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 6 · DO #4765 · 231_Rogers_Bx5FF15_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
FAO - Papers Related to Izmir. Turkey Work, 1973
Digital Object
DO #4765, page 6
Collection-level dates
1948–1977
Open PDF at page 6 ↗

Page transcription

When material is being prepared, due consideration of seed viability and available amount is made. Often, the recipient is asked to increase certain accessions and send the harvest back to the institute. This cooperation is well established with several institutes.

Recipients are always asked to supply the results of their studies on the material they received from the institute. Results have started to arrive.

SEED CONSERVATION

Seed collections, coming to the cold store are:

1. Original collections, from Turkey and other countries,
2. Improved varieties, from Turkey and other countries.

Seed collections, entering cold store, go through the following procedure:

1. Visibility of the collections are checked following the rules of ISTA (International Seed Testing Association). Viability tests are repeated periodically.
2. Drying of samples is done in the drying room where hundreds of samples can be dried simultaneously. The air humidity of the room is absorbed by a dehumidifier. The seed moisture is determined by means of different methods. Then seed moisture has decreased to desirable level, the samples are transferred into moisture proof containers.
3. Storage. The seed containers are placed in cold rooms where the temperature is ±0°C. In cold storage rooms, the collections of each year are arranged in alphabetical sequence of families, genera and species. Each sample is divided to 2-3 parts (base, active and excess- if sufficient material is available) and kept separately.

Storage data have been recorded on standard forms (Form 3). Information related to viability quantity, physical location, etc. of each sample will be recorded on free formats (Form 4).

Basic research, to find out optimum storage conditions for various species, is one of the inevitable duties in "Plant Genetic Resources" activities, since there are several species dealt with and for many of them no such data available.