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Soil parameters, measured before crop planting, are typically used to quantify the relationship between soil properties and crop yield and to identify factors limiting crop yield. However, soil properties during sensitive stages of crop growth may have a greater effect on crop yield than the initial values. We determined if inclusion of soil properties, measured during the reproductive stage, could improve the accuracy of crop yield prediction. Classification and regression trees were used to determine the explanatory power of different soil and rice variables for predicting rice yield in alkaline salt‐affected paddy fields in northeast China. The traditional method explained 77.5% of the rice yield variation and identified soil CO₃²⁻ in the 0‐ to 10‐cm soil layer, with single explanatory power of 53.4%, as the most important predictor. The whole explanatory power of the methods including soil variables during the reproductive stage and yield components, with/without soil variables before planting, increased to 81.3%. The residual sodium carbonate, measured in the 0‐ to 10‐cm soil layer during the reproductive stage, was identified as the most limiting factor due to its single maximum explanatory power of 60.5%. We conclude that inclusion of soil properties, measured during the reproductive stage, has potential for improving the rice yield prediction accuracy by enhancing the explanatory power in identification of the most limiting factor. These results encourage further investigation of the role of soil properties during sensitive stages of crop growth in crop yield prediction under different soil and climatic conditions.

Problems with rehydration and palatability are considered as unacceptable quality characteristics for the noodles produced using high-strength extrusion technique. Thus, the aim of this study was to solve these problems by designing a novel method to create a porous structure for the high-strength extruded noodles (HENs). The quality indices of HENs were significantly improved after adding to them thermostable α-amylase (TαA) at 0.05% to 0.10%. The microstructure graphs showed that a well-developed porous structures was successfully created throughout noodle strands. This indicated that the TαA has effectively worked on starch granules in spite of the high-strength performance of the extrusion process. MALLS-GFC, X-ray diffraction, and differential scanning calorimeter investigations showed that the appearance of a porous structure was mainly attributed to the internal collapse of α-1,4-glycosidic bonds and the dissolution of water-soluble degradation products, such as dextrin and oligosaccharides. Moreover, the slight inhibited effect of excess TαA on the starch gelatinization was because of the fact that the high enzyme concentration might cause TαA to adhere or overlay on it. Practical application The rehydration and palatability properties of HENs were greatly improved by creating a well-developed or honeycomb-like porous structure using TαA at low concentration. The findings of this study could be applied to enhance the quality characteristics of HENs and to encourage the research and development in the noodle industry.