13 extractive question-and-answer pairs built from Assessing genetic diversity of tomato (Solanum lycopersicum) genotypes cultivated under protected condition | The Indian Journal of Agricultural Sciences, published by epubs.icar.org.in. Source-evidenced topics include genetic diversity, tomato, solanum lycopersicum, genotypes, protected condition, icar-indian agricultural research institute, genetic variability, character association. 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: 7 list, 5 factual, 1 summary. 8 of the 13 pairs (61.5%) ask explanatory questions; the remaining 5 are factual or table-based questions. 92.31% of rows pass the corpus quality gate.
This dataset contains 13 extractive question-and-answer pairs derived from a study on the genetic diversity of tomato (Solanum lycopersicum) genotypes cultivated under protected conditions. The research, conducted at the ICAR-Indian Agricultural Research Institute, analyzed 36 tomato genotypes across 16 traits to understand genetic variability and character associations. Methods such as correlation and genetic divergence analyses were employed, and principal component analysis identified key traits contributing to variability. The dataset also includes metadata about The Indian Journal of Agricultural Sciences, where the study was published.
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df = desidata.load("epubs-icar-org-in-9a77c118c0d07b455a0eb2ae575f885e")
df.head()First 10 of 13 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_document | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|---|
| What did the variance analysis reveal about the tomato genotypes? | notable variations among genotypes | Present study was carried out during 2018–19 and 2019–20 at ICAR-Indian Agricultural Research Institute, New Delhi to evaluate 16 quantitative and qualitative traits of 36 genotypes of Tomato (Solanum lycopersicumL.) and to examine the genetic variability and character association between yield and its component traits. This investigation involved correlation and genetic divergence analyses to gain insights into the relationships among the various traits. The variance analysis revealed notable variations among genotypes, indicating a substantial level of genetic diversity among them. Among the genotypes, 178 and 115 were found promising for both yield and quality traits. Genotype no. 178 was found superior for fruit weight and yield. | 491 | summary | 0.890 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | The variance analysis revealed notable variations among genotypes, indicating a substantial level of genetic diversity among them. | p[0] | 0.700 | valid | |
| What methods were used to analyze the relationships among tomato traits? | correlation and genetic divergence analyses | Present study was carried out during 2018–19 and 2019–20 at ICAR-Indian Agricultural Research Institute, New Delhi to evaluate 16 quantitative and qualitative traits of 36 genotypes of Tomato (Solanum lycopersicumL.) and to examine the genetic variability and character association between yield and its component traits. This investigation involved correlation and genetic divergence analyses to gain insights into the relationships among the various traits. The variance analysis revealed notable variations among genotypes, indicating a substantial level of genetic diversity among them. Among the genotypes, 178 and 115 were found promising for both yield and quality traits. Genotype no. 178 was found superior for fruit weight and yield. | 350 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | This investigation involved correlation and genetic divergence analyses to gain insights into the relationships among the various traits. | p[0] | 0.700 | valid | |
| What traits are associated with component 3 in the principal component analysis? | number of fruit and number of fruit/cluster | The principal component analysis indicated that the first 3 components i.e. component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. The yield exhibited significant positive correlation with average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg). | 237 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. | p[0] | 0.700 | valid | |
| What traits were analyzed in the first component of the principal component analysis? | equatorial diameter, average fruit weight and fruit weight uniformity | The principal component analysis indicated that the first 3 components i.e. component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. The yield exhibited significant positive correlation with average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg). | 89 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. | p[0] | 0.700 | valid | |
| What traits were included in component 2 of the principal component analysis? | number of locule and equatorial/polar index | The principal component analysis indicated that the first 3 components i.e. component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. The yield exhibited significant positive correlation with average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg). | 174 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. | p[0] | 0.700 | valid | |
