Hunt Institute for Botanical Documentation
A Research Division of Carnegie Mellon University

Hunt Institute Archives Text Discovery Platform

Search a large and growing portion of our online collections, including handwritten documents.
PROTOTYPE

This prototype uses state-of-the-art artificial intelligence, including a vision-language model (VLM) capable of reading handwritten documents as well as typed and printed text, to create searchable transcriptions of digitized materials in the Hunt Institute Archives. This makes it possible to search the textual contents of individual pages, including material that may not be described in the archival catalog.

Use Keyword search for specific words, names, dates, scientific names, or phrases. Try Semantic search (experimental) to describe a topic, question, or kind of material when you do not know the exact wording used in the documents.

About the AI-generated transcriptions

The transcriptions are generated automatically from page images and may contain errors, especially with difficult handwriting, unusual names, multiple languages, image-quality problems, or complex layouts. They are intended primarily as a discovery aid rather than authoritative transcriptions.

Each result provides the generated transcription and links to the original digitized material and associated archival description so that readings can be checked against the source. The transcription workflow uses AI models run locally by the Hunt Institute.

About Keyword and Semantic search

Keyword search is the default and matches the wording in the transcriptions. Results contain all your terms. Use quotes for an exact phrase. Substring matching is supported, so aceae can find plant-family names ending in -aceae.

Semantic search (experimental) is useful when you know what kind of material you are looking for but do not know the words used in the documents. It ranks transcribed passages by similarity of meaning, so relevant results may not contain the exact words in your query.

Semantic queries can be broad research topics, descriptions of activities or relationships, or natural-language questions. For example:

Semantic search is not a chatbot: a question is used as a search query, and the system returns archival passages that appear conceptually related to it rather than generating an answer or summary. Short descriptions and ordinary research questions generally work better than lists of disconnected keywords. Quotation marks have no special meaning in Semantic mode. Cross-language matching may work in some cases, but it should not be treated as translation.

Keyword and Semantic search are complementary. Keyword search lets you require particular wording; Semantic search can surface differently worded passages about the same subject. Depending on the research question, trying both can reveal different useful material.

Open a result: use the prominent page-and-transcription link to see the metadata, PDF, and full transcription. Keyword-search terms are highlighted in the transcription.

Archives Collections Database (ArchivesSpace): the Collection, Item/Folder, and Digital Object links open the corresponding archival records. Collection-level dates describe the collection as a whole, not necessarily the specific item or page.

If a PDF does not load: on the detail page, use the Digital Object link, click “Go to file” in ArchivesSpace, and navigate to the page number shown here.

Current limitations
  • Automated transcriptions can contain missing or incorrect text or unintended repetition. Difficult handwriting, image quality, unusual layouts, and multiple languages can reduce accuracy. Always consult the original page image when an exact reading matters.
  • Semantic search remains experimental. Its rankings are an additional discovery aid, not a complete or definitive set of relevant results, and highly ranked pages can sometimes be only broadly related.
  • This is an active prototype. Search coverage, transcriptions, functionality, and the interface may continue to change as additional archival material is processed and the system is improved.

← Back to results

Page 3 · DO #454 · 204_Popenoe_Bx33FF24r

Collection
Wilson Popenoe (1892–1975) family papers
Item/Folder
Tropical Fruits - notes, manuscript pages - chapter in outline for proposed book with Herbert Wolfe, n.d.
Digital Object
DO #454, page 3
Collection-level dates
1882–1975
Open PDF at page 3 ↗

Page transcription

2
based upon the selection of superior seedlings of local origin,
and the introduction of grafted varieties of mango from the Old World. It should be remembered,
however, that the aboriginal inhabitants of tropical America had improved many of their fruits through seed selection,
thus raising the general level of the species to make the product of greater value to man. The pineapple is probably the best example
of improvement through vegetative propagation, which was possible because superior forms were easily propagated by suckers. The art
of grafting does not seem to have been known - or, at least,
practiced, by the aboriginal Americans.

The situation today is something like this: Commercial production of citrus fruits is extending rapidly. Banana culture has
spread into several new regions, and more growers are involved than was the case half a century ago. Pineapple culture prospers in
several countries. Avocados and mangos are beginning to be planted commercially in several tropical countries, stimulated by the importance
which these fruits have attained commercially in California, Florida and several regions in the Old World. The pressing
need for crop diversification is causing horticulturists to devote attention to fruits which have not yet been commercialised on an
extensive scale. Many fruits have been included

All this interest and activity draws attention to many problems,
One of these is the local supply of good nursery stock. Throughout tropical America, nurseries producing well-formed, vigorous, accurately labelled nursery trees are
few and far between. In past years