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 48 · DO #478 · 204_Popenoe_Bx33FF48r

Collection
Wilson Popenoe (1892–1975) family papers
Item/Folder
Cinchona Cultivation in Guatemala - manuscripts, notes, copies, n.d.
Digital Object
DO #478, page 48
Collection-level dates
1882–1975
Open PDF at page 48 ↗

Page transcription

-16-

is cut off several inches above the graft. In about one year's time the
graft is ready to be transplanted to its permanent place in the field.

It may be mentioned here that the art of grafting is something
which can be learned by experience much better than by written description.
During the past year, several young Guatemalan agriculturists have been trained
by Jorge M. Benitez to do this work and have been practicing it very successfully.
Those who desire to learn the art will probably save time and disappointment
by spending a few weeks working with an experienced man, rather
than attempting to master the art by themselves.

The best months for grafting Cinchona in Guatemala seem to be
June and July, though the work can be carried out successfully at any time
between the onset of the rains in May and the season of heavy rains in
September. The main thing is to remember that grafting is most successful in
moist weather, but not during the period of heavy rains.

FIELD CULTURE

Obviously we still have much to learn in Guatemala regarding the
treatment to be given Cinchona trees in the field. As yet there are no
commercial plantings on which to base recommendations. At the start we must
be guided largely by experience in other regions.

Here as elsewhere few difficulties attend the transplanting of trees
from the nursery (almacigo) to the field. They can be moved with bare roots
provided that they are not kept out of the ground more than a day or two.
Proper spacing in the field requires further experimentation here. In Java it
is customary to plant from three to four feet apart. As the trees grow and
begin to crowd one another, they are thinned out and the trees which are
removed in this process are used for the extraction of quinine. This is
continued year after year until the entire planting is dug up at the end of