Roasting can potentially affect the functional properties of the resulting coffee. For instance, antioxidant phenolic chlorogenic acids (CGA) are known to be thermally labile. In this study, we develop a new NIR spectroscopic method to measure CGA concentration found in the coffee beans. High performance liquid chromatography (HPLC) was used to determine standard reference values of CGA concentration. A partial least squares regression (PLSR) with full cross-validation method was employed for the development and the validation of the regression model. The resultant model accuracy of R_CV² = 0.76 and RMSECV = 1.16% with preprocessing of the spectra by MSC and SNV is thought to be accurate enough for the rapid and non-destructive determination of CGA concentration in roasted coffee beans.

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The objective of this study was to develop a crawler-type tractor that can be navigated autonomously in an open sky field using an RTK-GPS receiver and an IMU. A laser scanner and an emergency stop system were utilized for safety. The hydro static transmission (HST) system for steering and shift was calibrated in this study. An autonomous navigation control method is described in this article. A keyhole turning algorithm was used for headland turning. Autonomous navigation tests were carried out in an open sky field, and the RMS of lateral error in the navigation tests was less than 0.05 m in straight lines.

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The influence of sample temperature variation on L-AA determination using Fourier transform infrared attenuated total reflectance terahertz (FTIR-ATR-THz) spectroscopy was investigated. Using the best local calibration models at 22, 31 and 40 °C, prediction results for a prediction sample set at any one temperature were excellent, with low RMSEP and high SDR_pred values. However, bias and SEP were significantly increased when samples from different temperatures were used in these models; higher RMSEPs resulted. On the other hand, global calibration models based on combinations of different temperatures gave better prediction results, with lower RMSEP and higher SDR_pred values for all prediction samples at 22, 31 and 40 °C. With these global calibration models the bias predictions were also significantly decreased; resulting in lower RMSEP values.

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The main purpose of this study is to apply non-parametric method of data envelopment analysis (DEA) for optimization of energy inputs and reduction of greenhouse gas (GHG) emission for rice production in Guilan province of Iran. For these aims, 120 rice producers were selected for data collection in Astaneh Ashrafiyeh city of Guilan province. In this paper, seven energy inputs and rice yield as output were considered for DEA method. The technical, pure technical and scale efficiency were determined based on Charnes-Cooper-Rhodes (CCR) and Banker-Charnes-Cooper (BCC) models. The average of technical, pure technical and scale efficiency were calculated as 0.79, 0.98 and 0.81, respectively. The results revealed 35 (29.17% of total units) and 72 (60% of total units) rice producers were efficient in technical and pure technical efficiency, respectively. The total energy saving was estimated about 19.80%. Also, the highest share of contribution to the total savings energy was calculated as 43.41% for diesel fuel. The energy use efficiency was improved about 25% by converting present farms to target units. Furthermore, the GHG emission of each input was investigated for present and optimum units. The results indicated that the total GHG emission of present and optimum farms was calculated as 1847.26 and 1483.52 kgCO_2eq. ha⁻¹, respectively. Moreover, the effect of energy optimization in reduction of GHG emission was found to be as 363.74 kgCO_2eq. ha⁻¹. With respect to DEA method, the diesel fuel consumption of efficient units had the highest effect to helping for GHG reduction.

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Mycotoxin contamination in edible oil has been a serious problem in recent years. The feasibility of ATR- FTIR spectroscopy with Principal Component Analysis (PCA) was investigated for detecting 15-AcDON in crude and refined corn oils. Corn oils contaminated artificially with 15-acetyldeoxynivalenol (15-AcDON) and Fusarium asiaticum (defined as “Fusarium-contaminated corn oil”) and only with 15-AcDON (defined as “Fusarium-free corn oil”) were tested to simulate 15-AcDON contamination in crude oil and in refined oil, respectively. The contaminations with 15-AcDON at different levels were discriminated by a PCA score plot for both contaminated corn oils. The specific IR bands of 15-AcDON were revealed for each oil, which could be assigned to the symmetric stretching vibration of the ester (O)CeO. By comparison between the spectra of both oils, no interference of the F. asiaticum in the detection of 15-AcDON was found, however, the difference of the specific band region for 15-AcDON between both oils was observed. The results suggested that ATR-FTIR spectroscopy could be a promising method for rapid screening of 15- AcDON in crude and refined corn oils.

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This paper presents thin layer drying characteristics of hybrid rice seed and quality of the dried rice seed in terms of germination capacity and colour. Thin layer drying of hybrid rice seed was conducted at the temperature levels of 40 °C, 50 °C and 60 °C, relative humidity ranging 10 to 15% and air velocity ranging 0.55 to 0.65 m/s. Drying rate increases with the increase in drying air temperature and the drying air temperature has a significant effect on the seed quality. Five thin-layer drying models were fitted to the experimental data of thin layer drying of hybrid rice seed. Midilli equation was found to be the best followed by two term exponential equation, Page equation, Henderson and Pabis equation and Newton model. The agreement between the predicted and experimental results was excellent. Germination capacity was the highest for the drying air temperature of 40 °C and then it decreased significantly with the increase of drying air temperature above 40 °C. Colour of the hybrid rice seed did not change with the increase of drying temperature. Lightness, hue angle and chroma were found to be almost same for these three drying air temperatures. It is recommended that hybrid rice seed should not be dried above 40 °C.

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