ASRB Agricultural Research Service (ARS) - Agricultural Statistics scientist · India · Agricultural Scientists Recruitment Board (ICAR)
Original practice questions written to the published syllabus · not past papersForecasting harvests before they happen: Fisher's regression integral and weather-indices models, pre-harvest forecasts from biometric characters and farmers' appraisal, agro-meteorological and remote-sensing models, non-linear growth curves (logistic, Gompertz, Richards), and how statistical and crop-simulation models are combined.
In the exams: AICE-JRF Agricultural Meteorology 'statistical models' (present); ICAR MSc/PhD core in modelling; national crop-forecasting programmes (applied); light in national exams
How our questions for ASRB Agricultural Research Service spread across the units of Crop Forecasting, Weather-Based Models & Non-linear Growth Models. Difficulty: 22 easy, 35 medium, 0 hard.
| Pre-harvest forecasting: purpose and history | 8 | |
| Non-linear growth models: logistic, Gompertz, Monomolecular and Richards | 8 | |
| Evaluation of forecasts and their use in policy | 8 | |
| Models using plant biometric characters | 6 | |
| Farmers' eye estimates and appraisal-based forecasts | 6 | |
| Weather-based models: Fisher's regression integral and weather indices | 6 | |
| Agro-meteorological and composite models | 6 | |
| Remote-sensing-based yield forecasting with vegetation indices | 6 | |
| Fitting non-linear models: iterative estimation and goodness of fit | 3 |
Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.
A district's forecast area under wheat is 85,000 hectares and its forecast yield is 3.2 tonnes per hectare. What is the forecast production?
C. 272,000 tonnes
Production = area x yield = 85,000 x 3.2 = 272,000 tonnes. Dividing area by yield gives 26,563; adding them gives a meaningless 88,200; 2,720,000 is a decimal slip.
Further reading: ICAR-IASRI crop forecasting reports; Fisher (1924)
In the traditional anna (annewari) system of crop assessment, what does a rating of 16 annas indicate?
D. A normal crop
The anna system expresses expected outturn in annas of a rupee, with 16 annas meaning a normal crop; lower values indicate shortfalls and are used in some states to declare scarcity.
Further reading: ICAR-IASRI crop forecasting reports; Fisher (1924)
In an objective yield survey of the kind run by the US national agricultural statistics service, what is collected?
B. Plant counts and measurements in sample plots
Objective yield surveys lay out sample plots in fields and count and measure plants and fruit (ears, pods, bolls) to model yield, complementing farmer-reported surveys. Prices and elevator sales are not yield measurements.
Further reading: ICAR-IASRI crop forecasting reports; Fisher (1924)
Relief payments in a district depend on reported crop losses. What problem does this create for appraisal-based forecasts?
B. Appraisals may be biased downwards by the incentive
When reported losses bring payments, farmers and officials may understate yields; the bias can change with policy, so calibration must be re-estimated each season.
Further reading: ICAR-IASRI crop forecasting reports; Cochran, Sampling Techniques (double sampling)
Weekly crop-condition ratings report the share of a crop in classes from very poor to excellent. How are they turned into a yield forecast?
D. By regressing past final yields on past condition shares
Condition ratings are subjective; their link to yield is estimated from past years by regressing final yields on the shares or an index built from them, the same calibration logic as for appraisals.
Further reading: ICAR-IASRI crop forecasting reports; Cochran, Sampling Techniques (double sampling)
Which sensor type is preferred for mapping monsoon (kharif) rice when optical images are cloud-covered?
C. Synthetic aperture radar
SAR is an active microwave sensor that sees through cloud; flooded rice fields at transplanting have a distinctive backscatter, which makes SAR the standard tool for kharif rice.
Further reading: Jones, Plants and Microclimate; remote-sensing crop monitoring literature
For a logistic curve with asymptote K = 100 g per plant and rate r = 0.5 per week, what is the maximum absolute growth rate?
D. 12.5 g per plant per week
dY/dt = rY(1 - Y/K) is greatest at Y = K/2, giving rK/4 = 0.5 x 100/4 = 12.5. rK = 50 forgets the (1 - Y/K) factor; rK/e is the Gompertz maximum rate.
Further reading: Ratkowsky, Nonlinear Regression Modeling; Seber and Wild, Nonlinear Regression
Which growth model has no inflection point, with the growth rate highest at the start and declining steadily?
D. The monomolecular model
The monomolecular (Mitscherlich) model dY/dt = r(K - Y) gives a concave curve with no inflection. The logistic, Gompertz and Richards (m = 1 is the logistic) are sigmoid.
Further reading: Ratkowsky, Nonlinear Regression Modeling; Seber and Wild, Nonlinear Regression
Over ten years, a ministry's first advance estimate of rice production has been revised downwards in nine years. What does this suggest?
C. Early estimates have a systematic upward bias
Revisions consistently in one direction indicate bias in early estimates; users will learn to discount them, and the method needs correction.
Further reading: Hyndman and Athanasopoulos, Forecasting: Principles and Practice; ICAR-IASRI reports
Why should forecast accuracy be reported separately at district and state level?
A. Errors partly cancel when districts are summed
Independent district errors partly offset in the sum, so a system can be accurate for a state and poor for districts; users at each level need the relevant accuracy.
Further reading: Hyndman and Athanasopoulos, Forecasting: Principles and Practice; ICAR-IASRI reports
Ten here, 57 in the app. The Laisha app has every practice question we have written to ASRB Agricultural Research Service in this subject, marked as you go, with timed papers, a jump-to-unanswered list and a certificate when you pass at 70 per cent.
Free for ten days, then one subscription of US$10 a month. We would rather say so here than have you find it later.
An AI operating system for agriculture: free guides, manuals and tools written for every country.