Precision Agriculture in Sugar Cane Production Josh Lofton

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Precision Agriculture in Sugar Cane Production Josh Lofton 4/24/09

Precision Agriculture in Sugar Cane Production Josh Lofton 4/24/09

Intro into sugar cane • First mention of sugar cane in history was from

Intro into sugar cane • First mention of sugar cane in history was from Alexander in 326 BC in India • All sugar cane grown today are hybrids • US is 9 th largest producer of sugar cane with 28 million tons • Traditionally planted and grown for 3 -5 years – Plant crop – Ratoon crop

Intro into sugar cane • • Planted on bed with furrow measuring 15 -24”

Intro into sugar cane • • Planted on bed with furrow measuring 15 -24” Planted from late August to October Pre-plant fertilizers of 15 -45 -45 at planting Spring application of fertilizer – From mid-February to mid-May – From 60 -140 lbs N ac-1

Problem • Precision agriculture work in sugar cane has been slow • Currently most

Problem • Precision agriculture work in sugar cane has been slow • Currently most producers are only doing first generation precision agriculture • Sugar cane yield map suggested that sugar cane can vary in yield throughout the field – 70 -220 t ha-1

Current Practices • University of Florida is suggest using grid soil sampling techniques •

Current Practices • University of Florida is suggest using grid soil sampling techniques • Currently no yield monitoring system is commercially available • However there are many prototypes – LSU – Brazil – Australia

Current Practices • No literature on precision pest management • Field by field water

Current Practices • No literature on precision pest management • Field by field water management – Planting techniques – Buffer strips http: //www. oh. nrcs. usda. gov/programs/Lake_Erie_Buffer/images/Final_Report/grass_filter_strip_50 p. jp g

Potential for precision agriculture • Hybrid selection • Width between furrows • Commercial yield

Potential for precision agriculture • Hybrid selection • Width between furrows • Commercial yield monitor • More reliable measurement on replanting

Potential of precision agriculture • Knowing the soil properties • Better estimates of nutrient

Potential of precision agriculture • Knowing the soil properties • Better estimates of nutrient needs – Algorithm development • Variable rate application

Future • Mechanization of production needs to continue to grow • Educating producers http:

Future • Mechanization of production needs to continue to grow • Educating producers http: //www. soils. wisc. edu/extension /Assets/NWWFD 05. jpg

Sources • • FAO UC Davis LSU University of Florida

Sources • • FAO UC Davis LSU University of Florida

QUESTIONS?

QUESTIONS?