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 119 · DO #404 · 204_Popenoe_Bx30aFF5r

Collection
Wilson Popenoe (1892–1975) family papers
Item/Folder
Cinchona manuscript - correspondence, 10 January 1940–6 August 1942
Digital Object
DO #404, page 119
Collection-level dates
1882–1975
Open PDF at page 119 ↗

Page transcription

- 2 -
Succirubra from Belgian Congo: Dr. Krukoff will arrange with
contacts in Belgian Congo that seed be sent to Guatemala.

(Krukoff Calisaya): The employment of this material as root-stock
for grafting purposes will depend, of course, on the vigor seedlings
show in future.

(A-2). Grafting Problem. It was noted that success in grafting
depends on, In general: (1) Inherent ability of scion, (2) Skill
in grafting, (3) Extent of losses subsequent to grafting. Certain
clones apparently lend themselves to grafting more readily than
others. Ultimately, we shall undoubtedly have to concentrate our
grafting on this type of material.

Dr. Popence kindly agreed to return to Naranjo in November or
December and go over the problem of technique with Benitez in field.
Especial attention will be given to the grafting method commonly
used in Java, which is different from the method used by Benitez at
present. Benitez's method is used in general in grafting of Cinchona
in Guatemala today.

Hope was expressed that extent of losses susequent to grafting
would be reduced by placing grafting nurseries in more favorable
locations.

A-3. Fertilizing Problem. It was agreed that pure Ledger type
grafts at Naranjo and Merok Area, Los Andes, would be fertilized
on May 1, June 15, August 1, September 15 and November 1, 1942.
Also Ledger seedlings at these two locations which show hope of
survival. The reason for the application of this fertilizer will be
to increase supply of high-grade grafting material. We have the
following fertilizers on hand at present in Naranjo:

Sodium Nitrate    600 lbs.
Amm. Sulfate      2000 lbs.
Pot. Sulfate      1600 lbs.
Conc. Super Phosphate  1000 lbs.

To make 100 lbs. mixed fertilizer containing N 10% K2O 5% P2O5 5%
mix Sodium Nitrate 30 lbs.; Amm. Sulfate, 25 lbs.; Pot. Sulfate, 10 lbs;
Conc. Super Phosphate 14 lbs.; Sand 21 lbs.

When Sodium Nitrate gives out, use this formula: Amm. Sulfate
50 lbs.; Pot. Sulfate, 10 lbs.; Conc. Super Phosphate, 14 lbs.;
Sand, 26 lbs. (Kindness of R. F. L.).

It is clearly understood that this fertilizer program is of
secondary importance to the main planting program, and should in
no instance conflict with it.

* In addition to the above we have 900 lbs. Amm. Phosphate and
1250 lbs. Guano.