品质检测仪F-751是基于F-750基础上进行开发的针对猕猴桃、芒果、牛油果和甜瓜的品质快速无损评判的便携式仪器。它准确、无损快速测量果实的干物质量或糖度，从而评价果实的成熟度。
NIR（近红外测定）技术在成套设备中的应用可为我们提供客观量化的质量标准，已在生产中应用多年。我们的便携式设备把近红外分析技术带给田间种植者为作物收割前提供更好、更一致的成熟度的评估和测定。F-751已经开始在世界各地的大学、科研机构和种植商使用。
主要功能：
1、精确的测量干物质量或糖度（芒果、牛油果、猕猴桃和甜瓜）
2、快速测量（4～6秒）
3、非破坏测量
4、带全球定位系统，便于制作数据地图
5、野外可视半透显示屏
6、可更换/充电电池
7、SD卡数据存储
8、无需创建模型
9、收获前成熟度评估
10、采后品质检验
测量参数：
测量原始数据、反射率、吸光度、一阶导数、二阶导数、计算糖度或干物质并获取GPS信息
应用领域：
主要应用于果实成熟度和甜度相关参数的无损评估，包括田间作物管理和收获期评估、果实储藏、果实催熟及果实零售的各个环节。
主要技术参数：
1、光谱仪：滨松C11708MA
2、光谱范围：640-1050 nm
3、光谱样点大小: 2.3nm
4、光谱分辨率：最大20 nm（半峰全宽）
5、光源：卤素钨灯
6、镜头：镀膜增益近红外线镜头
7、快门：白色参考标准
8、显示器：带背光阳光可见透反液晶屏
9、操作环境：0-50ºC，0-90%（非结露）
10、数据连接：WiFi
11、记录的数据：原始数据、反射率、吸光度、一阶导数、二阶导数、GPS信息、日期和时间
12、测量：干物质量&糖度（ºBrix）
13、供电：可拆卸3400Ah锂电池
14、续航时间：大于500次测量
15、数据存储：可拆卸32GB SD卡
16、外壳：粉末喷涂铝合金型材
17、尺寸：18×12×4.5cm
18、重量：1.05 kg
选购指南：
主机、操作手册、叶夹 、箱子和相关配件
基本配置：
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参考文献：
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. Núñez-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).
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5. A. Zeb et al., Towards sweetness classification of orange cultivars 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).
7. M. Wohlers, A. McGlone, E. Frank, G. Holmes, Augmenting NIR Spectra in deep regression to improve calibration. Chemometrics and Intelligent Laboratory Systems 240, 104924 (2023).
8. C. B. S. Tong, M. Gullickson, M. Rogers, E. Burkness, W. D. Hutchison, Detection of Spotted-winged Drosophila (Diptera: Drosophilidae) Infestations in Blueberry Fruits1. Journal of Entomological Science 58, 370-374 (2023).
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 cultivar models allow for accurate peach fruit quality and maturity assessment following customization in phenotypically similar cultivars. Postharvest Biology and Technology 195, 112148 (2023).
产地：美国Felix
