کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8054942 1519497 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
High-throughput platform for automated sorting and selection of single seeds based on time-domain nuclear magnetic resonance (TD-NMR) measurement of oil content
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
High-throughput platform for automated sorting and selection of single seeds based on time-domain nuclear magnetic resonance (TD-NMR) measurement of oil content
چکیده انگلیسی
Sorting and selection of individual seeds by their oil content (OC) or oil mass from larger quantities of seeds is an important step for many applications in the breeding of oil seed crops. Time-domain nuclear magnetic resonance (NMR) has proved to be a very precise method for non-destructive OC measurement of seeds; however, benchtop NMR devices are not automated for high throughput. Our objectives were to construct a high-throughput platform for (i) singling seeds from bulks, (ii) measurement of their mass, (iii) measurement of their oil mass with NMR, and (iv) either sorting the measured seeds into fractions on the basis of their OC or placement of seeds individually in matrix trays for subsequent selection based on the recorded seed data. Modules for each of these tasks, some newly developed, were linked in a novel approach by transporting single seeds between modules using a combination of pneumatic and mechanical elements, as well as software for control of the platforms' parts and for remote control. Our platform enables fully automated measurement of up to 600 seeds h−1. Maize seeds were used to demonstrate the applicability of our platform for measurements of OC and seed mass. For both traits, repeatability and accuracy were extraordinarily high. The platform proved robust and stable in long series of measurements and represents a break-through for OC determination in the breeding of maize and oil seed crops.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosystems Engineering - Volume 164, December 2017, Pages 213-220
نویسندگان
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