One kind of biologically active salicylic acid (SA) analogue (acetylsalicylic acid, ASA) and two inactive compounds (4-aminosalicylic acid and 4-aminobenzoic acid), along with SA were chosen to evaluate their role in inducing chilling tolerance of two different chilling-tolerant maize (Zea mays L.) inbred lines. These compounds were applied as seed treatments or as a hydroponic application. The results showed that four compounds had no significant effect on germination of maize seeds; however, SA or ASA soaking treatments significantly increased the root length, shoot height, and shoot and root dry weights of seedlings grown under chilling stress. Hydroponic applications of SA or ASA significantly alleviated the accumulation of malondialdehyde, hydrogen peroxide, and superoxide radicals in roots and leaves of both lines under chilling stress, and the applications also increased the photosynthetic pigments, including chlorophyll a, chlorophyll b, and carotenoids. However, 4-aminosalicylic acid and 4-aminobenzoic acid applications had no significant effect in ameliorating the growth inhibition of seedlings under chilling stress. This study showed that SA and ASA significantly induced the chilling tolerance of maize; however, 4-aminosalicylic acid and 4-aminobenzoic acid were not effective in inducing tolerance to chilling stress. The results suggest that only SA analogues with biological activity may have the ability to induce chilling tolerance of maize.Résumé : Les auteurs ont choisi une sorte d'analogue de l'acide salicylique (AS) (acide acétylsalicylique, AAS) biologiquement actif et deux composés inactifs (acide 4-aminosalycilique et acide 4-aminobenzoique) ainsi que l'AS pour évaluer leur rôle dans l'induction de la tolérance au gel chez deux lignées consanguines et distinctes de maïs (Zea mays L.). Ils ont appliqué ces composés par traitements des graines ou en application hydroponique. Les résultats montrent que quatre traitements sont demeurés sans effet sur la germination des graines de maïs; cependant, les traitements de trempage des graines dans l'AS ou l'AAS augmentent significativement la longueur des racines, la hauteur de la tige, les poids secs de la tige et de la racine chez les plantules soumises à un stress par le gel. Les applications en hydroponique de l'AS ou de l'AAS diminuent significativement l'accumulation de la malondialdéhyde, du peroxyde d'hydrogène et des radicaux superoxyde dans les racines et les feuilles des deux lignées soumises au gel et augmente les pigments photosynthétiques, incluant la chlorophylle a, la chlorophylle b et les caroténoïdes. Cependant, l'acide 4-aminosalycilique et l'acide 4-aminobenzoique n'exercent aucun effet significatif dans l'amélioration de l'inhibition de la croissance par le stress dû au gel. Cette étude montre que l'AS et l'AAS induisent une tolérance significative au gel chez le maïs; cependant, l'acide 4-aminosalycilique et l'acide 4-aminobenzoique demeurent sans effet sur l'induction de la tolérance au stress dû au gel. Les résultats suggèrent que ...

Vigor identification in sweet corn seeds is important for seed germination, crop yield, and quality. In this study, hyperspectral image (HSI) technology integrated with germination tests was applied for feature association analysis and germination performance prediction of sweet corn seeds. In this study, 89 sweet corn seeds (73 for training and the other 16 for testing) were studied and hyperspectral imaging at the spectral range of 400–1000 nm was applied as a nondestructive and accurate technique to identify seed vigor. The root length and seedling length which represent the seed vigor were measured, and principal component regression (PCR), partial least squares (PLS), and kernel principal component regression (KPCR) were used to establish the regression relationship between the hyperspectral feature of seeds and the germination results. Specifically, the relevant characteristic band associated with seed vigor based on the highest correlation coefficient (HCC) was constructed for optimal wavelength selection. The hyperspectral data features were selected by genetic algorithm (GA), successive projections algorithm (SPA), and HCC. The results indicated that the hyperspectral data features obtained based on the HCC method have better prediction results on the seedling length and root length than SPA and GA. By comparing the regression results of KPCR, PCR, and PLS, it can be concluded that the hyperspectral method can predict the root length with a correlation coefficient of 0.7805. The prediction results of different feature selection and regression algorithms for the seedling length were up to 0.6074. The results indicated that, based on hyperspectral technology, the prediction of seedling root length was better than that of seed length.

Drought is one of the most important stress factors limiting the seed industry and crop production. Present study was undertaken to create novel drought-resistant pelleted seeds using the combined materials with superabsorbent polymer, poly(2-acrylamide-2-methyl propane sulfonic acid) (PAMPS) hydrogel, and drought resistance agent, salicylic acid (SA). The optimized PAMPS hydrogel was obtained as the molar ratio of 2-acrylamido-2-methyl-propanesulfonic acid (AMPS) to potassium peroxydisulfate (KPS) and N, N′-methylene-bis-acrylamide (MBA) was 1 : 0.00046 : 0.00134. The hydrogel weight after swelling in deionized water for 24 h reached 4306 times its own dry weight. The water retention ratio (RR) of PAMPS was significantly higher as compared with the control. It could keep as high as 85.3% of original weight after 30 min at 110°C; even at 25°C for 40 d, the PAMPS still kept RR at 33.67%. PAMPS disintegration ratio increased gradually and reached around 30% after embedding in soil or activated sludge for 60 d. In addition, there were better seed germination performance and seedling growth in the pelleted treatments with SA-loaded PAMPS hydrogel under drought stress than control. It suggested that SA-loaded PAMPS hydrogel, a nontoxic superabsorbent polymer, could be used as an effective drought resistance material applied to tobacco pelleted seeds.

The identification of seed vigor is of great significance to improve the seed germination rate, increase crop yield, and ensure product quality. In this study, based on a hyperspectral data acquisition system and an improved feature extraction algorithm, an identification model of the germination characteristics for corn seeds was constructed. In this research, hyperspectral data acquisition and the standard corn seed germination test for Zhengdan 958 were carried out. By integrating the hyperspectral data in the spectral range of 386.7 nm–1016.7 nm and the first derivative information of the spectral data, the root length prediction for corn seeds was successfully completed. The data regression model and prediction relationship between the spectral characteristics and seedling root length were established by principal component regression, partial least squares, and support vector regression. The first derivative information of the hyperspectral data was obtained by comparing the prediction model results with the original spectral data, which was preprocessed by Savitzky–Golay smoothing, multiplicative scatter correction, standard normal variate, and curve fitting. The results showed that the prediction model based on the first-order differential spectral data showed better performance than the one based on the spectral data obtained by other processing algorithms. By comparing the prediction results using different data characteristics and regression models, it was found that the hyperspectral method can effectively predict the root length of the seed, with the coefficient of determination reaching 0.8319.

In this work, a new local fault classification technique named neighbourhoodpreserving discriminant analysis (NPDA) was developed and applied for fault classification in industrial processes. Rather than using traditional global modelling methods, we used the neighbourhood-preserving embedding (NPE) algorithm, which describes data features stably and reliably. Taking the latent variables obtained by NPE and Fisher discriminant analysis (FDA) as the classification features, a classification model was constructed by NPDA and used to classify various types of faults. To evaluate fault classification, case studies on a continuous stirred tank heater process and a Tennessee Eastman benchmark process were conducted. The effectiveness of the proposed approach was confirmed, as improved classification results were obtained by NPDA.