CEL stalks.

Sugar cane (Saccharum spp.) crop residue baling for energy purposes in Brazil

The sugar cane crop according to several authors can generate, besides the industrialized stalks, an amount of crop residues from the order of 15 to 30% in weight of the aerial part of the plants, depending on the field conditions. The sugar cane area in Brazil is around 5.5×106 hectares, with an amount of 400.106 tons of stalks, with stalks yield of 72 tons.ha-1 (Unica, 2005). This study took place in a sugar cane plot (Latitude 22°46'S, Longitude 47°23'W and 600m of altitude) with 3% of slope, located in São Paulo State. The sugar cane variety was SP 80-1816, in its forth cut, 11 months old and with a planted row spacing of 1.40m. By other side, several sugar mills are bringing the crop residue to their patio to produce energy with the bagasse. One way for that is the baling operation to bring the crop residue at the sugar mill. Some fundamental variables were obtained to define the best set of machines to work with in sugar cane crop residue removal in the baling system among the studied ones, some of the variables were: Soil Index (T1 = 0.83%, T2 = 0.46%, T3 = 0.65%, T4 = 0.57%); Energy Efficiency (T1 = 82.48%, T2 = 83.88%, T3 = 82.83% and T4 = 82.97%) of the system and Effective Cost for Equivalent Energy in US$.EBP-1 (T1 = 11.10, T2= 10.46, T3 = 11.47 and T4 = 10.57) of the baled trash delivered at the sugar mill.

Identification of microsatellites markers associated with yield components and quality parameters in sugarcane

Marker assisted selection depends on the identification of tightly linked association between marker and the trait of interest. In the present work, functional (EST-SSRs) and genomic (gSSRs) microsatellite markers were used to detect putative QTLs for sugarcane yield components (stalk number, diameter and height) and as well as for quality parameters (Brix, Pol and fibre) in plant cane. The mapping population (200 individuals) was derived from a bi-parental cross (IACSP95-3018 x IACSP93-3046) from the IAC Sugarcane Breeding Program. As the map is under construction, single marker trait association analysis based on the likelihood ratio test was undertaken to detect the QTLs. Of the 215 single dose markers evaluated (1:1 and 3:1), 90 (42%) were associated with putative QTLs involving 43 microsatellite primers (18 gSSRs and 25 EST-SSRs). For the yield components, 41 marker/trait associations were found: 20 for height, 6 for diameter and 15 for stalk number. An EST-SSRs marker with homology to non-phototropic hypocotyls 4 (NPH4) protein was associated with a putative QTL with positive effect for diameter as also with a negative effect for stalk number. In relation to the quality parameters, 18 marker trait associations were found for Brix, 19 for Pol, and 12 for fibre. For fibre, 58% of the QTLs detected showed a negative effect on this trait. Some makers associated with QTLs with a negative effect for fibre showed a positive effect for Pol, reflecting the negative correlation generally observed between these traits.

Characterization of the Genetic Variability of a Sugarcane Commercial Cross Through Yield Components and Quality Parameters

The phenotypic characterization as well as the knowledge of the correlation among traits, is the first step to quantify the potential of a cross for further QTL (quantitative trait loci) detection. The present work aimed to evaluate the yield components and quality parameters variability of a mapping population derived from a bi-parental cross between IACSP95-3018 and IACSP93-3046 at plant cane and ratoon cane as well as to estimate the heritabilities and pair-wise correlation among the traits evaluated. The progeny clones differed significantly for the traits measures indicating the existence of significant amount of variability among them as also as the presence of transgressive clones. Broad-sense heritabilities values were generally high for stalk diameter, stalk weight, stalk height, Brix and Pol%Cane in plant cane and ratoon cane. Tones of sugarcane per hectare (TCH) were significantly correlated with stalk weight and stalk number in both years. Regarding to all the yield components, stalk number together with stalk weight were the most important components in the determination of TCH. While fiber and Pol%Cane were negative correlated showing that they are inversely correlated traits. © 2012 Society for Sugar Research & Promotion.

Anthropogenic influences on Cd, Cr,Cu, Ni, Pb and Zn concentrations in soils and sediments in a watershed with sugar cane crops at São Paulo State, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sugarcane trash management assessed by the interaction of yield with soil properties

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

PRODUCTIVITY OF CANE SUGAR: LINEAR AND SPATIAL VARIABILITY BETWEEN COMPONENTS AND TECHNOLOGICAL PRODUCTION

Nowadays, the culture of the sugarcane plays an important role regarding the Brazilian reality, especially in the aspect related to the alternative energy sources. In 2009, the municipality of Suzanapolis (SP), in the Brazilian Cerrado, an experiment was conducted with the culture of the sugarcane in a Red eutrophic, with the aim of selecting, using Pearson correlation coefficients, modeling, simple, linear and multiple regressions and spatial correlation, and also the best technological and productive components, to explain the variability of the productivity of the sugarcane. The geostatistical grid was installed in order to collect the data, with 120 sampling points, in an area of 14.53 ha. For the simple linear regressions, the plants population is the component of production that presents the best quadratic correlation with the productivity of the sugarcane, given by: PRO = -0.553**xPOP(2)+16.14*xPOP-15.77. However, for multiple linear regressions, the equation PRO = -21.11+4.92xPOP**+0.76xPUR** is the one that best presents in order to estimate that productivity. Spatially, the best correlation with yield of the sugarcane is also determined by the component of the production population of plants.