Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced endeffectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.

Following the finalization of the work performed to establish the triplepoint temperature versus isotopic composition relationship for protium (Metrologia 42, 171 (2005)) adopted into the ITS-90 definition by the International Committee for Weights and Measures (CIPM) in 2005, and a preliminary exploration of the variability in the triple-point temperature of neon gas samples arising from differences in isotopic

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Spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) imagery is a valuable tool to monitor plant nutrition, reduce nitrogen (N) application to real needs, thus producing both economic and environmental benefits. The objectives of the trial were i) to compare the spectral reflectance of 3 turfgrasses acquired via UAV and by a ground-based instrument; ii) to test the sensitivity of the 2 data acquisition sources in detecting induced variation in N levels. N application gradients from 0 to 250 kg ha-1 were created on 3 different turfgrass species: Cynodon dactylon x transvaalensis (Cdxt) ‘Patriot’, Zoysia matrella (Zm) ‘Zeon’ and Paspalum vaginatum (Pv) ‘Salam’. Proximity and remote-sensed reflectance measurements were acquired using a GreenSeeker handheld crop sensor and a UAV with onboard a multispectral sensor, to determine Normalized Difference Vegetation Index (NDVI). Proximity-sensed NDVI is highly correlated with data acquired from UAV with r values ranging from 0.83 (Zm) to 0.97 (Cdxt). Relating NDVI-UAV with clippings N, the highest r is for Cdxt (0.95). The most reactive species to N fertilization is Cdxt with a clippings N% ranging from 1.2% to 4.1%. UAV imagery can adequately assess the N status of turfgrasses and its spatial variability within a species, so for large areas, such as golf courses, sod farms or race courses, UAV acquired data can optimize turf management. For relatively small green areas, a hand-held crop sensor can be a less expensive and more practical option.

This chapter describes the three main techniques of mechanical weed management, i.e. (1) the use of tillage, (2) cutting weeds, and (3) pulling weeds. The economics of mechanical weed management is discussed.

Intra-row weed control in organic or low-input cropping systems is more difficult than in conventional agriculture. The various mechanical and thermal devices available for intra-row weed control are reported in this review. Low-tech mechanical devices such as cultivators, finger-weeders, brush weeders, and torsion-weeders tend to be used in low density crops, while spring-tine harrows are mainly applied in narrow-row high-density crops. Flame weeding can be used for both narrow and wide-row sown crops, provided that the crop is heat-tolerant. Robotic weeders are the most recent addition to agricultural engineering, and only a few are available on the market. Nowadays, robotic weeders are not yet used in small and medium sized farms. In Europe, high-income niche crops are often cultivated in small farms and farmers cannot invest in high-tech solutions. Irrespectively of the choice of low- or high-tech machines, there are several weeders that can be used to reduce the use of herbicides, making of them a judicious use, or decide to avoid them

Autonomous mowers are battery-powered machines designed for lawn mowing that require very low human labour. Autonomous mowers can increase turf quality and reduce local noise and pollution compared with gasoline-powered rotary mowers. However, very little is known about the effects of autonomous mowing on encroaching weeds. The aim of this research was to compare the effects of an autonomous mower and an ordinary gasoline-powered mower on weed development in an artificially infested tall fescue (Festuca arundinacea Schreb.) turf with different nitrogen (N) rates. A three-way factor experimental design with three replications was adopted. Factor A consisted of three N rates (0, 75, and 150 kg ha −1 ), factor B consisted of two mowing systems (autonomous mower vs. walk-behind gasoline rotary mower equipped for mulching), and factor C which consisted of four different transplanted weed species: (a) Bellis perennis L., (b) Trifolium repens L.; (c) Trifolium subterraneum L.; and (d) Lotus corniculatus L. Of these, B. perennis is a rosette-type plant, while the other three species are creeping-type plants. The interaction between mowing system and transplanted weed species showed that the four transplanted weed species were larger when mowed by the autonomous mower than by the rotary mower. The autonomous mower yielded larger weeds probably because the constant mowing height caused the creeping weed species to grow sideways, since the turfgrass offered no competition for light. N fertilization increased turf quality and mowing quality, and also reduced spontaneous weed infestation. Autonomous mowing increased turf quality, mowing quality, but also the percentage of spontaneous weed cover.

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