Paulo Sérgio Graziano Magalhães

Assessment of sugarcane trash for agronomic and energy purposes in Brazil

Due to new possibilities for using sugarcane (Saccharum spp.) trash for electricity generation, and the production of 2nd generation ethanol and others chemicals, the interest for its recovery has increased. However, the question of how much trash can be removed from sugarcane field still needs to be clarified. This study evaluated the amount of dry matter, nutrients content, structural compounds and efficiency of the enzymatic hydrolysis of the hydrothermal pretreated materials for tops and dry leaves in samples from sugarcane varieties. Tops and dry leaves present differences in nutrients content and moisture. Therefore, the amount of trash to be collected should not be simply based on percentages, but also should take into account the different fractions of the crop residues. For instance, around 80 % of N, P and K were derived from tops. Therein, the environmental indicators of the entire chain of sugarcane could be benefited because more nutrients would be recycled and less mineral fertilizers might be used for sugarcane production if tops are left on the field. Further, the tops have seven times more moisture than dry leaves and higher amounts of extractives (organic compounds of low molecular weight). Moreover, as the result of yield obtained in the pretreatment steps for dry leaves were superior to the tops and the glucose yields obtained in the enzymatic hydrolysis step were similar, it can be predicted that for second generation ethanol production, it is more viable to recover parts of the dry leaves fraction, leaving the tops on the field.

Sistema de monitoramento de perdas visíveis de cana-de-açúcar em colhedora de cana picada

In the last few years the sugar-cane mechanical harvested area has increased, especially in regions with appropriated slop. The use of this technology brings some inconveniences, such as, the increase in the percentage of extraneous matter, which causes the reduction of technological quality of the raw material, and losses in the field. Extraneous matter (trash) is composed of tops and leaves in major percentage, plus soil and roots, and eventually some metal parts. In the green cane harvest system the percentage of extraneous matter has a tendency to increase due to the great amount of vegetal matter to be processed. The increase in the blower fan speed to reduce the amount of extraneous matter can lead to an unacceptable economic level of raw material losses. The main objective of this work was, using a cane loss monitor, to evaluate and quantify the amount of visible losses of sugar cane through the primary extractor at two different fan speeds. Afterwards these losses were related to the harvester cleaning efficiency. The piezoelectric transducer shows a reasonable sensibility. The results show that the cleaning efficiency in the primary extractor (85% mean), the cane losses (between 5.68% and 2.15%) and fan speed are interrelated. The total losses and specially splinters (between 3.19% and 0.91%), showed a significant difference among the treatments.

Penetrógrafo eletrônico automático

This paper presents the development of an automatic recording penetrometer, which operates at the touch of a button. It incorporates a data acquisition system, which can store data of 187 tests and has a serial PC interface. The test characterization such as dates, location (latitude and longitude) can be recorded as well. The maximum working depth may be set and the load cell calibration can be verified through a keyboard with 2 lines display. A speed variation error of < 5% compared to ASAE standard was verified for cone indices between 500 and 5,684 kPa. The equipment is compact, easy to handle and can realize one test every minute.

Análise dos atributos do solo e da produtividade da cultura de cana-de-açúcar com o uso da geoestatística e árvore de decisão

One of the challenges of precision agriculture is to offer subsidies for the definition of management units for posterior interventions. Therefore, the objective of this work was to evaluate soil chemical attributes and sugarcane yield with the use of geostatistics and data mining by decision tree induction. Sugarcane yield was mapped in a 23ha field, applying the cell criterion, by using a yield monitor that allowed the elaboration of a digital map representing the surface of production of the studied area. To determine the soil attributes, soil samples were collected at the beginning of the harvest in 2006/2007 using a regular grid of 50 x 50m, in the depths of 0.0-0.2m and 0.2-0.4m. Soil attributes and sugarcane yield data were analyzed by using geostatistics techniques and were classified into three yield levels for the elaboration of the decision tree. The decision tree was induced in the software SAS Enterprise Miner, using an algorithm based on entropy reduction. Altitude and potassium presented the highest values of correlation with sugarcane yield. The induction of decision trees showed that the altitude is the variable with the greatest potential to interpret the sugarcane yield maps, then assisting in precision agriculture and, revealing an adjusted tool for the study of management definition zones in area cropped with sugarcane.

Sistema de sincronismo entre a colhedora de cana-de-açúcar e o veículo de transbordo

One of the problems found in mechanical harvest of sugar cane is the lack of synchronism between the harvest machine and the infield wagon, causing crop losses as well as operational capacity. The objective of the present research was to design a system capable of helping to synchronize the sugar cane harvest machine with the wagon. The communication between tractor and harvest machine is wireless. Two ultrasound sensors coupled to the elevator and a microprocessor manage such information, generating a correct synchronization among the machines. The system was tested in laboratory and on field performing its function adequately, maintaining the two machines in synchronization, indicating and alerting the operators their relative positions. The developed system reduced the sugar cane lost in 60 kg ha-1 comparing to the harvest with the system turned off.

