What’s the hardest part of growing cotton? Seeing what needs attention.
When spraying, it can be difficult to know where pests are concentrated. When fertilizing, it can be difficult to see which areas need closer inspection. As harvest approaches, different parts of a field may develop at different speeds. A whole season involves decisions that experience alone cannot always resolve.
FieldFusion satellite NDVI comparisons make changes in vegetation visible on a map. The following April–October sequence shows how that view can support a cotton management workflow: find a difference, scout the field, decide what to do, and compare again.
Reading these maps: use the NDVI legend and acquisition dates in each image. Color palettes vary, and a color alone does not diagnose pests, nutrient deficiency or harvest readiness. This seasonal sequence illustrates a workflow; local crop timing, weather and field conditions determine the right action.
April · Sowing: everything starts with a clean field
Plowing, basal fertilizer, land leveling and removal of residual mulch prepare the seedbed. The early comparison establishes a starting point before a strong vegetation signal develops. Save this baseline so later changes can be read in context.
May · Emergence: uneven growth, spotted at a glance
As seedlings emerge, vegetation patterns become more visible. Compare the same field across dates to locate patches that differ from their surroundings. Those areas give a practical starting point for checking emergence, soil moisture and crop condition on the ground.
Next step: inspect missing patches before considering reseeding or transplanting. Check weaker areas before deciding whether water, nutrition or another factor requires attention.
June · Squaring: put fertilizer where it is needed
During squaring, canopy cover expands and differences between zones become easier to compare. Use the map to guide scouting, then combine field observations with soil information and agronomic advice to decide which areas need intervention.
Precision water and fertilizer management: where supported by the irrigation and application setup, zone-based decisions can help target inputs. NDVI alone should not set fertilizer rates; confirm the cause of a weak signal and the compatibility of the receiving equipment.
July · Flowering and bolling: canopy closure calls for closer scouting
As the canopy develops and cotton enters flowering and boll setting, keep monitoring changes while checking crop condition in the field. The supplied seasonal workflow also highlights topping and scouting for cotton bollworm and spider mites at this stage.
Precision spraying: use observed changes to prioritize scouting. Where pests are confirmed, plan treatment using field evidence and product guidance. NDVI does not identify a pest species or replace scouting; prescription execution depends on compatible equipment.
August–September · Boll fill: stability first
During boll filling, watch whether vegetation patterns remain stable or begin to change. Follow up on unusual zones and combine map observations with checks on irrigation, nutrition and boll condition. The aim is to support crop development through consistent, timely management.
October · Harvest: read the change, then confirm readiness
Later in the season, a declining vegetation signal can accompany crop senescence or defoliation. Compare dates to see where changes are happening, then check boll opening, crop condition and local harvest requirements before making a decision.
Precision harvest planning: confirm defoliation and boll opening in the field, organize harvest batches, and adjust machine settings for actual conditions. Map colors alone do not confirm maturity, fiber quality or a yield gain.
From experience, to visible data
- Precision spraying: focus scouting on areas that need attention, then plan treatment using confirmed field evidence.
- Precision fertilizing: compare management zones and combine map data with agronomic recommendations.
- Better-informed yield management: track the whole season and keep decisions connected to observations. Outcomes depend on field conditions and execution.