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Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772–0.942, 0.774–0.970, 0754–0.960, and 0.800–0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index.

Background: Root-knot nematodes (RKN, Meloidogyne spp.) are economically significant pests that cause immense damage to a wide range of crops. Among them, M. incognita and M. enterolobii are of particular concern, as their high virulence and broad host range. RKN are challenging for detection due to their subterranean lifestyle underground. Also, the mixed infection of nematodes in field crops complicates the need for more accurate diagnostic and quantification technologies., Results: To address this challenge, we developed and optimized a novel duplex droplet digital PCR (ddPCR) method, using primer/probe sets targeting M. incognita and M. enterolobii, to simultaneously identify and quantify both species within a single assay. The innovative ddPCR diagnostic demonstrated excellent performance in terms of sensitivity, precision and reproductivity when quantifying the eggs and soil samples containing juveniles of both species. Moreover, the application of the duplex ddPCR method enables the monitoring of population dynamics of M. incognita and M. enterolobii under competitive environmental conditions. Our results indicated that the reproduction factor of M. incognita possibly inhibited when in mixed populations of M. enterolobii., Conclusion: In this study, we first applied duplex ddPCR technique for differentiating mixed infections of M. incognita and M. enterolobii, offering a valuable tool for species detection and quantification. It enables the monitoring of population dynamics for both species, which is crucial for providing theoretical guidance for the implementation of timely and effective control measures. © 2024 Society of Chemical Industry., (© 2024 Society of Chemical Industry.)