Correlation of physical and chemical attributes of soil with sugarcane yield

O objetivo deste trabalho foi avaliar as correlacoes entre a produtividade da cana‑de‑acucar e alguns atributos fisicos e quimicos do solo. Para isso, uma area de 42 ha, em Araras, SP, foi selecionada. As propriedades do solo foram determinadas a partir de amostras coletadas no inicio da safra 2003/2004, por meio de uma grade regular de 100x100 m. A produtividade foi avaliada por meio de um monitor de produtividade (Simprocana). Analises de correlacao foram realizadas entre a produtividade da cana‑de‑acucar e as seguintes propriedades do solo: pH, pH CaCl 2 , N, C, indice de cone, teor de argila, materia orgânica, P, K, Ca, Mg, H + Al, capacidade de troca cationica e saturacao por bases. Os coeficientes de correlacao foram respectivamente de ‑0,05, ‑0,29, 0,33, 0,41, ‑0,27, 0,22, 0,44, ‑0,24, traco, ‑0,06, 0,01, 0,32, 0,14 e 0,04. As correlacoes de atributos quimicos e fisicos do solo com a produtividade da cana‑de‑acucar sao baixas, por si mesmas, e nao sao capazes de explicar a variacao na produtividade da cana‑de‑acucar, o que indica que, alem das propriedades do solo, outras variaveis devem ser analisadas.

Height estimation of sugarcane using an unmanned aerial system UAS based on structure from motion SfM point clouds

ABSTRACT The use of unmanned aerial systems (UAS) as remote-sensing platforms has tremendous potential for obtaining detailed, site-specific descriptions of crop features, which would be very useful for precision agriculture. In sugarcane plantations, for example, cane height can be an indicator of yield and other parameters because it is highly influenced by the soil, total sugar content, leaf nitrogen content, temperature and light intensity. This article describes the generation of crop surface models (CSMs) from high-resolution images that were obtained using a UAS to estimate sugarcane height. Using a UAS with an on-board RGB camera, we created densified three-dimensional point clouds of the study area in two different flight line directions (North/South and East/West) using structure from motion (SfM) with multi-view stereo (MVS). Then, the digital surface model (DSM) and digital terrain model (DTM) were extracted and used to create CSMs. Maps of sugarcane height were created based on this information. We investigated the influences of different flight line directions (N/S and E/W) on sugarcane height estimations and their accuracy by comparing our maps with ground references. From the validation conducted using both flight lines, the average heights were closer to the field-verified data. The resulting maps showed differences in sugarcane height that were confirmed by field measurements. This method has potential for future use by sugarcane-related industries, researchers and farmers to estimate average crop height.

How much sugarcane trash should be left on the soil

Large amounts of crop residues are preserved when sugarcane is harvested mechanically, without previous burning. When all this started, many problems associated with trash (or straw, treated here as synonyms) preservation emerged. Later, it was realized that this residue is a valuable asset for both energy production and soil preservation. There is not a well established tradeoff as to whether the trash should be used for energy production or be left in the field. Are these conflicting options? Therefore, there is an unanswered question about if and how much sugarcane trash could be removed from the cultivated fields without jeopardizing long term soil quality and plant productivity. The ethanol industry wants to remove as much trash as possible from the field but this decision must take into account many factors and variables.In this context, the present special edition of

Spatial variability of soil attributes and sugarcane yield in relation to topographic location

Soils submitted to the same management system in places with little variation of landscape, manifest differentiated spatial variability of their attributes and crop yield. The aim of this work was to investigate the correlation between spatial variability of the soil attributes and sugarcane yield as a result of soil topography. To achieve this objective, a test area of 42 ha located at the Sao Joao Sugar Mill, in Araras, in the State of Sao Paulo, Brazil, was selected. Sugarcane yield was measured with a yield monitor fitted in a sugarcane harvester and GPS signal. A total of 170 soil samples were taken at regular 50 m grid, at a depth of 0 - 0.2 m. The area under study was divided into two sites based on topography. The following soil attributes were analysed: organic matter (OM) content, exchangeable potassium (K), calcium (Ca) and magnesium (Mg), their base saturation percentage (%BS), cation exchange capacity (CEC), pH, clay, silt, total sand and density. The use of landscape and geostatistics enable defining areas with different spatial variability in soil attributes and crop yield, providing the visualization and definition of homogeneous management zones. The largest spatial variability of soil attributes and sugarcane yield was in the lowest part of the field.

A computational environment to support research in sugarcane agriculture

Abstract Sugarcane is an important crop for tropical and sub-tropical countries. Like other crops, sugarcane agricultural research and practice is becoming increasingly data intensive, with several modeling frameworks developed to simulate biophysical processes in farming systems, all dependent on databases for accurate predictions of crop production. We developed a computational environment to support experiments in sugarcane agriculture and this article describes data acquisition, formatting, storage, and analysis. The potential to support creation of new agricultural knowledge is demonstrated through joint analysis of three experiments in sugarcane precision agriculture. Analysis of these case studies emphasizes spatial and temporal variations in soil attributes, sugarcane quality, and sugarcane yield. The developed computational framework will aid data-driven advances in sugarcane agricultural research.