Coefficients of repair and maintenance costs of self-propelled combine harvesters in Italy

Purchasing and maintaining agricultural machines are two of the most considerable costs of the agricultural sector, which includes farm equipment manufacturers, farm contractors and farms.  In this context, repair and maintenance costs (R&M costs) generally constitute 10%-15% of the total costs related to agricultural equipment and tend to increase with the age of the equipment; hence, an important consideration in farm management is the optimal time for equipment replacement.  R&M cost estimation models, calculated as a function of accumulated working hours, are usually developed by ASAE/ASABE for the agricultural situation in the United States, which is considerably different than agricultural context of other countries.  So, the goal of this work is to recalculate model parameters according to the Italian situation.  For this purpose, data related to 20 self-propelled combine harvesters in Italy were collected. According to the model, which was obtained by interpolating the data through a two-parameter power function (as proposed by the literature), the R&M cost incidence on the list price of Italian self-propelled combine harvesters at 3,000 working hours (estimated life of the machines) was 23.1% as compared with 40.2% calculated through the most recent U.S. model.    Keywords: operating costs, agricultural mechanization, machinery managemen

Optical devices evaluation for diagnosis of Plasmopara viticola

Remote sensing (RS) is the most widely adopted technique for crop monitoring in precision viticulture (PV).  Recent research looks at the development of proximal sensing technologies alternative to RS.  The present work considers the possible use of proximal sensing optical devices for diagnosis in vineyard; in particular, we evaluated the GreenSeeker RT100 and the Crop Circle (two commercial optical sensors) in detecting different levels of grapevine downy mildew symptoms.  The analysis was conducted on vine leaves that had been picked from plants of cv.  Cabernet Franc infected by Plasmopara viticola.  Leaves were divided into homogeneous infection classes and then analyzed through the optical devices and a portable Vis/NIR (visible/near infrared) spectrophotometer used as tester.  Data showed a linear relation between the percentage of symptomatic leaf area and normalized difference vegetation index NDVI calculated through the two optical sensors (R2 = 0.708 for GreenSeeker; R2 = 0.599 for Crop Circle; R2 = 0.950 for the spectrophotometer).  The regression obtained for GreenSeeker is more significant than the regression obtained for Crop Circle.  This fact suggests a greater capability of GreenSeeker than Crop Circle in detecting different disease levels and its possible use in diagnosis application in vineyard.Keywords: precision viticulture, diagnosis, NDVI, proximal sensing, optical devices 

The profitability of precision spraying on specialty crops: a technical–economic analysis of protection equipment at increasing technological levels

A technical–economic analysis was conducted on three different technological levels of spraying equipment for specialty crops, based on the results on precision spraying technologies reported in scientific literature. The application scenarios referred to general protection protocols against fungal diseases adopted in vineyards and apple orchards in Central-Southern Europe. The analysis evaluated the total costs of protection treatments (equipment + pesticide costs), comparing the use of conventional air-blast sprayers (referred to as L0), of on–off switching sprayers (L1), and of canopy-optimised distribution sprayers (L2). Pesticide savings from 10 to 35% were associated with equipment L1 and L2, as compared to L0. Within the assumptions made, on grapevines, the conventional sprayer L0 resulted in the most profitable option for vineyard areas smaller than 10 ha; from 10 ha to approximately 100 ha, L1 was the best option, while above 100 ha, the more advanced equipment L2 resulted in the best choice. On apple orchards, L0 was the best option for areas smaller than 17 ha. Above this value, L1 was more profitable, while L2 never proved advantageous. Finally, in a speculation on possible prospectives of precision spraying on specialty crops, the introduction of an autonomous robotic platform able to selectively target the pesticide on diseased areas was hypothesised. The analysis indicated that the purchase price that would make the robotic platform profitable, thanks to the assumed pesticide and labour savings over conventional sprayers, was unrealistically lower than current industrial cost. This study showed that, in current conditions, profitability cannot be the only driver for possible adoption of intelligent robotic platforms for precision spraying on specialty crops, while on–off and canopy-optimised technologies can be profitable over conventional spraying in specific conditions

Comparing commercial optical sensors for crop monitoring tasks in precision viticulture.

The emergence of precision agriculture technologies and an increasing demand for higher quality grape products has led to a growing interest in Precision Viticulture. Actually, cultural monitoring is the most important application in PV systems: it requires specific technologies able to investigate the cultural conditions. To this aim, typically remote sensing surveys are adopted. These, anyhow, involve technical, economical and organisational barriers hampering a wide diffusion of their application. In order to overcome these problems, it would be necessary to substitute and/or integrate remote sensing information with alternative ground sensing technologies, to be employed directly inside the vineyard. This paper considers a commercial optical sensor, the GreenSeeker, useful in ground sensing surveys, and it compares its performances in monitoring vine with results obtained by a multispectral digital camera used as a tester. The experimentation was carried out in a greenhouse, on an artificial row including 15 grapevines (Cabernet Sauvignon variety). In front of the row, it was fixed a metallic rail gauge in order to permit a longitudinal movement of the Greenseeker sensor. Each plant was investigated at three different heights with a 5 s data time acquisition. Simultaneously, photos of the same grapevine were took by a multispectral digital camera, in order to obtain NDVI values through image analysis. The multispectral digital camera, normally used for remote sensing survey in agriculture, was considered as a test. Results demonstrate a strength correlation (R2 = 0.97) between the NDVI values measured through the two methods. This shows the same behaviour of the two tools, according to crop vigour and stress conditions induced into the plants. Consequently the GreenSeeker can be considered as a suitable solution for cultural monitoring in viticulture

Analysis of electric energy consumption of automatic milking systems in different configurations and operative conditions.

