Abstract

Teachers of agricultural English have to decide which words to put on next week’s vocabulary list, with very little to go on. Students meet English in textbooks, journal articles, lectures and communication in the field, and the commercial materials available in Japan are not necessarily corpus-based. Agricultural word lists do exist: Bunparit and Kongcharoen (2025) derived one from 6.8 million words of research articles. What such lists leave out is the specialised sense. Most of this work counts forms or families rather than senses, draws on written texts alone, and has not been tried with learners. A learner who knows stand will not know that in agronomy a stand is the density of emerged crops in a field, and a headword list leaves that gap unmarked.

This presentation reports a preliminary study towards such a list. We treated words listed in a textbook’s index as items the book itself marks as discipline-relevant, and asked how they are distributed across high-frequency (GSL 1 and 2), academic (AWL) and other vocabulary. Using AntWordProfiler, we compared an introductory agronomy textbook (Sheaffer & Moncada, 2012; 143,776 tokens) with an introductory applied linguistics textbook (Schmitt & Rodgers, 2020; 134,040 tokens). Index-listed words account for 56.83% of agronomy tokens and 43.96% of applied linguistics tokens. Of index types, 65.16% fall outside the GSL and the AWL in agronomy but only 42.38% in applied linguistics, where academic vocabulary is much better represented (22.00% of index types, against 7.73% in agronomy). Of the 640 types shared by the agronomy index and glossary, a third are high-frequency words, which suggests that stripping out high-frequency and academic vocabulary before keyword extraction would lose familiar words carrying specialised senses.

Index membership marks disciplinary importance, not technicality, and such clues are less accurate than Chung and Nation’s (2004) four-step rating scale, so these items are candidates only: the agronomy index also holds function words and words used in general senses. The next step is to replicate and extend Chung and Nation (2003), with subject experts rating vocabulary from agronomy, applied linguistics and anatomy. The longer-term aim is an openly available corpus and a sense-level list for agriculture.