Precision harvesting and traceability in Durum wheat

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Presentation transcript:

Precision harvesting and traceability in Durum wheat Francesco Morari DAFNAE, University of Padova

Veneto Region: the landscape

Pasta can be made with flour of different cereals… Pasta can be made with flour of different cereals….. but the best past is made with flour of Durum wheat…. 1) Durum wheat produces pasta with good cooking quality and stability to overcooking 2) High quality pasta = high protein content & high gluten content

High quality standard could be guaranteed by mean of: North Italy represents the northern limit for cultivation of durum wheat in Europe with uncertain results in terms of grain quality (e.g. protein content). Grain quality is strongly influenced by the interactions between cultivar, management and pedo-climatic conditions High quality standard could be guaranteed by mean of: Variety selection N input at rates often double than those required to maximizing grain yield Higher cost and environmental problems

Precision agriculture and sensor technologies offer new potentialities to meet grain quality standards N variable rate application and site-specific N balance optimize N input according to soil variability with an overall increase of N efficiency and reduction of N leaching and GHGs emission Precision harvesting maximize the tonnage of higher quality grades, allowing to separate the grain according to its quality

$ Precision harvesting The Italian cereal market offers a premium to durum wheat stocks with a protein content > 13.5% Homogeneous harvest 13.2 % no premium $ 13.7% Precision harvest 13.7 % premium 12% no premium 12% Map of protein content

The case study of Miana Serraglia farm Location: Venice Lagoon watershed Field size: 13.5 ha Problem: area classified as Nitrate Vulnerable Zone (EU Nitrate Directive) Goal: increase quality/quantity of durum wheat mitigating N pollution

Nitrogen VRA based on prescription map Durum wheat (cv Biensur ) 2 years 2010-2011 sod-seeding, Fertilization tillering stage (February) – base fertilisation 52 kg ha-1 y-1 (AN) stem elongation (April) differentiated in the MZs (U) flowering stage (May ) 15 kg ha-1 y-1 (foliar-UAN)

Yield and protein contents were measured in continuous Sensed points

Rx Grains – scanning camera- Sensor: 256 pixel diode array sensor (MMS1, Zeiss, Germany) range of 400-1100nm Infrared light source: 20W halogen lamp

Management zone harvesting (MZ) Each Homogeneous zone (HZ) is separately harvested. HZ are identified using GPS system mounted on combine.

Grain flour quality in management zone harvesting Sequential protein extractions on grain flour were performed on 6 sub-samples per MZ Different gluten protein fractions, gliadins, high (HMW-GS) and low-molecular weight glutenins (LMW-GS) were quantified spectrophotometrically Higher quality higher content of gluten higher ratio HMW/LMW higher ratio glutenins/gliadins

Making site-specific pasta Evaluation in terms of technological properties organoleptic test

Year 2011 Water stress in the last part of crop cycle strongly affected the wheat performances High variability within the zones

NDVI maps

Protein quality first year Higher quality in LFZ higher content of gluten higher ratio HMW/LMW higher ratio glutenins/gliadins

Year 2012

Year 2012

Site-specific pasta 200+ 15 200+0 130 +0 130 +15 160+0 160+15

Technological parameters: firmness Pasini et al., 2017)

What next?

Management zone harvesting (MZ) Each Homogeneous zone (HZ) is separately harvested. HZ are identified using GPS system mounted on combine. No necessity the presence of NIR sensor on combine Product selected on the basis of qualitative potential of each HZ.

On-combine differential harvesting <13,5% > 13,5% On-combine differential harvesting (CD) The combine’s hopper is divided into two different bins. NIRs sensor gives information on the go about field protein. It is important to check the right cut-off value. Cillis et al., 2016

Cillis et al., 2016

Research Partners Giuliano Mosca Luigi Sartori Donato Cillis Paolo Berzaghi Gabriella Pasini Giovanni Visioli Roberto Ferrise Marco Bindi Research supported by Progetto AGER, grant n. 2010-C21J10000660002

Thank you for your attention