Nutrition and end-use quality - Promising tool for high-throughput phynotyping application of optical measurement
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Nutrition and end-use quality - Promising tool for high-throughput phynotyping application of optical measurement
- 1. Nutritional and end-use quality Haruki Ishikawa Plant physiologist Promising tool for high-throughput phynotyping Application of optical measurement
- 2. Key factors of phenotyping -Breeders interest: Yield, tolerance, resistance, architecture, physiology, ecology etc… -Direct measurement parameters: Yield, image-based projected leaf area, chlorophyll fluorescence, stem diameter, plant height/width, compactness, stress pigment concentration, tip burn, internode length, color, leaf angle, leaf rolling, leaf elongation, seed number, seed size, tiller number, flowering time, germination time etc…
- 3. High-throughput -What is “high-throughput”? e.g. a performance per unit time = it can measure 100 plants per day -Limitation of labor intensive method Touch-counting system for efficient counting Grain size and color measurement system For evaluation of Striga seed germination in Nematoglogy ICRISAT HQ, FieldScan (precision screening of tens of thousands of plants under filed conditions): phynospex.
- 4. High throughput phenotyping with Spectroscopy -Fourier Transform Infra-Red (FT-IR) Spectroscopy FT-IR is a method of measuring an infrared absorption spectrum -What we can do We can : Qualitative analysis for find particular components in sample, identification of chemical substances, residual pesticides…etc. Quantitative analysis for protein contents, sugar or starch contents, water contents, particular components…etc. FT-IR system (JASCO) “The sugar content automatic measurement system for apple” -Rapid -Low-cost -Labor- effective -Repeatable
- 5. Current study -Nitrogen content in the cowpea seed- 1. Sample preparation Breeders field: varieties, growth condition, number of sample…etc. Lab: sample preparation (depend on method of measurement) 2. Establishment of calibration curve/model True value (ref. from chemical analysis) and Spectra data require 3. Validation of calibration curve ↓ 4. Quantitative analysis for interest samples Chemometrics technique
- 6. Current study -Nitrogen content in the cowpea seed- 18 J Biol Food Sci Res Table 1: Characteristics of locations used for sample generation in 2011 and 2012. Field Country AEZs* Latitude Longitude Type of field Fertilizer rate Ibadan Nigeria Forest savanna transition 7°29’292"N 3°54’690"E Experimental Low: 0kg/ha High: 40kg/ha Minjibir Nigeria Sudan savanna 12°08'448"N 8°40'069"E Experimental Low: 40kg/ha High: 100kg/ha Toumnia Niger Sahel 13°58’747”N 9°01’698”E Farmer Low: 40kg/ha High: 100kg/ha *AEZs: Agro-ecological zones. 251 germplasms * 3 different locations * 2 fertilizer conditions * 2 years = 3012 samples Source: S. Muranaka, M. Shono, M. Kumar, H. Takagi, H. Ishikawa (2015) J. Biological Food Science Research. 4(2), pp16-24. Spectra data acquisition ↓ Chemometrics analysis ↓ Calibration curve model ↓ Validation
- 7. Region: MIR Sample condition: powder Acquisition time: 2min/sample Throughput: 150 samples/day Current study -Nitrogen content in the cowpea seed- Source: S. Muranaka, M. Shono, M. Kumar, H. Takagi, H. Ishikawa (2015) J. Biological Food Science Research. 4(2), pp16-24. J Biol Food Sci Res Figure 3. Validation of the MIRS calibration model for the N content of grain samples collected from Ibadan, Minjibir, and Toumnia, in different agro-ecological zones (total n = 636). calibration models for crude protein contents in s pulses (e.g. broad bean, faba bean, chickpea, that we used for the experiment cannot represent all possible variations, the results showed that the MIRS With cost and time saving characteristics of the method, these accurate and robust calibration models for predicting grain N contents should be useful tools for field agronomic studies and breeding in cowpea.