| Which indexing services include The Indian Journal of Agricultural Sciences? | Elsevier Scopus, Clarivate Analytics ESCI, DOAJ. | This work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4. International License. The copyright of the articles published inThe Indian Journal of Agricultural Sciencesis vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR. Print ISSN:0019-5022Online ISSN:2394-3319NAAS Rating (2026):6.7WoS Impact Factor (June 2026):0. Indexedin Elsevier Scopus, Clarivate Analytics ESCI, DOAJ.Plagiarism checkby iThenticate.The work is licensed underAttribution-NonCommercial-NoDerivatives 4. | 727 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | Indexedin Elsevier Scopus, Clarivate Analytics ESCI, DOAJ.Plagiarism checkby iThenticate.The work is licensed underAttribution-NonCommercial-NoDerivatives 4. | ||||
| Which traits showed a significant positive correlation with yield? | average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg) | The principal component analysis indicated that the first 3 components i.e. component 1 (equatorial diameter, average fruit weight and fruit weight uniformity); component 2 (number of locule and equatorial/polar index); and component 3 (number of fruit and number of fruit/cluster) collectively accounted for 81.48% of the variability. The yield exhibited significant positive correlation with average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg). | 394 | list | 0.820 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | The yield exhibited significant positive correlation with average fruit weight (g), pericarp thickness (cm), polar diameter of fruit (cm), equatorial diameter of fruits (cm) and average fruit weight after each harvest (kg). | p[0] | 0.700 | valid | |
| Which tomato genotypes were identified as promising for both yield and quality traits? | 178 and 115 | Present study was carried out during 2018–19 and 2019–20 at ICAR-Indian Agricultural Research Institute, New Delhi to evaluate 16 quantitative and qualitative traits of 36 genotypes of Tomato (Solanum lycopersicumL.) and to examine the genetic variability and character association between yield and its component traits. This investigation involved correlation and genetic divergence analyses to gain insights into the relationships among the various traits. The variance analysis revealed notable variations among genotypes, indicating a substantial level of genetic diversity among them. Among the genotypes, 178 and 115 were found promising for both yield and quality traits. Genotype no. 178 was found superior for fruit weight and yield. | 612 | list | 0.740 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | Among the genotypes, 178 and 115 were found promising for both yield and quality traits. | p[0] | 0.700 | valid | |
| Who holds the copyright for articles published in The Indian Journal of Agricultural Sciences? | Indian Council of Agricultural Research | This work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4. International License. The copyright of the articles published inThe Indian Journal of Agricultural Sciencesis vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR. Print ISSN:0019-5022Online ISSN:2394-3319NAAS Rating (2026):6.7WoS Impact Factor (June 2026):0. Indexedin Elsevier Scopus, Clarivate Analytics ESCI, DOAJ.Plagiarism checkby iThenticate.The work is licensed underAttribution-NonCommercial-NoDerivatives 4. | 213 | factual | 0.570 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | The copyright of the articles published inThe Indian Journal of Agricultural Sciencesis vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. | ||||
| Which genotype was identified as superior for fruit weight and yield? | Genotype no. 178 | Present study was carried out during 2018–19 and 2019–20 at ICAR-Indian Agricultural Research Institute, New Delhi to evaluate 16 quantitative and qualitative traits of 36 genotypes of Tomato (Solanum lycopersicumL.) and to examine the genetic variability and character association between yield and its component traits. This investigation involved correlation and genetic divergence analyses to gain insights into the relationships among the various traits. The variance analysis revealed notable variations among genotypes, indicating a substantial level of genetic diversity among them. Among the genotypes, 178 and 115 were found promising for both yield and quality traits. Genotype no. 178 was found superior for fruit weight and yield. | 680 | factual | 0.490 | https://epubs.icar.org.in/index.php/IJAgS/article/view/141287 | Among the genotypes, 178 and 115 were found promising for both yield and quality traits. Genotype no. 178 was found superior for fruit weight and yield. | p[0] | 0.700 | valid |
Read straight from the file — download or use the API URL for the full dataset.
| p[23] |
| 0.700 |
| valid |
| p[23] |
| 0.700 |
| valid |