Japanese horseradish (wasabi) grows in very specific conditions, and recent environmental climate changes have damaged wasabi production. In addition, the optimal culture methods are not well known, and it is becoming increasingly difficult for incipient farmers to cultivate it. Chlorophyll a, b and carotenoid contents, as well as their allocation, could be an adequate indicator in evaluating its production and environmental stress; thus, developing an in situ method to monitor photosynthetic pigments based on reflectance could be useful for agricultural management. Besides original reflectance (OR), five pre-processing techniques, namely, first derivative reflectance (FDR), continuum-removed (CR), de-trending (DT), multiplicative scatter correction (MSC), and standard normal variate transformation (SNV), were compared to assess the accuracy of the estimation. Furthermore, five machine learning algorithms—random forest (RF), support vector machine (SVM), kernel-based extreme learning machine (KELM), Cubist, and Stochastic Gradient Boosting (SGB)—were considered. To classify the samples under different pH or sulphur ion concentration conditions, the end of the red edge bands was effective for OR, FDR, DT, MSC, and SNV, while a green-peak band was effective for CR. Overall, KELM and Cubist showed high performance and incorporating pre-processing techniques was effective for obtaining estimated values with high accuracy. The best combinations were found to be DT–KELM for chl a (RPD = 1.511–5.17, RMSE = 1.23–3.62 μg cm⁻²) and chl a:b (RPD = 0.73–3.17, RMSE = 0.13–0.60); CR–KELM for chl b (RPD = 1.92–5.06, RMSE = 0.41–1.03 μg cm⁻²) and chl a:car (RPD = 1.31–3.23, RMSE = 0.26–0.50); SNV–Cubist for car (RPD = 1.63–3.32, RMSE = 0.31–1.89 μg cm⁻²); and DT–Cubist for chl:car (RPD = 1.53–3.96, RMSE = 0.27–0.74).

The growth of tea plants (Camellia sinensis L.) is promoted by the presence of aluminum (Al), a beneficial element under acidic conditions, but the influence of rhizosphere pH on this interaction is not known. To understand the mechanisms underlying the adaptation to acidic rhizosphere conditions, we evaluated ionome profiles and the effect of pH on tea growth in hydroponic culture. The optimum pH for tea growth was around pH 4.2, and growth was inferior under a pH less than 3.8 or higher than 5.0. Under the optimum pH growth and Al accumulation were markedly stimulated by Al treatment. Al content and accumulation in new and mature leaves and new roots (the predominant tissues that accumulate minerals in tea plants) gradually declined with decrease in pH, especially in new roots. Ionome profiles drastically altered Al treatment, but changes were more pronounced in new roots than in new or mature leaves and did not depend on pH. Although the uptake of most cationic minerals in new roots was decreased by Al treatment, cationic mineral contents in new and mature leaves were not decreased by Al. In contrast to other plant species, the content and accumulation of manganese, despite it being a cationic nutrient, were significantly increased by Al treatment. These results indicated that one role of Al as a beneficial element was to maintain the shoot nutrient status by effectively utilizing Al‐limited elements in the roots.

Leaf chlorophyll content is used as a major indicator of plant stress and growth, and hyperspectral remote sensing is frequently used to monitor the chlorophyll content. Hyperspectral reflectance has been used to evaluate vegetation properties such as pigment content, plant structure and physiological features using portable spectroradiometers. However, the prices of these devices have not yet decreased to consumer-affordable levels, which prevents widespread use. In this study, a system based on a cost-effective fingertip-sized spectrometer (Colorcompass-LF, a total price for the proposed solution was approximately 1600 USD) was evaluated for its ability to estimate the chlorophyll contents of radish and wasabi leaves and was compared with the Analytical Spectral Devices FieldSpec4. The chlorophyll contents per leaf area (cm²) of radish were generally higher than those of wasabi and ranged from 42.20 to 94.39 μg/cm² and 11.39 to 40.40 μg/cm² for radish and wasabi, respectively. The chlorophyll content was estimated using regression models based on a one-dimensional convolutional neural network (1D-CNN) that was generated after the original reflectance from the spectrometer measurements was de-noised. The results from an independent validation dataset confirmed the good performance of the Colorcompass-LF after spectral correction using a second-degree polynomial, and very similar estimation accuracies were obtained for the measurements from the FieldSpec4. The coefficients of determination of the regression models based on 1D-CNN were almost same (with R² = 0.94) and the ratios of performance to deviation based on reflectance after spectral correction using a second-degree polynomial for the Colorcompass-LF and the FieldSpec4 were 4.31 and 4.33, respectively.

The amount of chlorophyll in a plant useful to indicate its physiological activity and then changes in chlorophyll content have been used as a good indicator of disease as well as nutritional and environmental stresses on plants. Chlorophyll content estimation is one of the most applications of hyperspectral remote sensing data. The aim of this study is to evaluate dimensionality reduction for estimating chlorophyll contents from hyperspectral reflectance. Random Forest (RF) has been applied to assess biochemical properties such as chlorophyll content from remote sensing data; however, an approach integrating with dimensionality reduction techniques has not been fully evaluated. A total of 200 Zizania latifolia leaves with 5 treatments from Shizuoka University field were measured for reflectance and chlorophyll content. then, the regression models were generated based on RF with three dimensionality reduction methods including principal component analysis, kernel principal component analysis and independent component analysis. This research clarified that PCA is the best method for dimensionality reduction for estimating chlorophyll content in Zizania Latifolia with a RMSE value of 5.65 ± 0.58 μg cm-2.

Background: For papillary thyroid cancer, lymph node excision may be less important for smaller tumors and rather limited node excision might be sufficient to prevent recurrence.Methods: We compared patients who had undergone modified radical neck dissection with patients who had undergone limited node basin excision. Between 1967 and 1996, 4966 patients at our institution had resection of pure papillary carcinoma tumors larger than 11 mm.Results: In patients whose tumors were larger than 25 mm without local adhesion, modified radical neck dissection had a significantly better prognosis compared to that of more limited node excision. For patients with a primary tumor larger than 11 mm, modified radical had a better prognosis than partial node excision only if there was adhesion or invasion to the recurrent nerve, jugular vein, common carotid artery, vagus nerve, or trachea.Conclusion: The size of papillary cancer of the thyroid directly affects prognosis and the role of nodal dissection.