International audienceThis article tackles the multi-trip vehicle routing problem with time windows and limited duration. A trip is a timed route such that a succession of trips can be assigned to one vehicle. We provide an exact two-phase algorithm to solve it. The first phase enumerates possible ordered lists of clients which match the maximum trip duration criterion. The second phase uses a Branch and Price scheme to generate and choose a best set of trips so that all customers are visited. We propose a set covering formulation as the column generation master problem, where columns (variables) represent trips. The sub-problem selects appropriate timing for trips and has a pseudo-polynomial complexity. Computational results on Solomon's benchmarks are presented. The computational times obtained with our new algorithm are much lower than the ones recently obtained in the only two studies published on this problem to date

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The design of Mildium results from the formalisation of a common management of both powdery and downy mildews and eventually leads to a significant fungicide reduction at the plot scale. It could encourage stakeholders to design customised farm-scale and low-chemical-input decision support methods.

In 2016, spray deposit measurements have been carried out according to ISO22522:2007 on a vine estate (Domaine Mas Piquet, 15 ha, Languedoc). On this estate, plots vigor ranges from low to medium compared to other vineyards. On 4 days (28th April, 25th May, 23rd June and 18th July 2016), spray deposition has been measured on 5 plots of different vine varieties chosen for their distinct vigor. Two different sprayers have been used: a low performance sprayer (pneumatic arch sprayer used every 4 rows) and a high performance sprayer (air assisted side by side sprayer). Spray deposition was measured using a tracer (Tartrazine E102) sprayed on sampling 40 cm² PVC collectors placed within the vegetation: on each plot, 4 trees have been sampled for each sprayer. On each tree, collectors were positioned on leaves within the canopy according to a profile perpendicular to the row, following a grid 20 cm high and 10 cm wide with one collector per pixel. A total amount of 3048 collectors have been analyzed individually. The dataset provide the normalized deposit expressed per unit of leaves area for one gram of tracer sprayed per hectare (unit: ng dm−2 for 1 g ha−1) on each collector. In addition, the dataset propose crop parameters measured manually on each sampled tree: inter-row distance, height, average of thickness in order to calculate two crop structure indicators: TRV (Tree Row volume) and LWA (Leaf Wall Area).

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Abstract:The world we live in is an increasingly spatial and temporal data-rich environment, and agriculture is no exception. However, data needs to be processed in order to first get information and then make informed management decisions. The concepts of 'Precision Agriculture' and 'Smart Agriculture' are and will be fully effective when methods and tools are available to practitioners to support this transformation. An open-source software called GeoFIS has been designed with this objective. It was designed to cover the whole process from spatial data to spatial information and decision support. The purpose of this paper is to evaluate the abilities of GeoFIS along with its embedded algorithms to address the main features required by farmers, advisors, or spatial analysts when dealing with precision agriculture data. Three case studies are investigated in the paper: (i) mapping of the spatial variability in the data; (ii) evaluation and cross-comparison of the opportunity for site-specific management in multiple fields; and (iii) delineation of within-field zones for variable-rate applications when these latter are considered opportune. These case studies were applied to three contrasting crop types, banana, wheat and vineyards. These were chosen to highlight the diversity of applications and data characteristics that might be handled with GeoFIS. For each case-study, up-to-date algorithms arising from research studies and implemented in GeoFIS were used to process these precision agriculture data. Areas for future development and possible relations with existing geographic information systems (GIS) software is also discussed.

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