5 extractive question-and-answer pairs built from Advancing tuber crops research: New initiatives | Indian Horticulture, published by epubs.icar.org.in. Source-evidenced topics include tuber crops, genome editing, crispr/cas, omics technologies, machine learning, climate resilience, predictive breeding, biomarker discovery. Every answer is a verbatim span of text the source prints, and each row carries the passage it sits in, its offset in that passage, the source quote, the page and the location in the document, so any row can be checked against the original. Question types in the export: 2 list, 2 summary, 1 relationship. 5 of the 5 pairs (100.0%) ask explanatory questions; the remaining 0 are factual or table-based questions. 100.00% of rows pass the corpus quality gate.
This dataset contains five extractive question-and-answer pairs focused on advancements in tuber crop research, sourced from the publication 'Advancing tuber crops research: New initiatives' by Indian Horticulture. The questions explore topics such as genome editing, omics technologies, artificial intelligence, and machine learning, emphasizing their roles in improving tuber crops like cassava, sweet potato, yam, and aroids. The answers highlight precise trait modifications, insights into genetic variation, and the integration of traditional breeding with modern tools.
Browse more agriculture datasets, including other records from the same source when available.
Explore Agriculture datasetsAgronomic zinc biofortification of potato (Solanum tuberosum) through soil and foliar zinc sulphate application in Rajasthan | The Indian Journal of Agricultural Sciences - Question and Answer Dataset
Agriculture · 6 rows
Assessment on therapeutic value and diversity analysis in traditional rice (Oryza sativa) landraces of Tamil Nadu | The Indian Journal of Agricultural Sciences - Question and Answer Dataset
Agriculture · 13 rows
Assessment of avoidable yield losses due to insect pests and diseases in wheat (Triticum aestivum) | The Indian Journal of Agricultural Sciences - Question and Answer Dataset
Agriculture · 12 rows
Bhat (Black soybean):A sustainable choice for hill farming | Indian Farming - Question and Answer Dataset
Health · 6 rows
ICAR Annual Report 2023-24 - Question and Answer
Agriculture · 590 rows
ICAR Annual Report 2023-24 — Question and Answer Dataset
Agriculture · 590 rows
Bio-smart technologies for increasing shelf life and postharvest disease management in fruits for distant and export markets | Indian Horticulture - Question and Answer Dataset
Agriculture · 5 rows
Agricultural growth and its impact on gross state value added: An econometric analysis of major crop sectors in Haryana | The Indian Journal of Agricultural Sciences - Question and Answer Dataset
Agriculture · 9 rows
Use the API URL with your free DD token in notebooks, scripts, and pipelines.
https://www.desidata.in/api/datasets/epubs-icar-org-in-0c0806d912defd6f3ca5b96f9d729ab6/downloadDataset downloads are free. For Python or API downloads, sign in once and create a free DD token; set it as DD_TOKEN or save it in your notebook's secrets. Requests are linked to your account so your download history and counts stay accurate.
# One-time install: pip install desidata
# Set DD_TOKEN in your environment first (create a free token in Profile & settings).
import desidata
df = desidata.load("epubs-icar-org-in-0c0806d912defd6f3ca5b96f9d729ab6")
df.head()First 5 of 5 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_document | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|---|
| What does genome editing enable in tuber crops? | precise trait modification for disease resistance, nutrition, and climate resilience | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. Traditional breeding remains essential but it is strengthened by these tools. AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | 219 | summary | 0.970 | https://epubs.icar.org.in/index.php/IndHort/article/view/173664 | Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. | p[0] | 0.700 | valid | |
| What role does AI and machine learning play in tuber crop development? | accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. Traditional breeding remains essential but it is strengthened by these tools. AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | 637 | summary | 0.970 | https://epubs.icar.org.in/index.php/IndHort/article/view/173664 | AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | ||||
| What strengthens traditional breeding in tuber crops? | genome editing, omics, and AI | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. Traditional breeding remains essential but it is strengthened by these tools. AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | 141 | relationship | 0.930 | https://epubs.icar.org.in/index.php/IndHort/article/view/173664 | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. | p[0] | 0.700 | ||
| What insights do omics technologies provide for tuber crops? | genetic variation, biochemical pathways, and trait expression | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. Traditional breeding remains essential but it is strengthened by these tools. AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | 389 | list | 0.820 | https://epubs.icar.org.in/index.php/IndHort/article/view/173664 | Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. | ||||
| What technologies are revolutionizing the improvement of tuber crops? | genome editing, omics, and AI | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. Genome editing, especially CRISPR/Cas, enables precise trait modification for disease resistance, nutrition, and climate resilience. Omics technologies viz., genomics, metabolomics, and phenomics provide insights intogenetic variation, biochemical pathways, and trait expression, while integrated multi-omics enhances predictive breeding and biomarker discovery. Traditional breeding remains essential but it is strengthened by these tools. AI and machine learning accelerate data integration, linking genotype to phenotype, predicting complex traits, and enabling climate-smart, resilient, nutritionally rich and highyielding tuber crop development. | 141 | list | 0.820 | https://epubs.icar.org.in/index.php/IndHort/article/view/173664 | Tuber crops like cassava, sweet potato, yam, and aroids are vital for global food security, and their improvement is being revolutionized by genome editing, omics, and AI. | p[0] | 0.700 |
Read straight from the file — download or use the API URL for the full dataset.
| p[0] |
| 0.700 |
| valid |
| valid |
| p[0] |
| 0.700 |
| valid |
| valid |