As the channels for straw usage are steadily increasing, sub-plot level straw information abundance is increasingly a topic drawing the attention. However, a systematic investigation on sub-plot straw information abundance is lacking. A field study was conducted in a post-harvest wheat field to explain sub-plot straw information abundance. Multiple indicators were proposed, including straw mass distribution, fragmented straw clumping index, side-shadow of standing straw, fragmentation index of straw pieces, lodging index of standing straw etc., and specific digitization techniques were designed, i.e. cell sampling + weighing method, machine vision with uniform layer straw on white plate method, background plate side vison method, sieving method, supplemented with manual counting for calibration. In addition to the acquired indices, normalized parameters of straw information were analyzed and the correlations among indicators were visually explained. Results showed that techniques investigated in this work were effective for collecting straw information for improved info-abundance. Information technologies proposed were powerful when applied for interpretating the underlying causes for each indicators, e.g. straw distribution within the cutter width, influence from wheat row width, straw exits performance, straw damage status by the harvesters etc. Correlation analysis also indicated relationships among observed indicators, e.g. similarity between straw mass distribution and fragmented straw distribution was 0.89, yet the value was 0.43 with standing straw distribution. Fragmented straw has 0.64 in similar with clumping index, while that for standing straw and side-shadow was 0.48. Achieved results by this work could be useful for future when the subplot straw information abundance and its utilization were to be systematically investigated.