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DRAINAGE OF IRRIGATED LANDS<br />

C. B. DANDEKAR 1 , B. A. CHOUGULE 2<br />

1<br />

C. B. DANDEKAR, Executive Director, Rex Polyextrusion Ltd, Kumar’s Plaza, North Shivajinagar, Sangli, India, cbdandekar@rediffmail.com. 2<br />

B. A. CHOUGULE, Ex. Officer In-charge, Agricultural Research Station Kasabe Digraj, Maharashtra, India; currently Rex Polyextrusion Ltd,<br />

Kumar’s Plaza, North Shivajinagar, Sangli, India, ssdproj@rexpoly.co.in.<br />

CSBE100037 – Salinity affects millions of hectares of once productive land in many countries.<br />

Besides economic losses, rapid salinization of land and water resources is inflicting environmental<br />

damage, particularly in irrigated areas where salinity increase has charted a parallel path with<br />

irrigation development. However, irrigated land use as such is not responsible for salinization, but<br />

it is the faulty irrigation practices, inadequate provision of drainage and lopsided economic<br />

incentives that play a major role. Different measures including surface, subsurface and biodrainage<br />

systems have been adopted to prevent/mitigate and reclaim the affected areas. Large scale<br />

adoption of mechanized subsurface drainage (SSD) systems is at its inception stage. Experiences<br />

from large scale SSD installations in the northern states of Haryana, Rajasthan and Maharashtra<br />

have evidenced that the technology can be successfully adopted in reclaiming saline and<br />

waterlogged lands while surface drainage and bio-drainage have limitations and do not show<br />

improvement in soil and crop productivity. Two large scale SSD projects were installed on 2165<br />

ha at Dudhgaon and Kasabe Digraj in Sangli district of Maharashtra (India) in the year 2005 to<br />

2008. There is good improvement in the soil properties of affected lands within one year due to<br />

SSD installation in the fields. The pH decreased from 8.11 to 7.63, the soil conductivity EC from<br />

8.11 to 4.60 dS/m, SAR from 7.10 to 3.94 and ESP from 9.31 to 4.60; which shows improvement<br />

in salt affected soils. Yield of sugarcane increased from 75 T/ha to 172 T/ha within a year.<br />

MONITORING OF GRAIN QUALITY AND SEGREGATION OF GRAIN ACCORDING<br />

TO PROTEIN CONCENTRATION THRESHOLD LEVEL ON AN OPERATING<br />

COMBINE HARVESTER<br />

HILKE RISIUS 1 , JUERGEN HAHN 1 , HUBERT KORTE 2<br />

1 H. Risius, Humboldt-Universitaet zu Berlin, Germany, Biosystems Engineering Division, hilke.risius@agrar.hu-berlin.de,<br />

j.hahn@agrar.hu-berlin.de. , 2 H. Korte, CLAAS SE GmbH, Germany, hubert.korte@claas.com.<br />

1 J. Hahn,<br />

CSBE100043 – Quality has become an essential attribute of agricultural products and production<br />

processes in particular as a result of European Commission Regulations. Moreover, sorting of grain<br />

based on protein concentration could enable growers to realise price premiums in value-added<br />

markets. The variability of soils, topography and fertility are known to influence grain yield and<br />

quality. Interdependency of these factors has also been considered as limitation for site-specific<br />

nitrogen management strategies. The aim of this collaborative research project is to monitor protein<br />

concentration variability and to segregate grain into quantities of high or low protein content on a<br />

combine harvester. Near-infrared spectrometry (NIRS) was used to determine protein<br />

concentration of winter wheat and spring barley in both diffuse reflection and diffuse transmission<br />

in field trials in Brandenburg and Thuringia. Performance characteristics were obtained during the<br />

2008 and 2009 field trials, a total of 300 ha of wheat and 60 ha of barley were harvested. Protein<br />

predictions correlated well with reference measurements (Barley: R2 = 0.94, SEP = 0.31 %;<br />

Wheat: R2 = 0.96, SEP = 0.33 %). Deviations of NIRS analysis results beyond the calibration error<br />

were logged constantly and helped to ensure correct grain tank filling. Process data were also<br />

classified using principal component analysis (PCA), the prediction range of protein values, their<br />

standard deviation as well as the hotelling T2-statistics. Segregation results are accurate and<br />

promising for implementation as a tool to improve grain marketing. […].<br />

28<br />

XVII th World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR) – Québec City, Canada – June 13-17, 2010

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