Intelligent detection of hard seeds of snap bean based on hyperspectral imaging.

As a common problem in snap beans, hard seed has seriously affected the large-scale industrial planting and yield of snap bean. To realize accurate, quick and non-destructive identifying the hard seeds of snap bean is of great significance to avoiding the effects of hard seeds on germination and growth. This research was based on hyperspectral imaging (HSI) to achieve accurate detection of hard seeds of snap bean. This study obtained the characteristic spectra from the hyperspectral image of a single seed, and then combined the synthetic minority over-sampling technique (SMOTE) and Tomek links to balance the numbers of hard and non-hard seed samples. The characteristic wavelengths were extracted from the average spectrum. Then the average spectrum was processed by first derivative (1D). After that, the characteristic wavelengths could be extracted using successive projections algorithm (SPA). Finally, a radial basis function-support vector machine (RBF-SVM) model was established to realize the intelligent detection of hard seeds, and the detection accuracy rate reached 89.32%. The research results showed that HSI technology could achieved accurate, fast and non-destructive testing of the hard seeds of snap bean, which is of great significance to the large-scale and standardized planting of snap bean and increase the yield per unit area.

Beam waist shrinkage of high-power broad-area diode lasers by mode tailoring.

A new approach was proposed and its role in improvement of the beam quality of high-power broad-area diode lasers was demonstrated, in which a composite arrow array and trench microstructure was used to suppress the beam waist and tailor the high order lateral modes. The beam waist shows a special shrinkage with increasing injection current resulting from the combined effect of mode tailoring and the thermal lens effect. A 58% improvement in lateral beam parameter product was realized compared with conventional broad-area diode lasers.

Does dual reduction in chemical fertilizer and pesticides improve nutrient loss and tea yield and quality? A pilot study in a green tea garden in Shaoxing, Zhejiang Province, China.

Tea tree (Camellia sinensis) is a valuable and popular cash crop widely planted in tropical and subtropical areas of China. To increase tea yield and quality, high rates of chemical fertilizer and pesticide application have generally been used; however, increasing usage of fertilizers and pesticides does not always proportionally increase tea yield. Indeed, excessive nutrient inputs may cause serious agricultural non-point source pollution. A pilot study on dual reduction in fertilizers and pesticides was conducted in a green tea plantation in Shaoxing, Zhejiang Province, to explore the environmental effects of different fertilizer and pesticide managements (e.g., changes in soil properties and nutrient accumulation, nutrient inputs in runoff water) and to reveal the potential effects of the interaction of these two managements on tea yield and quality. Traditional formulas and rates of chemical fertilizers and pesticides were used as the baselines (100% usage); replacement with different proportions of organic fertilizer (i.e., 20%, 50% and 80%) and direct pesticide reductions of 30%, 50%, and 80% were tested. The results showed that proper management with organic fertilizer replacement can effectively mitigate soil acidification and nutrient deficiency in tea plantations, increase soil organic matter (OM) and ammonium nitrogen (NH4-N) contents, and promote tea yield and quality. Moreover, managements with organic fertilizer replacement can markedly reduce the inputs of ammonium nitrogen (NH4-N), nitrate nitrogen (NO3-N), total phosphorus (TP), and total potassium (TK) in runoff water. Soil nutrient accumulation was the highest while the runoff nutrient input was the lowest at 20% organic fertilizer replacement. Experimental spraying of bifenthrin and chlorfenapyr revealed that these pesticides were mainly trapped by the tea leaves and rarely entered the soil or water bodies. Although pesticide reduction treatments can effectively decrease pesticide residues in tea leaves, differences in pesticide residue between various treatments were not obvious due to the rapid degradation of pesticides. Multivariate analysis of variance showed that 50% of the variation in tea yield, bud density, polyphenols, and caffeine can be explained by interactions between fertilizers and pesticides. Combinations of 20% or 50% organic fertilizer replacement and 30% or 50% pesticide application reduction are appropriate for both mitigating nutrient loss and balancing tea yield and quality, especially the combination of 50% organic fertilizer replacement and 50% pesticide reduction, which produced the best results. This study demonstrates the feasibility of dual reductions in fertilizers and pesticides for mitigating environmental hazards while maintaining the yield and quality of tea.