Assessing the climate adaptive potential of imported Chili in comparison with local cultivars through germination performance analysis.

BACKGROUND: The study offers insightful information about the adaptability of local and imported Chili cultivars. This experiment examines how three different chili cultivars Tanjung, Unpad, and Osaka perform in the germination and early growth phases while considering a wide range of environmental conditions. Research conducted in Jatinangor, Sumedang Regency, Indonesia, highlights the differences between cultivars and the varied possibilities for adaptability each variation possesses. RESULTS: Among them, Tanjung stands out as the most promising cultivar; its robust performance is demonstrated by its high germination index 91.7. Notable features of Osaka include the highest biomass output (1.429 g), the best water usage efficiency (WUE) at 0.015 g/liter, and the best distribution uniformity (91.2%) and application efficiency (73.6%) under different irrigation conditions. Tanjung's competitiveness is further evidenced by the fact that it trails Osaka closely on several metrics. Lower performance across criteria for Unpad suggests possible issues with flexibility. CONCLUSION: The value of this information becomes apparent when it comes to well-informed breeding programs and cultivation techniques, especially considering uncertain climate patterns and global climate change. This research contributes significantly to the body of knowledge, enabling well-informed choices for environmentally dynamic, sustainable chili farming.

Antioxidative response of parthenocarpic tomato, iaa9-3 and iaa9-5, under heat stress condition.

It has previously been shown that parthenocarpic tomato mutants, iaa9-3 and iaa9-5, can adapt, grow, and produce fruit under heat-stress conditions. However, the physiological processes in those two mutants especially for the enzymatic system that works to neutralize ROS are not clear. The objective of this research was to determine how the scavenging enzyme system responds to the heat stress in those mutants. The iaa9-3, iaa9-5, and WT-MT as a control were cultivated under two environmental conditions; normal and heat stress conditions. Vegetative and reproductive growth were observed during cultivation period. The activities of catalase (CAT), ascorbate peroxidase (APX) and superoxide dismutase (SOD) were investigated in both wild-type and parthenocarpic tomato mutants under normal and heat stress conditions. The results showed that under heat stress condition, the mutants, iaa9-3 and iaa9-5, and WT-MT resulted in reduction of the vegetative growth, but those mutants showed better growth than WT-MT. Higher chlorophyll content in iaa9-3 and iaa9-5 was observed under normal or heat stress condition. Despite their growth reduction under heat stress conditions, iaa9-3 and iaa9-5 resulted in the significant higher CAT, APX and SOD activity than WT-MT. The results suggest that higher chlorophyll content and enhanced CAT, APX and SOD activity in the iaa9-3 and iaa9-5 mutants are adaptive strategies to survive in heat stress conditions.

Comparison of color spectrophotometer and Vis/NIR spectroscopy on assessing natural pigments of cucumber applied with different ethephon concentrations.

In recent decades, the development of non-destructive measurement methods for agricultural commodities has gained a lot of attention among scientists, but these techniques have different levels of accuracy for each instrument used. Therefore, this study aimed to compare the prediction accuracy of natural pigments, such as Total Carotenoid Content (TCC) and Total Flavonoid Content (TFC) using a color spectrophotometer and Visible/Near-Infrared (Vis/NIR) spectroscopy (381-1065 nm). The effect of ethephon concentration on the spectral characteristics and the accuracy of predicting pigments was studied. The samples used include cucumber fruit, which consisted of the 'Mars', 'Vanesa', and 'Roberto' varieties. During the planting of the fruit, ethephon was applied at different concentrations of 0 ppm, 150 ppm, and 300 ppm. The results showed that the best accuracy for predicting TCC was obtained through a color spectrophotometer (Rcal = 0.89, Rpred = 0.90, RPD = 2.44), while the best prediction for TFC was the Vis/NIR spectroscopy (Rcal = 0.86, Rpred = 0.83, RPD = 1.78). Furthermore, the ethephon affects the spectral characteristics of cucumber fruit. Ethephon concentration of 150 ppm produced the highest accuracy value compared to others. This study proved that the use of non-destructive measurement methods with a color spectrophotometer and Vis/NIR spectroscopy has good performance in predicting TCC and TFC. The techniques are also easy to use, do not require chemicals, and have high accuracy.

Simple analytical method using ultraviolet spectral dataset and chemometrics for the authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications.

The possible application of a simple analytical method based on a UV (ultraviolet) spectral dataset coupled with SIMCA (soft independent modeling of class analogy) for authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications (GIs) was demonstrated. Three types of Indonesian specialty ground roasted coffee were used: GIs arabica coffee from Gayo Aceh (96 samples), GIs liberica coffee from Meranti-Riau (119 samples), and GIs robusta coffee from Lampung (150 samples) with 1 g weight of each sample. All samples were extracted using hot distilled water and 3 mL aqueous filtered samples were pipetted into a 10 mm quartz cell. Original UV spectral datasets were recorded in the range of 190-399 nm. The pre-processed spectral dataset was generated using three simultaneous different preprocessing techniques: moving average smoothing with 11 segments, standard normal variate (SNV), and Savitzky-Golay (SG) first derivative with window size and polynomial order value of 11 and 2. The supervised classification based on the SIMCA method was applied for preprocessed selected spectral data (250-399 nm). The PCA data showed that GIs coffee with different botanical and geographical indications can be well separated. The SIMCA classification was accepted with 100 % of correct classification (100 % CC). This dataset demonstrated the potential use of UV spectroscopy with chemometrics to perform simple and affordable authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications (GIs).

