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Raw materials, technological processes, intermediers and by-products of sugar industry have been characterized by near infrared (NIR) spectroscopy.Various sample preparation and spectroscopic methods were compared in order to optimize the measurement conditions of different types of samples. Sugar beet quality parameters were investigated in raw and deep frozen brei form and it was concluded that dry matter and sugar content of samples can be detected with good accuracy (SD = 0.3 -0.4%) using standard thawing method and special sample holder. Inspite of big sample set (N = 200) with broad variation in alpha-amino nitrogen it was not found acceptable correlation between spectroscopic data and alpha-amino nitrogen content of sugar beet. Raw and purified (filtered, saturated) thin and thick juices and diluted massecuites were investigated using transmission method respectively. Brix value (dry matter) and sugar content, as well as colour of juices were measured with acceptable accuracy but the calibration of purity value showed high standard error. Selected and combined calibrations were developed for six different technological intermediers in three different factories. Chemical composition of molasses (Brix, sugar content, purity) were also measued by NIR using an optimalized sample preparation method. It was concluded that some of the conventional analysis methods (ICUMSA) can be substituted with NIR measurements where a significant reduction was observed in dangerous reagents (lead acetate) and labour-costs.

The goal of this research was to investigate the effect of electrical conductivity (EC) levels of the nutrient solution on the fresh weight, chlorophyll, and nitrate content of hydroponic-system-grown lettuce. The selected cultivars are the most representative commercial varieties grown for European markets. Seven cultivars (‘Sintia,’ ‘Limeira,’ ‘Corentine,’ ‘Cencibel,’ ‘Kiber,’ ‘Attiraï,’ and ‘Rouxaï’) of three Lactuca sativa L. types’ (butterhead, loose leaf, and oak leaf) were grown in a phytotron in rockwool, meanwhile the EC level of the nutrient solutions were different: normal (<1.3 dS/m) and high (10 dS/m). The plants in the saline condition had a lower yield but elevated chlorophyll content and nitrate level, although the ‘Limeira’ and ‘Cencibel’ cultivars had reduced nitrate levels. The results and the special characteristic of the lollo-type cultivars showed that the nitrate level could be very different due to salinity (‘Limeira’ had the lowest (684 µg/g fresh weight (FW)) and ‘Cencibel’ had the highest (4396 µg/g FW)). There was a moderately strong negative correlation (−0.542) in the reverse ratio among the chlorophyll and nitrate contents in plants treated with a normal EC value, while this relationship was not shown in the saline condition. Under the saline condition, cultivars acted differently, and all examined cultivars stayed under the permitted total nitrate level (5000 µg/g FW).

According to the Commission Regulation (EC) No. 1258/2011, the maximum allowed nitrate content of lettuce is defined within a broad range (2000–5000 mg NO3/kg), depending on harvest season and technology. This study focuses on the identification of the differences in nitrate accumulation between lettuce types and varieties, depending on production technology and on the investigation of the application of non-destructive FT-NIR spectroscopy for nitrate quantification, towards widely used UV–Vis spectroscopy. In the present study, combinations of seasons and technologies (spring × greenhouse, autumn × open field) were employed for the production of types (batavia, butterhead, lollo and oak leaf; both red and green colored); a total of 266 lettuce heads were analyzed. It was found that with standardized technology and conditions, autumn harvested green oak leaf lettuce types accumulated significantly less nitrate, than red oak or lollo leaf types. With spring harvested lettuces, batavia types generally accumulated generally more nitrates than butterhead types. Based on the linear discriminant analysis (LDA) of FT-NIR measurements the four distinct variety types diverge; the lollo type explicitly diverges from batavia and butterhead types. The LDA further revealed, that within lollo and oak leaf variety types, red and green leaved varieties diverge as well. A model was successfully built for the FT-NIR quantification of the nitrate content of lettuce samples (R2 = 0.95; RMSEE = 74.4 mg/kg fresh weight; Q2 = 0.90; RMSECV = 99.4 mg/kg fresh weight). The developed model is capable of the execution of a fast and non-invasive measurement; the method is suitable for the routine measurement of nitrate content in lettuce.

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The effect of an attribute is evaluated without changing other factors. The other type is when the effect of the interactions of different treatments is analysed. In some cases, it would be necessary to use new approaches. How can we evaluate cultivars, methods, proceedings, treatments, etc. meanwhile using all parameters at the same time? Sum of Ranking Differences (SRD) is an alternative statistical method, implemented by Héberger (2010). Validation and the software implementation was done by Héberger and Kollár-Hunek (2011). Cultivars, methods, procedures, treatments, etc. can be compared successfully with SRD-method. Several international publications proved the relevancy of the methodology. In this study, SRD-method is introduced, as well as those researches, which conducted in horticultural and food sciences. Based on these, new fields of application are suggested.

There is a great supply of leafy vegetables on the market; hence capturing consumer’s attention (and decision) is critically important. Several scientific publications deal with consumer choices and the newest technology to capture consumer attention is eye-tracking. Eye-trackers are commonly used in Western Europe and Asia also, where it is an important and widely-used tool during product developments and the creation of marketing strategies. In Hungary, there are only a few publications about eye-tracking applications in vegetable growing and food industry. In our research, photographs about sorrel, lamb lettuce, spinach, leaf lettuce and dandelion leafs were analysed by eye-tracking technology and the eye movements of the participants during their decision making process of leafy vegetables were captured and evaluated. The eye-tracking analyses were carried out in the Sensory Laboratory of the Faculty of Food Sciences of Szent István University, using a Tobii X2-60 eye-tracker and Tobii Studio (version 3.0.5, Tobii Technology AB, Sweden) software. We aimed to answer the following research questions: Are there any connections between the eye movements of participants and their decisions? What amount of visual attention can be registered during the decision making process? Furthermore, the following metrics were measured and evaluated: fixation durations on the leafy vegetables, number of returns to products, pathways of visual attention, time until the final decision making and motivation of their final decisions. Measurement of the subconscious consumer decision making processes is way easier using eye-trackers compared to the traditional questionnaire-based methods, because it is hard or impossible to control our eye movements. Eye-tracking can be used successfully for understanding the expectations and decisions of the consumers.