品質檢測儀F-750是一款用于分析與農產品品質密切相關的內部及外部特性的測量儀器。
NIR（近紅外測定）技術在成套設備中的應用可為我們提供客觀量化的質量標準，已在生產中應用多年。我們設備把近紅外分析技術帶給田間種植者為作物收割前提供更好、更一致的成熟度的評估和測定。
F-750使用近紅外（NIR）光譜技術無損的評估品質指標，如干物質、總可溶性固體（TSS或白利糖度）。F-750具有廣泛的應用從確定收獲時間到在包裝廠和進口時對水果的品質進行客觀分析。
主要功能：
1、針對農產品的品質進行檢測
2、快速測量（4～6秒）
3、非破壞測量
4、定位系統，便于制作數據地圖
5、可更換/充電電池
6、SD卡數據存儲
7、可創建特殊品種的模型
8、收獲前成熟度評估
9、采后質量檢驗
測量參數：
可測量可溶性固形物（糖度或百利糖）、干物質、內部顏色等參數
應用領域：
主要應用于果實成熟度和甜度相關參數的無損評估，包括田間作物管理和收獲期評估、果實儲藏、果實催熟及果實零售的各個環節。
主要技術參數：
1、光譜儀：卡爾蔡司MMS-1光譜儀
2、光譜范圍：310-1100 nm
3、光譜樣點大小: 3 nm
4、光譜分辨率：8-13 nm
5、光源：氙氣鎢燈
6、鏡頭：鍍膜增益近紅外線鏡頭
7、快門：白色涂漆參考標準
8、顯示器：陽光可見透反液晶屏
9、數據傳輸：USB和WIFi
10、光譜數據輸出選項：反射率，吸收率，一階導數，二階導數
11、操作環境：0-50oC, 0-90% （非結露）
12、測量：吸光度、二階導數吸光度
13、供電：可拆卸3100毫安時鋰離子電池
14、續航時間：大于1600次
15、數據存儲：可拆卸32GB SD卡
16、外殼：粉末噴涂鋁合金型材
17、尺寸：18×12×4.4cm
18、重量：1.05 kg
選購指南：
主機、操作手冊、葉夾 箱子和相關配件
基本配置：
可選附件：
用于測量小型果實，例如：藍莓
參考文獻：
1. D. Valasiadis et al., Wide-characterization of high and low dry matter kiwifruit through spatiotemporal multi-omic approach. Postharvest Biology and Technology 209, 112727 (2024).
2. G. Nú?ez-Lillo et al., A First Omics Data Integration Approach in Hass Avocados to Evaluate Rootstock–Scion Interactions: From Aerial and Root Plant Growth to Fruit Development. Plants 13, 603 (2024).
3. A. Mumford, Z. Abrahamsson, I. Hale, Predicting Soluble Solids Concentration of ‘Geneva 3’ Kiwiberries Using Near Infrared Spectroscopy. HortTechnology 34, 172-180 (2024).
4. B. Giussani, G. Gorla, J. Riu, Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview. Critical Reviews in Analytical Chemistry 54, 11-43 (2024).
5. A. Zeb et al., Towards sweetness classification of orange crs using short-wave NIR spectroscopy. Scientific Reports 13, 325 (2023).
6. Y. Yu, M. Yao, Is this pear sweeter than this apple? A universal SSC model for fruits with similar physicochemical properties. Biosystems Engineering 226, 116-131 (2023).
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9. V. S. Titeli, M. Michailidis, G. Tanou, A. Molassiotis, Physiological and Metabolic Traits Linked to Kiwifruit Quality. Horticulturae 9, 915 (2023).
10. A. Sharma et al., Chemometrics driven portable Vis-SWNIR spectrophotometer for non-destructive quality evaluation of raw tomatoes. Chemometrics and Intelligent Laboratory Systems 242, 105001 (2023).
11. A. Praiphui, K. V. Lopin, F. Kielar, Construction and evaluation of a low cost NIR-spectrometer for the determination of mango quality parameters. Journal of Food Measurement and Characterization 17, 4125-4139 (2023).
12. A. Praiphui, F. Kielar, Comparing the performance of miniaturized near-infrared spectrometers in the evaluation of mango quality. Journal of Food Measurement and Characterization 17, 5886-5902 (2023).
13.C. Lu, H. Xu, B. Lannard, X. Yang, Seasonal Changes in Amylose and Starch Compositions in ‘Ambrosia’ Apples Associated with Rootstocks and Orchard Climatic Conditions. Agronomy 13, 2923 (2023).
14. J. E. Larson, P. Perkins-Veazie, T. M. Kon, Apple Fruitlet Abscission Prediction. II. Characteristics of Fruitlets Predicted to Persist or Abscise by Reflectance Spectroscopy Models. HortScience 58, 1095-1103 (2023).
15. J. E. Larson, T. M. Kon, Apple Fruitlet Abscission Prediction. I. Development and Evaluation of Reflectance Spectroscopy Models. HortScience 58, 1085-1092 (2023).
16. L. Duckena et al., Non-Destructive Quality Evaluation of 80 Tomato Varieties Using Vis-NIR Spectroscopy. Foods 12, 1990 (2023).
17. B. M. Anthony, D. G. Sterle, I. S. Minas, Robust non-destructive individual cr models allow for accurate peach fruit quality and maturity assessment following customization in phenotypically similar crs. Postharvest Biology and Technology 195, 112148 (2023).
產地：美國Felix