Automatic milking systems (AMS) have been a revolutionary innovation in dairy cow farming. Currently, more than 10,000 dairy cow farms worldwide use AMS to milk their cows. Electric consumption is one of the most relevant and uncontrollable operational cost of AMS, ranging between 35 and 40% of their total annual operational costs. The aim of the present study was to measure and analyze the electric energy consumption of 4 AMS with different configurations: single box, central unit featuring a central vacuum system for 1 cow unit and for 2 cow units. The electrical consumption (daily consumption, daily consumption per cow milked, consumption per milking, and consumption per 100L of milk) of each AMS (milking unit + air compressor) was measured using 2 energy analyzers. The measurement period lasted 24h with a sampling frequency of 0.2Hz. The daily total energy consumption (milking unit + air compressor) ranged between 45.4 and 81.3 kWh; the consumption per cow milked ranged between 0.59 and 0.99 kWh; the consumption per milking ranged between 0.21 and 0.33 kWh; and the consumption per 100L of milk ranged between 1.80 to 2.44 kWh according to the different configurations and operational contexts considered. Results showed that AMS electric consumption was mainly conditioned by farm management rather than machine characteristics/architectures

Algorithms for the interpretation of continuous measurement of the slurry level in storage tanks

This paper describes a device for monitoring the slurry level in storage tanks. In particular, it describes the inference engine used within the StorEyes software. This software was developed by the Authors to interpret and manage data collected from measurements taken by ultrasonic or pressure sensors mounted on slurry tanks for continuous monitoring of the stored effluent level. The monitoring device consists of a data-logger that uses a GPRS device for the wireless transmission of data to a Farm Information System server, a buffer for the temporary storage of data in case of malfunction of the farm network, and a GPS receiver. The inference engine consists of a set of algorithms used to derive from raw measurements (usually in V) intelligible information about the loading/unloading events in storage facilities. The inference engine has been tested and calibrated through two years of acquisitions at two pilot farms with different slurry tank loading and unloading management systems

Design and testing of a GPS/GSM collar prototype to combat cattle rustling

Rustling is an age-old practice that was widespread in Italy until the first half of the 20th century. Today, incidents of cattle rustling are again being reported. However, the problem is not only found in Italy. It is also becoming a plague for ranchers in the US and is still rampant in East Africa. In Italy, the cattle rustling phenomena have usually been limited through the direct control of the herdsmen. Global positioning system (GPS) and geographic information system (GIS) combined technologies are increasingly applied for tracking and monitoring livestock with greater spatial and temporal resolution. However, so far, no case studies of the use of GPS technology to combat cattle rustling have been reported in the literature. The aim of this research was to develop a GPS/GSM (global system for mobile communication) collar, using commercial hardware and implementing a specific software [ARVAshepherd 1.0; ARVAtec Srl, Rescaldina (MI), Italy] to track animals' movements outside their grazing area and to signal when animals are straying outside virtual perimeters. A phase I study was conducted from January to June 2011 to build the GPS/GSM collar and to assess its performances in terms of GPS accuracy and precision, while a phase II study was conducted in July 2011 to test the GPS collar under real-life operating conditions. The static GPS positioning error achieved a circular error probable (50%) and horizontal 95% accuracy of 1.462 m and 4.501 m, respectively. This is comparable with values obtained by other authors in static tests of a commercial GPS collar for grazing studies. In field tests, the system was able to identify the incorrect position of the cattle and the warning messages were sent promptly to the farmer, continuing until the animals had been repositioned inside the fence, thus highlighting the potential of the GPS/GSM collar as an anti-theft system

Real-time dry matter content of corn silage by a microwave sensor

Daily dry matter (DM) intake in dairy cow is a central point to meet nutritional requirements and optimal performance, reducing the incidence of metabolic diseases. DM content of some forages, such as silages, can undergo huge variations during storing, affecting the total daily DM consumed. Reference laboratory method is time consuming and cannot be applied to daily changes in diet composition. Currently, new promising real-time technologies are available to monitor the DM content of feeds. The aim of the study was to test and calibrate a portable microwave sensor (MS) for DM content in corn silage samples. Twenty-two samples were collected from a corn silage front; sampling procedure was optimized to collect as much as DM content variability as possible within the samples. MS readings were performed with 3 different methods for each samples: 1) directly on the silage front, 2) with the MS over the collected sample and 3) with MS placed under the sample. After the first MS reading, a correspondent silage sample was obtained by a silage corer for readings 2 and 3 and the laboratory DM content assay. A simple regression analysis was performed (JMP, SAS Institute, Cary, NC, 2015) over obtained data. Results evidences as the best MS reading method is represented by the probe burdening on the sample (R2=0.75) with respect to the other methods. The obtained results outlined as, with a correct reading method, MS can be valuable tool to determine DM content of corn silage directly at farm level

Environmental assessment of individual and collective manure management systems

In intensive livestock area with large nutrient surplus collective management systems can be a suitable solution. However, the collective system should carefully evaluated for environmental sustainability to avoid cross effects. The aim of this study was to evaluate the environmental effects of the introduction of a collective treatment plant for energy production and nitrogen removal. For this purpose an assessment methodology, for individual farms and collective treatments plants, has been defined to estimate the emissions of the main pollutants to the air (CO2, CH4, N2O, NH3) and to the soil (N). The method devised has been assessed in a case study (a treatment plant collecting manure from 12 farms). The main effect of the introduction of the collective management system from the environmental point of view is a reduction of greenhouse gases emissions of 61% due to methane emission reduction and renewable energy production. Furthermore, it reduces the amount of nitrogen to be applied to land from 430 kg ha-1 to about 220 kg ha-1, decreases the emission of ammonia in the air by about 17% due to lower amount of nitrogen that is managed by farms in the storage and spreading operations