Acetone was investigated and found to be an appropriate alternative to Triton X-100 as a solvent of essential oils in bioassays aimed to investigate their effects on pinewood nematode (Bursaphelenchus xylophilus) mortality. Therefore it was used as dilution agent to screen the effectiveness of fifty two essential oils against this pest. Thirteen essential oils were highly effective, resulting in more than 90% pinewood nematode mortality at 2 mg/mL, with six of them resulting in 100% mortality. LC₁₀₀ values ranged between 0.50 mg/mL and 0.83 mg/mL for the essential oils of Origanum vulgare and Satureja montana, respectively. Essential oils were submitted to gas chromatography and gas chromatography-mass spectrometry analysis and their chemical composition established. Data from essential oils with 100% mortality at 2 mg/mL and other essential oils previously found to have LC₁₀₀ ≤ 2 mg/mL was combined, their chemical profiles investigated by correspondences analysis plus automatic classification.

This paper presents a dataset of seed volumes calculated from length, width, and when available, thickness, abstracted from printed literature—essentially scientific journals and books including Floras and illustrated manuals, from online inventories, and from data obtained directly by the authors or provided by colleagues. Seed volumes were determined from the linear dimensions of seeds using published equations and decision trees. Ways of characterizing species by seed volume were compared and the minimum volume of the seed was found to be preferable. The adequacy of seed volume as a surrogate for seed size was examined and validated using published data on the relationship between light requirements for seed germination and seed size expressed as mass.

Datasets containing information on seed size have been published and are currently available. Nevertheless, there is a lack in the literature of a dataset dedicated to seed shape. We present a preliminary version for a dataset on seed morphology based on a comparison of seed shape with geometric figures. Similarity of the outline of seed images with geometric models is considered as a basis to classify seeds according to the geometric figures they resemble (e.g., ellipse, oval, cardioid). This allows, first, the classification of plant species according to their geometric type of seed, and second, seed shape quantification. For each seed image, the percent of similarity of their outline with a geometric figure can be calculated as a J index. Similarity in absolute terms is considered only when the J index >90. This criterion is important to avoid ambiguity and increase discrimination. The dataset opens the possibility of studying the relationship between seed shape and other variables such as seed size, genome complexity, life form or adaptive responses.