21
Apr

Simulating postrainy sorghum yield response to on-station N management in India

Low residual soil moisture and limited nitrogen (N) inputs have in the last few decades stunted the productivity of postrainy (rabi) sorghum, a key multipurpose cereal crop for subsistence farmers of central India. Its adaptability to the harsh abiotic constraints of semi-arid tropical systems is one of the reasons it is preferred on marginal lands.

Yield difference between farmers practice (FP) and optimum N practice (OS) was negative in low yielding environments.

Yield difference between farmers practice (FP) and optimum N practice (OS) was negative in low yielding environments.

Sorghum is known to respond well to additional nitrogen (N) application in on-station trials. We tried to test if a sufficient dose of N on-station (OS) would significantly enhance postrainy sorghum production. Also, how relevant is typical on-station N management in screening material for postrainy sorghum cultivation under farmer conditions?

Frequency of years with grain yield advantage due to on-station N practice. The yellow and red squares signify higher likelihood of grain yield loss while the light and dark blue squares signify higher likelihood of grain yield gain due to on-station N application (OS).

Frequency of years with grain yield advantage due to on-station N practice. The yellow and red squares signify higher likelihood of grain yield loss while the light and dark blue squares signify higher likelihood of grain yield gain due to on-station N application (OS).

To test this, 83 districts in central India were identified to simulate postrainy sorghum yields through the sorghum module of APSIM platform (v7.6). Soil information was compiled from the National Bureau of Soil Survey and Land Use Planning (NBSS-LUP) and World Soil Information (ISRIC). Fifty years’ meteorological data was generated by Marksim (v1.0). Sorghum crop management was reconstructed based on the recommendations described in Trivedi et al. 2008.

Sorghum cultivar Maldandi (M 35-1) was used in the APSIM simulation. Since before using the APSIM model for validation and further application, it needs to be calibrated with cultivar plant type coefficients (i.e., duration of phenophases, leaf initiation rate, leaf appearance rate and other crop growth parameters data), the values of the coefficients estimated by Ravi Kumar et al. 2009 and Kholova et al. 2013, 2014 were used.

The compiled soil information, meteorological data, reconstructed crop management recommendations and the relevance of such a set-up was tested against observed yields and meteorological records.

Simulation of canopy growth dynamics with low N application (orange line is farmer practice) and non-limiting N application (blue line is on-station N practice) along with associated grain yield (GY). The well-fertilized crop failed to yield (purple line) while the lower dose of N application resulted in crop yields of ~900 kg/ha (red line).

Simulation of canopy growth dynamics with low N application (orange line is farmer practice) and non-limiting N application (blue line is on-station N practice) along with associated grain yield (GY). The well-fertilized crop failed to yield (purple line) while the lower dose of N application resulted in crop yields of ~900 kg/ha (red line).

The first set of baseline simulations were carried out with the recommended farmer practice (FP) of applying 20 kg urea/ha as a starter dose and 20 kg urea/ha as top dressing. The second set was carried out using the typical on-station N practice of applying 50 kg DAP/ha as a starter dose and 100 kg urea/ha as top dressing. Grain and stover yields generated under on-station N management were compared to the farmer practice and the frequencies of yield advantage of OS over FP were calculated for all simulation units and projected onto a map.

The on-station practice enhanced stover production across central India, but in low yielding environments average yield was 1500 kg/ha with significant grain yield loss.  This was on expected lines. Well-fertilized crops establish larger canopy earlier in the season which reflects in higher crop demand for transpiration and leads to earlier water depletion from the soil. Therefore, on-station crops face water stress earlier in the season with less moisture available to facilitate grain-filling processes.

Simulation of crop water depletion dynamics during the season. S/D is the water supply/demand ratio (the lower the ratio, the larger the stress effect on the crop); the orange line stands for crop grown with limited N input (farmers practice) where stress begins later in the season compared to the blue line which is the water stress trajectory of the crop raised using on-station N practice.

Simulation of crop water depletion dynamics during the season. S/D is the water supply/demand ratio (the lower the ratio, the larger the stress effect on the crop); the orange line stands for crop grown with limited N input (farmers practice) where stress begins later in the season compared to the blue line which is the water stress trajectory of the crop raised using on-station N practice.

Our study showed that of the 83 districts investigated, only 19 with deep vertisols and high soil water holding capacity are likely to benefit from on-station N practice in terms of production. This small modelling exercise clearly demonstrated the futility of on-station experimental set-ups in developing elite material of postrainy sorghum in India. Loss in grain production will be the inevitable result in a majority of postrainy sorghum production areas.

About the author:

Dr. Swarna Ronanki, Scientist (Agronomy) ICAR-Indian Institute of Millets Research Hyderabad.

Leave a Reply

Time limit is exhausted. Please reload CAPTCHA.

You are donating to : Science Info Platform

How much would you like to donate?
Would you like to make regular donations? I would like to make donation(s)
How many times would you like this to recur? (including this payment) *
Name *
Last Name *
Email *
Phone
Address
Additional Note
paypalstripe
Loading...
Top
Facebook
Twitter
Flickr
YouTube
Slide share
LinkedIn
RSS