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D. L. N. Rao et al.
broad recommendations for fertilizer usage as for example sugarcane in Karnataka,
India could lead to insufficient nutrient application. With the availability of soil
fertility maps at watershed and mandal and district level, fertilizer recommendations
based on such maps can form the basis of precision farming.
In another subset, site-specific nutrient management (SSNM) aims at optimizing
agriculture production by managing both the crop and the soil to improve yields
and nutrient uptake. This was developed for irrigated rice systems for Asia by IRRI
in 1996 [23] and subsequently tested in more than 200 irrigated rice farms across
Asia. It focused on managing field-specific spatial variation in indigenous NPK
supply, temporal variability in plant N status occurring within a growing season and
medium-term changes in soil P and K supply resulting from actual nutrient balance.
The approach required a data management option to predict soil nutrient supply and
plant uptake in absolute terms in the high-yielding irrigated rice systems in Asia.
A modified QUEFTS model [41, 103] was used for this purpose. It described the
relationship between grain yield and nutrient accumulation as a function of climatic
yield potential and the supply of the three macronutrients. In a situation of balanced
nutrition, the QUEFTS model assumed a linear relationship between grain yield and
plant nutrient uptake at constant internal efficiencies until yield targets reach about
70–80% of yield potential. As yields approach the potential yield, the internal nutrient
efficiencies decline as the relationship between grain yield and nutrient uptake enters
a non-linear phase. To model this in a generic sense required the empirical determination of two boundary lines describing the minimum and maximum internal
efficiencies of N, P and K in the plant across a wide range of yields and nutrient
status. A database containing more than 2000 entries on the relationship between
rice grain yield and nutrient uptake was used to derive the generic boundary lines of
internal efficiencies [22]. The balanced N, P and K uptake requirements for 1000 kg
of rice grain yield were estimated from the respective envelope functions as 14.7 kg
N, 2.6 kg P and 14.5 kg K, which is valid for the linear phase of the relationship
between yield and nutrient uptake. The corresponding borderlines for describing the
minimum and maximum internal efficiencies were estimated at 42 and 96 kg grain
kg
−1 N, 206 and 622 kg grain kg
−1 P and 36 and 115 kg grain kg
−1 K, respectively
[103]. The parameters were found to be valid for any site in Asia at which modern
rice varieties with a harvest index of about 0.45–0.55 were grown. A study of 179
rice farms in 6 Asian countries found that SSNM led to yield increases of 7% and
total profitability increases of 12% [24].
Various fertilizer decision support tools to implement 4R nutrient stewardship
(right source, right rate, right time and right place) like Nutrient Expert combined
with ‘Green Seeker’ to guide fertilization improved the N use efficiency and reduced
the environmental footprint of wheat production under no-till in North-west India
[82]. In North-central China [106] fertilizer recommendation from Nutrient Expert
for summer maize improved the yields, reduced N fertilizer by 35%, improved the
agronomic efficiency of N and reduced N 2 O and total GHG emissions by 17–18%
over soil test-based fertilizer recommendations.
D. L. N. Rao et al.
broad recommendations for fertilizer usage as for example sugarcane in Karnataka,
India could lead to insufficient nutrient application. With the availability of soil
fertility maps at watershed and mandal and district level, fertilizer recommendations
based on such maps can form the basis of precision farming.
In another subset, site-specific nutrient management (SSNM) aims at optimizing
agriculture production by managing both the crop and the soil to improve yields
and nutrient uptake. This was developed for irrigated rice systems for Asia by IRRI
in 1996 [23] and subsequently tested in more than 200 irrigated rice farms across
Asia. It focused on managing field-specific spatial variation in indigenous NPK
supply, temporal variability in plant N status occurring within a growing season and
medium-term changes in soil P and K supply resulting from actual nutrient balance.
The approach required a data management option to predict soil nutrient supply and
plant uptake in absolute terms in the high-yielding irrigated rice systems in Asia.
A modified QUEFTS model [41, 103] was used for this purpose. It described the
relationship between grain yield and nutrient accumulation as a function of climatic
yield potential and the supply of the three macronutrients. In a situation of balanced
nutrition, the QUEFTS model assumed a linear relationship between grain yield and
plant nutrient uptake at constant internal efficiencies until yield targets reach about
70–80% of yield potential. As yields approach the potential yield, the internal nutrient
efficiencies decline as the relationship between grain yield and nutrient uptake enters
a non-linear phase. To model this in a generic sense required the empirical determination of two boundary lines describing the minimum and maximum internal
efficiencies of N, P and K in the plant across a wide range of yields and nutrient
status. A database containing more than 2000 entries on the relationship between
rice grain yield and nutrient uptake was used to derive the generic boundary lines of
internal efficiencies [22]. The balanced N, P and K uptake requirements for 1000 kg
of rice grain yield were estimated from the respective envelope functions as 14.7 kg
N, 2.6 kg P and 14.5 kg K, which is valid for the linear phase of the relationship
between yield and nutrient uptake. The corresponding borderlines for describing the
minimum and maximum internal efficiencies were estimated at 42 and 96 kg grain
kg
−1 N, 206 and 622 kg grain kg
−1 P and 36 and 115 kg grain kg
−1 K, respectively
[103]. The parameters were found to be valid for any site in Asia at which modern
rice varieties with a harvest index of about 0.45–0.55 were grown. A study of 179
rice farms in 6 Asian countries found that SSNM led to yield increases of 7% and
total profitability increases of 12% [24].
Various fertilizer decision support tools to implement 4R nutrient stewardship
(right source, right rate, right time and right place) like Nutrient Expert combined
with ‘Green Seeker’ to guide fertilization improved the N use efficiency and reduced
the environmental footprint of wheat production under no-till in North-west India
[82]. In North-central China [106] fertilizer recommendation from Nutrient Expert
for summer maize improved the yields, reduced N fertilizer by 35%, improved the
agronomic efficiency of N and reduced N 2 O and total GHG emissions by 17–18%
over soil test-based fertilizer recommendations.