- 8. Region: NIR Sample condition: Whole seed Acquisition time: 17 sec/sample Throughput: 750 samples/day Current study -Nitrogen content in the cowpea seed- Non-destructive whole seed measurement Establishment of the model in progress
- 9. FTIR -apply for other crops- e.g. Yam or cassava (starch, water content) Collaboration work with JIRCAS ■特 長 ・携帯型手持式ソリューション ・安全な近赤外光使用 ・簡単なポイント&シュート操作 ・専門性を必要としない最小限のトレーニング ・非破壊測定法による定性分析、定量分析が可能 ・豊富な内蔵検量線 ・すべてのデータはメモリに保管され、 ログとしてPC にダウンロード可能 ・迅速な同定のためのカラー液晶画面 ・バッテリーは 5 時間を以上の連続使用が可能 ・充電式リチウムイオン電池 ・わずか数秒の即時分析 ハンディNIR装置microPHAZIR-ＡＧ 時代はデジタル分光へ・・・・ ◆MEMS技術と先進信号変換技術の融合により生まれたデジタル分光装置の登場です ◆ベンチトップNIRの性能が、片手で持ちはこび可能になりました ◆超小型高性能分光機で高品質なデータで家畜飼料、農産物の品質管理が可能です microPhazirAGTM はラボ用近赤外分光装置の性能を、「現場」へ持ちだして使用できるように開発されたハンド ヘルドNIR装置です。その心臓部にはDTS技術（Digital Transform Spectroscopy）に基づき開発された超小型N IR分光システムが組み込まれております。 microPhazirAGTM では、小型ハンディながらベンチトップタイプと同等の高品質スペクトルの取得が可能で、判 別分析の他に定性・定量分析も可能です。特に品質管理現場での各種検査分析に適合いたします。 納入業者による 出荷評価 受入れ検査 工程管理 最終出荷 事前検査 アプリケーション 飼料/農産物の各種品質検査に最適 品 名 農業用ハンディ近赤外（NIR）分光装置 型 式 マイクロフェイザーAG（microPHAZIR-AG） 外形寸法 266×251×110㎜ 重 量 約1.8㎏ 動作原理 近赤外分光法による非破壊分析 分光器 MEMSミラー採用による無調整型 スペクトルレンジ 1600～2400nm 波長分解能 12nm 測定法 拡散反射法 測定時間 3～60秒 測定モード 定量分析 結果表示 カラー液晶スクリーン データダウンロード USBケーブルでPCデーター通信 使用温度範囲 5～50℃ 電源 （バッテリー） 充電可能なリチウムイオン電池 ■一般仕様 ■測定例 Handy FTIR (NIR) microPhazirTM AG Accuracy Establish robust calibration model with various samples & Cost performance Does it balance with the data needed? NIR gun Analysis for sugar content
- 11. Focus on different region of IR Middle Infra-red Region (MIR) Near Infra-red Region (NIR) 25μm~2.5μm (400~4000cm1) 2.5μm~1.0μm (4000~10000cm1) Quantitative/Qualitative analysis Hydroscopic compound → inadequacy Hydroscopic compound → adequacy Quantitative/non-destructive analysis
Editor's Notes
- Good afternoon. I am Haruki Ishikawa. I am honor to have the opportunity to talk today. I will show you a phenotyping example, especially nutritional and end-use quality topic.
- Plant phenotyping is the comprehensive assessment of complex plant traits such as growth, development, tolerance, resistance, architecture, physiology, ecology, yield, and the basic measurement of individual quantitative parameters that form the basis for the more complex traits. Examples for such direct measurement parameters are ***. These phenotyping parameters were mostly based on experience and intuition, in a process where measurement and interpretation were not separated. As you know, there are various phenotyping methods and these are characteristically designed in each traits and/or interest.
