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observed in the nutritional content of rice (Kennedy
and Burlingame, 2003). Many factors, such as cli-
mate, geography and geochemistry, agricultural
practices, post-harvest conditions and handling, as
well as genetic composition of the cultivar are
known to affect the nutrient composition of rice.
Among these factors cultivar-specific differences
have received the least attention.
Rice research in India has traditionally focused on
ways of increasing yield to match the country’s bur-
geoning population and trade. The importance of
enhancing nutritional quality to improve human
health through rice breeding is only now coming in
focus. In 2002, the International Rice Commission
recommended that the existing biodiversity of rice
varieties and their nutritional composition needed
to be explored and that nutrient content must be
among the main criteria used for selection of rice
cultivars for use in areas of food insecurity. Rice is
an important source of nutrients and breeding rice
crops with particularly enhanced nutrient concen-
tration requires knowledge of the variation in the
trait among the available germplasm. Therefore this
study was initiated in order to document the nutri-
ent composition of 269 high-yielding rice cultivars
cultivated in India. Nutrient analysis was carried out
using brown rice, the raw material for white rice.- Methodology
2.1 Sample processing
All varieties (indica subspecies) of rice were sup-
plied by the Directorate of Rice Research (ICAR), Ra-
jendranagar, Hyderabad in the form of brown rice.
Samples were powdered using cyclone mill (UDY
Corporation, USA) and stored in clean polyethylene
bottles from where aliquots were taken for analysis.
2.2 Proximate composition
Moisture, ash and dietary fibre content were as-
sayed using the Association of Official Analytical
Chemists (AOAC, 2006) methods 934.01, 942.05 and
985.29, respectively. Protein content (N X 5.95) was
determined by the AOAC Kjeldahl method (984.13).Total fat was determined by the AOAC method after
acid digestion (996.01). Carbohydrate content was
determined by calculating the difference (100 –
moisture+fat+protein+ash+total dietary fibre).2.3 Mineral analysis
Approximately 0.5 g of sample was accurately
weighed into a Teflon PFA digestion vessel to which
high purity acid mixture (3.0 mL HNO3 and 1.0 mL
H2O2) was added. Each sample was taken in dupli-
cate, sealed and digested in a microwave digestion
system (CEM, Corp. MARSXpress). After completion
of the digestion, vessels were cooled, carefully re-
moved and transferred to a 2 5 ml volumetric flask.
Analysis of calcium, copper, iron, magnesium, man-
ganese, potassium and zinc was carried out after
appropriate dilutions in an Atomic Absorption Spec-
trometer (iCE 3300 Thermo Scientific). Phosphorus
was estimated by the Fiske and Subbarow method
as described in AOAC method (931.01).2.4 Quality control
For mineral estimation a blank and a Certified Ref-
erence Material (NIST 1568a or 1547) were included
in each digestion batch for quality assurance. A
comparison of the mean content values for each of
the analyte in this study and that given in the CRM
certificate is presented in Table 1. The precision
data shows good agreement reflecting good data
quality.Table 1.Analysis of Certified Reference Material
Minerals CRM No. Sample Measured Certified
Value (mg/kg) Value (mg/kg)
Fe NIST-1 5 68a Rice Flour 7. 5 7 ± 0.16 7.4 ± 0.9
Zn NIST-1 5 68a Rice Flour 19.22 ± 0. 35 19.4 ± 0. 5
Cu NIST-1 5 68a Rice Flour 2.4 ± 0.1 55 2.4 ± 0. 3
Mn NIST-1 5 68a Rice Flour 18. 5 2 ± 0. 3 76 20.0 ± 1.6
Ca NIST-1568a Rice Flour 118 ± 2.3 118 ± 6
Mg NIST-1568a Rice Flour 560 ± 3 560 ± 20
K NIST-1 5 68a Rice Flour 1280 ± 3 .2 1280 ± 8
P NIST-1547 Peach Leaves 1360 ± 16 1370 ± 70