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Spatial hierarchical Bayes Small Area Model for disaggregated level crop acreage estimation
PRIYANKA ANJOY, HUKUM CHANDRA, KAUSTAV ADITYA. The Indian Journal of Agricultural Sciences, 2020-10-28
Topic: Risk, prevention and care in population studies
Crop area statistics in most of the states in India are provided based on complete enumeration or census approach. But, shortage of man power, failure of the primary and revenue staffs to devote adequate time and attention in collection and compilation of data has deteriorated the quality of area statistics as well as increased the time lag in availability of data in hand. In the view of above problem, a well-designed sample survey has the ability to cater the need of accurate and timely crop area information with utilization of limited resources. A pilot study conducted by ICAR- Indian Agricultural Statistics Research Institute attempts to estimate disaggregated level crop yield based on reduced number of Crop Cutting Experiments (CCEs) while crop acreage estimation has been done through sample survey approach. But, traditional sampling theory has also some limitations in providing reliable and valid estimates particularly for districts/areas with few or negligible sample sizes. To tackle this need Small Area Estimation (SAE) approach has been considered in this paper. In particular, using Hierarchical Bayes spatial small area model disaggregated level crop area has been estimated for two major crops, rice and wheat respectively in the state of Uttar Pradesh for Agriculture year 2015-16. Estimates produced using SAE technique has acceptable precision level.
Key findings
- A pilot study conducted by ICAR- Indian Agricultural Statistics Research Institute attempts to estimate disaggregated level crop yield based on reduced number of Crop Cutting Experiments (CCEs) while crop acreage estimation has been done through sample survey approach.
- But, traditional sampling theory has also some limitations in providing reliable and valid estimates particularly for districts/areas with few or negligible sample sizes.
- To tackle this need Small Area Estimation (SAE) approach has been considered in this paper.
- In particular, using Hierarchical Bayes spatial small area model disaggregated level crop area has been estimated for two major crops, rice and wheat respectively in the state of Uttar Pradesh for Agriculture year 2015-16.
- Estimates produced using SAE technique has acceptable precision level.
Why it matters
This study is about statistical methods for crop acreage estimation in India, not Alzheimer's disease, so it does not provide information on treating, curing or preventing Alzheimer's. It found that small area estimation produced estimates with acceptable precision.
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Study details
- Evidence strengthLow
How this study scored 25/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (The Indian Journal of Agricultural Sciences) |
| Journal's citation record | 0 / 4 | The Indian Journal of Agricultural Sciences: journal h-index 44 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.4 citations a year over 8 year(s) since 2020 |
| Impact for its field and year | 1 / 6 | Cited 0.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 0 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Kaustav Aditya: h-index 10 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Indian Council of Agricultural Research: institution h-index 256 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 25 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.56093/ijas.v90i9.106627
- Original source →
- Free full text: The Indian Journal of Agricultural Sciences →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
ANJOY, P., CHANDRA, H., & ADITYA, K. (2020). Spatial hierarchical Bayes Small Area Model for disaggregated level crop acreage estimation. The Indian Journal of Agricultural Sciences. https://doi.org/10.56093/ijas.v90i9.106627
Vancouver
ANJOY P, CHANDRA H, ADITYA K. Spatial hierarchical Bayes Small Area Model for disaggregated level crop acreage estimation. The Indian Journal of Agricultural Sciences. 2020. doi:10.56093/ijas.v90i9.106627.
BibTeX
@article{anjoy2020-438bfc4c,
author = {ANJOY, PRIYANKA and CHANDRA, HUKUM and ADITYA, KAUSTAV},
title = {{Spatial hierarchical Bayes Small Area Model for disaggregated level crop acreage estimation}},
journal = {The Indian Journal of Agricultural Sciences},
year = {2020},
doi = {10.56093/ijas.v90i9.106627},
url = {https://doi.org/10.56093/ijas.v90i9.106627}
}
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