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 54 · DO #4870 · 231_Rogers_Bx8FF2_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Data from Jamaica Dept. Agric. Cassava , 1953–55
Digital Object
DO #4870, page 54
Collection-level dates
1948–1977
Open PDF at page 54 ↗

Page transcription

Resume' of cassava study for Jamaica, July 12, 1954

In order that any group of plants useful to man may be most fruitful, it is essential to utilize the most productive plants of that group. Often plants are maintained merely because of some preference of an emotional nature, not for reason of most productivity.

It is impossible to make a wise choice of plants for a particular purpose unless a thorough knowledge of all clones, varieties, or species of the group under consideration is available. It is possible, with a thorough classification, to proceed with the process of selection for any purpose, whether for studies of an agronomic nature or for hybridization to produce combinations of useful characteristics or other such studies.

To provide a basis for such activities as mentioned above, an effort is being made to classify all the variants of cassava, (Manihot utilissima). The method of classification is essentially one of morphology, comparing structures of the variants to determine relationships amongst them, but the biochemical information of carbohydrate, protein and fat content are also valuable in such work. Although stem, leaf and root colors can be useful in certain cases, it is more important to base a classification on more stable characteristics such as type of branching, height of plant, shape of leaf, number of lobes of leaf, root shape and size; size shape and number of leaf bases or scars on stems, etc. No characteristic must be overlooked, no matter how insignificant it may seem, for these structures are our best indicators of the gene complement of the plants.

Although morphological rather than color characteristics are most important in classification, it is still important to record the information as to colors of various parts. These will sometimes give some preliminary indication of relationship, and it is essential that these observations must be recorded at the time of observation in the field. If not recorded at the moment all other data are collected, but memory is relied upon to give this information at a later date, the data as to colors of parts, maturity of fruit or other part is very liable to error.

In order that permanent records of the variants be kept, a system of photography and herbarium specimens of each variant must be employed. The type of specimen made (what parts to include in the specimen) and the kind of photographs to be made must be determined by an intense study of the whole group under study. No two groups (other than closely related groups) will have the same requirements to provide the soundest data for classification. This can be accomplished best by constant observation in the field, and cannot be expected to be done in a very short period. The value of "museum" plots in such a study cannot be over-estimated; these provide a constant source of new information.

These considerations apply to my study of cassava. They are of equal value in the study of any particular group. It is a valuable technique if employed consistently and competently.