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The contribution of spike photosynthesis to grain yield (GY) has been overlooked in the accurate spectral prediction of yield. Thus, it’s essential to construct and estimate a yield-related phenotypic trait considering spike photosynthesis. Based on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years, our objectives were to (i) construct a yield-related phenotypic trait (spike–leaf composite indicator, SLI) accounting for the contribution of the spike to photosynthesis, (ii) develop a novel spectral index (enhanced triangle vegetation index, ETVI3) sensitive to SLI, and (iii) establish and evaluate SLI estimation models by integrating spectral indices and machine learning algorithms. The results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area index. ETVI3 maintained a strong correlation with SLI throughout the growth stage, whereas the correlations of other spectral indices with SLI were poor after spike emergence. Integrating spectral indices and machine learning algorithms improved the estimation accuracy of SLI, with the most accurate estimates of SLI showing coefficient of determination, root mean square error (RMSE), and relative RMSE values of 0.71, 0.047, and 26.93%, respectively. These results provide new insights into the role of fruiting organs for the accurate spectral prediction of GY. This high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.

β-Ga2O3 photodetectors have the advantages of low dark current and strong radiation resistance in UV detection. However, the limited photocurrent has restricted their applications. Herein, MSM UV photodetectors based on (InxGa1−x)2O3 (x = 0, 0.1, 0.2, 0.3) by a sol-gel method were fabricated and studied. The doping of indium ions in Ga2O3 leads to lattice distortion and promotes the formation of oxygen vacancies. The oxygen vacancies in (InxGa1−x)2O3 can be modulated by various proportions of indium, and the increased oxygen vacancies contribute to the enhancement of electron concentration. The results show that the amorphous In0.4Ga1.6O3 photodetector exhibited improved performances, including a high light-to-dark current ratio (2.8 × 103) and high responsivity (739.2 A/W). This work provides a promising semiconductor material In0.4Ga1.6O3 for high-performance MSM UV photodetectors.