- Modern techniques for crop improvement rely on both DNA sequencing and accurate quantification of plant traits to identify genes and germplasm of interest. With rapid advances in DNA sequencing technologies, plant phenotyping is now a bottleneck in advancing crop yields. Therefore, high-throughput phenotyping is demanded. ‘High-throughput' is a classification that is relative to the effort associated with the measurement. Throughput is defined a performance per unit time. So, here high-throughput phenotyping is defined as technology that can measure minimally hundreds of plants per day. Then, at the field, the measurement based on experience and intuition has limitation. An optical measurement technique is a key technology for the high-throughput phenotyping. A population on the order of hundreds allows for analysis of mutant populations, detection of QTLs, and discovery of gene by environment associations. Planteye, its 3D leaser scanning system can scan 5000 plants per hr. Leaf size, leaf angle, number of leaf, highest and various parameter you can choice.
- Other optical measurement technique, especially imaging techniques already introduced by Isamal, Sato, and Ryo. Also, Bussie already mentioned about nutritional study. So, here, I will show you a example of nutritional phenotyping with spectroscopy. Fourier transform infra-red spectroscopy, so called FTIR, is a method of measuring an infrared absorption or transmission spectrum. As you know, this technique use a optics. Therefore, the measurement is rapid, low-cost, labor-effective and repeatable. And, what we can do
- Lets see the case study, I will show you our current study. We tried to determine Nitrogen content in the cowpea seed using by FTIR. The methodology of this study is same as quantitative spectrographic analysis. Sample preparation, Establishment of calibration curve, and its validation. After those, we can begin quantitative analysis. The most important step is establishment of calibration model and its validation. Because, the density of compound of the crop sample is unknown, it differ from the general quantitative analysis. Therefore, chemometrics technique is required, and gather as much sample as possible with different condition.
- As you know well, the applicability and accuracy of calibration depend on the population used in calibration model development. Genetic variation in the chemical composition of samples greatly influences the accuracy of the models developed, depending on the type of sample, and target traits. Also, environmental factors such as growing location, weather conditions, and soil fertility may affect the chemical composition of samples and decrease the accuracy of the calibrations. To this purpose, we prepared 251 germplasm * 3 locations * 2 fertilizer conditions * 2 years = 3012 samples. And the nitrogen content of these samples determined using by NC analyzer. We generated 925 data set for calibration model. Then, spectra data acquisition performed by FTIR and its analysis, model development and validation were done.
- In the results, obtained MIRS calibration model showed a reasonable balance between accuracy and applicability in predicting the N contents of grain samples collected from different agro-ecological zones of West Africa. Our findings also suggest that MIR information may be useful in increasing the robustness of calibration models for quantitative analysis regardless of the environmental effects. After the model development, we can use this for further N content analysis in the cowpea seed. When you bring your interest seed, we can provide you the nitrogen content in the seed within 2min. Of course, it is depend on the technician, but also we can predict, according to data acquisition time, we can handle 150 samples per day.
- Lets see further application of FTIR. A key advance in high throughput phenotyping is the capability to non-destructively capture plant traits. In the nutritional study, if the seed screening possible with non-destructive FTIR, breeder can plant the seed after analysis. Now, establishment of the calibration model with non-destructive technique is in progress.
- I wish this presentation could contribute further discussion of phenotyping. Thank you for your attention.
- I would like to omit details, but just right to the point. In the optics, light is not only visible region and its also means electromagnetic radiation. The electromagnetic spectrum is the range of all possible frequencies of electromagnetic radiation. The "electromagnetic spectrum" of an object has a different meaning, and is instead the characteristic distribution of electromagnetic radiation emitted or absorbed by that particular object. Infra-red spectroscopy handles the optical radiation of the region of IR. There are 3 regions in the IR region. Especially, FTIR use middle and near infrared regions. The characteristic of each region are listed here. Most important thing is here. MIR is suitable for the sample without water such as powder or after freeze dry, and high resolution characteristic analysis. NIR is suitable for the non-destructive analysis such as whole crop.