Non-Targeted Detection and Quantification of Food Adulteration of High-Quality Stingless Bee Honey (SBH) via a Portable LED-Based Fluorescence Spectroscopy.

Stingless bee honey (SBH) is rich in phenolic compounds and available in limited quantities. Authentication of SBH is important to protect SBH from adulteration and retain the reputation and sustainability of SBH production. In this research, we use portable LED-based fluorescence spectroscopy to generate and measure the fluorescence intensity of pure SBH and adulterated samples. The spectrometer is equipped with four UV-LED lamps (peaking at 365 nm) as an excitation source. Heterotrigona itama, a popular SBH, was used as a sample. 100 samples of pure SBH and 240 samples of adulterated SBH (levels of adulteration ranging from 10 to 60%) were prepared. Fluorescence spectral acquisition was measured for both the pure and adulterated SBH samples. Principal component analysis (PCA) demonstrated that a clear separation between the pure and adulterated SBH samples could be established from the first two principal components (PCs). A supervised classification based on soft independent modeling of class analogy (SIMCA) achieved an excellent classification result with 100% accuracy, sensitivity, specificity, and precision. Principal component regression (PCR) was superior to partial least squares regression (PLSR) and multiple linear regression (MLR) methods, with a coefficient of determination in prediction (R2p) = 0.9627, root mean squared error of prediction (RMSEP) = 4.1579%, ratio prediction to deviation (RPD) = 5.36, and range error ratio (RER) = 14.81. The LOD and LOQ obtained were higher compared to several previous studies. However, most predicted samples were very close to the regression line, which indicates that the developed PLSR, PCR, and MLR models could be used to detect HFCS adulteration of pure SBH samples. These results showed the proposed portable LED-based fluorescence spectroscopy has a high potential to detect and quantify food adulteration in SBH, with the additional advantages of being an accurate, affordable, and fast measurement with minimum sample preparation.

The Authentication of Gayo Arabica Green Coffee Beans with Different Cherry Processing Methods Using Portable LED-Based Fluorescence Spectroscopy and Chemometrics Analysis.

Aceh is an important region for the production of high-quality Gayo arabica coffee in Indonesia. In this area, several coffee cherry processing methods are well implemented including the honey process (HP), wine process (WP), and natural process (NP). The most significant difference between the three coffee cherry processing methods is the fermentation process: HP is a process of pulped coffee bean fermentation, WP is coffee cherry fermentation, and NP is no fermentation. It is well known that the WP green coffee beans are better in quality and are sold at higher prices compared with the HP and NP green coffee beans. In this present study, we evaluated the utilization of fluorescence information to discriminate Gayo arabica green coffee beans from different cherry processing methods using portable fluorescence spectroscopy and chemometrics analysis. A total of 300 samples were used (n = 100 for HP, WP, and NP, respectively). Each sample consisted of three selected non-defective green coffee beans. Fluorescence spectral data from 348.5 nm to 866.5 nm were obtained by exciting the intact green coffee beans using a portable spectrometer equipped with four 365 nm LED lamps. The result showed that the fermented green coffee beans (HP and WP) were closely mapped and mostly clustered on the left side of PC1, with negative scores. The non-fermented (NP) green coffee beans were clustered mostly on the right of PC1 with positive scores. The results of the classification using partial least squares-discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and principal component analysis-linear discriminant analysis (PCA-LDA) are acceptable, with an accuracy of more than 80% reported. The highest accuracy of prediction of 96.67% was obtained by using the PCA-LDA model. Our recent results show the potential application of portable fluorescence spectroscopy using LED lamps to classify and authenticate the Gayo arabica green coffee beans according to their different cherry processing methods. This innovative method is more affordable and could be easy to implement (in terms of both affordability and practicability) in the coffee industry in Indonesia.

The Role of Moringa Leaf Extract as a Plant Biostimulant in Improving the Quality of Agricultural Products.

Ensuring high-quality agricultural products has become important in agriculture since society's standard of living has risen. Meanwhile, Moringa oleifera L. leaf extract (MLE) has been used as a plant biostimulant to improve product quality. The effectiveness of MLE is associated with its beneficial components, consisting of nutrients, phytohormones, secondary metabolites, amino acids, and bioactive compounds. Previous studies have been carried out to find the effects of MLE application on the quality of different crops, including basil, kale, spinach, maize, radish, brinjal, pepper, tomato, grape, strawberry, and more. The results are generally positive concerning physical, nutritional, and chemical qualities. This review comprises recent findings regarding MLE application as a plant biostimulant to increase quality attributes, with its underlying mechanism.

Enhanced visible/near-infrared spectroscopic data for prediction of quality attributes in Cucurbitaceae commodities.

Spectra data of 300 samples from 6 Cucurbitaceae commodities, including zucchini, bitter gourd, ridge gourd, melon, chayote, and cucumber, were recorded using a handheld visible/near-infrared (Vis/NIR) instrument. Vis/NIR data were obtained in the form of absorbance spectra data at a wavelength of 381-1065 nm. The spectral data has the potential to be reused to predict quality attributes in the form of soluble solids and water content on several Cucurbitaceae commodities. The accuracy of the Vis/NIR calibration model can be increased by applying spectra preprocessing, for example, second derivative savitzky-golay (dg2). The calibration model was developed using the principal component regression (PCR) method on RAW and dg2 spectra. The enhanced Vis/NIR dataset can be used to evaluate the inner quality attributes of intact fruits in a rapid, non-destructive manner.