In order to measure wheat yield and wheat spike phenotypes, the grain number of wheat spikes is counted manually at present, but acquiring the grain number of wheat spikes is laborious and time-consuming. Counting the grain number of wheat spikes with an image processing method is promising, yet the application of this method is flawed due to its low accuracy. In this work, images of wheat spikes were collected and processed with technical procedures, including image cropping, image graying, histogram equalization, image binarization, eroding operation, removing small objects, filling image holes, revolving vertical spikes, cutting off stems, and removing stems. Wheat stems in binary images were eliminated by the sum pixels method, and the morphological characteristic parameters of the image areas of wheat spikes and lengths of wheat spike axes were calculated. Mathematical models relating the image areas of wheat spikes and lengths of the wheat spike axes to the grain number were established, and the mathematical models were verified. The results showed that the characteristic parameters of the image areas of wheat spikes and the lengths of the wheat spike axes for the spike images were linear relative to the grain number, and the maximum determination coefficients R² were 0.9336 and 0.9012, respectively. The maximum determination coefficients R² for the practical and predicted grain numbers were 0.9552 and 0.9369, respectively, and the minimum average absolute error was 2.3, while the average relative error for the mathematical models was 5.65%. The mathematical models relating the image areas of wheat spikes and the lengths of the wheat spike axes to the grain number were practical and accurate, and the mathematical model comparing the image area of wheat spikes and the grain number was superior to that comparing the length of the wheat spike axis and the grain number. The grain number of wheat spikes could be acquired accurately and quickly by the image processing method extracting the characteristic parameters of wheat spikes.

Mechanical damage to wheat grains is inevitable during harvester threshing; damaged wheat grains are vulnerable to mold colonies. Selecting optimal threshing pattern is an important approach to reduce wheat storage quality loss for threshing damage. Wheat harvested by tangential flow threshing patterns (TFTP) and axial flow threshing patterns (AFTP) were used as test samples and wheat harvested manually were used as control samples. Moisture contents of all wheat grains were adjusted to 18% (wet basis) before storage, then wheat grains were stored in an artificial climate box at temperature of 30 °C and humidity of 80% RH. The mold colonies and fatty acids value of wheat harvested by TFTP increased faster than those of wheat harvested by AFTP, the dry basis 1000 grain weight, seed vigor and germinating traits of wheat harvested by TFTP decreased faster than those by AFTP during storage. After storage, there were significant differences between TFTP and AFTP in the mold colonies, seed vigor, dry basis 1000 grain weight (p < 0.05). Germination potential and rate were significantly negative correlation with mold colonies. Aberrations of seedling and mold colonies in seedling root had significantly positive correlation with the mold colonies. The storage quality traits of wheat harvested by AFTP were better than those of wheat harvested by TFTP. AFTP should be preferred for wheat harvested mechanically in terms of the storage quality of wheat.

Sowing space and depth critically influence wheat canopy architecture, yet their layer-specific effects remain poorly understood. This two-year field study evaluated the effects of three sowing spaces (1.5, 3.0, 4.5 cm) and three sowing depths (2, 3, 6 cm) on canopy projection area, leaf inclination angle, leaf area distribution, and leaf area index (LAI) of dryland wheat (Triticum aestivum ‘Ningmai 13’) in Luhe, Nanjing, China, using image-based phenotyping with manual validation. Narrow spacing (1.5 cm) with intermediate depth (3 cm) produced the largest canopy projection area (0.239–0.245 m²) and an increase in leaf erectness in the middle canopy layer (+23% above average). The highest LAI values (4.23–4.28 m² m⁻²) were achieved with narrow spacing (A₁B₁, A₁B₂), demonstrating that dense canopies can be established under dryland conditions. Grain yield (g/plant) was measured as a supporting agronomic indicator; the highest yield per plant (14.36 g/plant) was observed in A₃B₁. Image-based measurements showed excellent agreement with manual methods (R² > 0.97 for all traits), validating the phenotyping pipeline. These findings contribute to a deeper understanding of how sowing parameters shape wheat canopies in dryland systems.