Non-destructive techniques in seed quality determination
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1 Non-destructive techniques in seed quality determination Merete Halkjær Olesen Aarhus University Science & Technology Department of Agroecology TATION presen
2 Outline Seed anatomy and the importance of seed quality (germination and seed health) Technology Non-destructive technologies used to assess various aspects of seed quality Results from PhD project Seeds Pathology 2
3 Seed anatomy Spinach seed. A: Seed with pericarp, B: True seed, brown testa, C: Perisperm, D: Embryo, E: Micropylar endosperm 3
4 Germination Any initial variation in plant size will increase as the crop matures, the larger plants in the population will continue to secure proportionally more of the resources available. Komatzuna -Mizuna -Pak Choi -Chinese -Spinach cabbage 4
5 Seed health Identification Outside or inside the seed coat Microscopy, PCR, ELISA Colour, size and shape of the fungal structures 5
6 Technologies in seed science and testing RGB imaging Hyperspectral and multispectral imaging X-ray imaging Magnetic resonance imaging (Infrared spectroscopy) Near infrared spectroscopy Chlorophyll fluorescence Oxygen measurement (respiration) Ethanol measurement (fermentation) 6
7 Multispectral imaging 19 light emitting diodes wavelengths ranging from 395 to 970 nm High-resolution camera 1280 x 960 pixel images Infected spinach seeds VIS NIR 7
8 Spectral signature of mean data Alternaria Cladosporium Fusarium Stemphylium Uninfected Verticillium Mean intensity Wavelength (nm) 8
9 Segmentation of uninfected seeds from infected seeds Raw picture CDA and treshold setting Binary morphology Test of 100 naturally infected seeds 84% uninfected detected by VideometerLab 71% uninfected observed by microscope 9
10 Multispectral imaging and germination Extended Canonical Variates NIR ECV# Sample number Extended Canonical Variates VIS ECV# Sample number Average of 300 seeds Pre-study of 25 seeds 10
11 FT-NIR spectroscopy Moving mirror Interferometer Fixed mirror Beam splitter Light source Detector sample Diffuse transmission Interferogram NIR spectrum ranging from 833 to1667 nm 30 seeds within 12 min NIR spectrum Fourier transformation 11
12 Explorative evaluation Raw Spectra of Spinach seed samples x 10-3 Obj #143 PCA Res. variance vs. T^2 [Model 1] Absorption [log (1/R)] Wavelength (cm-1) Residual variance PC# Obj #122 Obj #20 Obj Obj Obj #63 #52 Obj #228 Obj #152 Obj #288 Obj #28 #249 #60 Obj #88 #194 #116 #291 Obj #290 Obj #289 #92 Obj #312 #27 #210 Obj #172 #164 #159 #283 Obj Obj #127 Obj #301 #232 Obj Obj #133 Obj Obj #313 #9#158 #45 Obj Obj #106 Obj #121 Obj #160 #306 #296 #267 #75 #21 #104 #168 #112 #128 #46 Obj #181 Obj #41 #42 Obj Obj #74 #32 #213 #233 #222 #72 #38 Obj #248 #151 #156 #57 Obj #205 #18#144 Obj #115 #50 Obj #189 #126 #251 Obj Obj #135 #253 #294 #43 #198 #113 #124 #211 #169 #91 #82 #85 Obj #49 #149 #255 #252 Obj Obj Obj #304 #178 #65 #199 Obj #218 #86 #229 Obj #5 #167 #15 Obj #61 #24 Obj #174 #68 #161 Obj #270 Obj #58 #73 #29 #162 #163 #261 #81 #142 #134 Obj #79 #117 #51 #140 #221 Obj #26 #53 #153 #299 #33 #274 #165 #120 #64 #206 #148 #285 #316 #311 Obj Obj #281 #240 #314 #59 #37 #70 #286 #212 #269 #208 #25 #23 #94 Obj #254 #268 Obj #191 #118 Obj #130 #150 #78 #6 #278 #138 #55 #247 #123 #204 #266 #125 Obj Obj #155 Obj #177 #279 #185 #146 #260 #141 #264 #230 #17 #197 #62 #201 #202 #225 Obj #246 #175 Obj #284 #235 #132 #315 #31 #303 #234 #300 #295 #114 #287 #275 #292 #257 #66 #182 #245 #108 #239 #256 #271 #317 #84 #107 #209 #139 #190 #203 #273 #220 #69 #186 #293 #223 #180 #36 #183 #297 #154 #298 #188 Obj #242 #39 #237 #95 #216 #227 #110 #276 #54 #219 #131 #217 #103 #71 #307 #80 #244 #87 #195 #259 #90 #263 #302 #89 #258 #309 #173 #119 #40 #99 #77 #105 #93 #250 Obj #207 #265 #184 #272 #56 #226 #166 #214 #147 #76 #137 #262 Obj #215 #129 #310 #241 #67 #196 #102 #192 #282 #157 #193 #111 #231 #100 #280 #83 #44 #96 #224 #171 #34 #47 #176 #145 #305 #187 #101 #48 #12 #243 #109 #136 #170 #238 #179 #200 #308 #98 #4 #97 #277 #35 # Hotelling T^2 PC#1 (93.332%) Outlier detection (PCA plot and Hotelling s T-square versus residual variance plots for PC1) 12
13 Mean spectra 13
14 Classification (ECVA = supervised model) Spinach seed germinated at 15 o C Germination % Calibration set germ/non germ Validation set germ/non germ #PCs Correctly classified seeds (%) Normal, without pericarp Normal, with pericarp /2 108/ Aged, without pericarp /12 127/ Aged, with pericarp /15 108/
15 Scatter plot Spinach Pak choi 15
16 Assignments of NIR spectra (Osborne et al., 1993) 16
17 Conclusions Non-destructive technologies tested in my Ph.D project have proved to be valuable tools in correlation of colour and biochemical information to seed germination and health of spinach seeds Control of Verticillium in seed production fields is important and multispectral imaging can be employed as a fast seed testing method Both methods are user friendly, rapid and effiecient for testing the seeds 17
18 Thank you 18
19 Papers included in Ph.D thesis Seed health M. H. Olesen, J. M. Carstensen and B. Boelt (2010). Use of VIS-NIR system combined with multispectral image analysis in spinach seed. Proceedings of the 14th International Conference on NIR Spectroscopy M. H. Olesen, J. M. Carstensen and B. Boelt (2011). Multispectral imaging as a potential tool for seed health testing of spinach. Seed Science and Technology. 39, M. H. Olesen, R. Gislum and B. Boelt (2012). Verticillium infected soil and seed treatment evaluation in spinach seed production. Acta Agriculturae Scandinavica B. Submitted Germination M. H. Olesen, N. Shetty, R. Gislum and B. Boelt (2011). VIS-NIR imaging A tool to predict germination of spinach seed. Proceedings of the 15th International Conference on NIR Spectroscopy. Submitted M. H. Olesen, N. Shetty, R. Gislum and B. Boelt (2011). Classification of viable and non-viable spinach (Spinacia oleracea L.) seeds by single seed near infrared spectroscopy and extended canonical variates analysis. Journal of Near Infrared Spectroscopy, 19,
20 Papers not included in Ph.D thesis N. Shetty, T-G. Min, R. Gislum, M. H. Olesen, and B. Boelt (2011). Optimal sample size for predicting viability of cabbage and radish seeds based on NIR spectra of single seeds. Journal of Near Infrared Spectroscopy, N. Shetty, M. H. Olesen, R. Gislum, L. C. Deleuran and B. Boelt (2011). Use of PLS-DA on VIS-NIR multispectral image data to examine germination ability and speed in spinach seeds. Journal of Chemometrics. Accepted L.C. Deleuran, M.H. Olesen, N. Shetty, R. Gislum and B.Boelt (2011). Importance of seed Quality for the freshcut chain. Acta Horticulturae. Accepted 20
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