Understanding the barriers to the implementation of precision agriculture in the central region

There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics

The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

Drivers of change in animal protein production systems: changes from 'traditional' to 'modern' beef cattle production systems in Brazil

Until 1990, beef cattle production in Brazil was recognized as an enterprise of low investment, low cost of production, as well as an extensive production system that used large land areas to be economically feasible. The situation changed for the Brazilian beef market when the economy stabilized in 1994 and all sectors involved in the beef supply chain were able to predict their associated costs and profits. During the same period, purchasing power of the Brazilian population grew, and as a consequence, consumers began to demand higher quality beef products. This new scenario in the late 1990s and early 2000s has led to more intensive beef production systems in Brazil as well as the need for a greater understanding of how technologies might be applied. As consequence of this evolution, in the last five years, a necessity to increase beef production has occurred. The quality of Brazilian beef has improved compared with beef produced 15 years ago, but continued improvements are needed to achieve excellence in terms of large-scale production of high quality beef, be sustainable over a long period of time, and increase our contribution to global food security.

Ecological intensification of cereal production systems: Yield potential, soil quality, and precision agriculture

Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70–80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.

Forage legumes for energy-efficient animal production : proceedings of a trilateral workshop held in Palmerston North, New Zealand, April 30-May 4, 1984 /

Item 26-A-1

Animal production potential of some new Leucaena accessions in the Markham valley, Papua New Guinea

Signal grass pastures were oversown with four Leucaena spp. planted in hedgerows and evaluated for their agronomic productivity and ability to support steer liveweight gains. Each Leucaena sp. (L. leucocephala, L. pallida, L colli. nst. i., L. trichandra) was planted as seedlings into two I ha paddocks in rows 5 m apart, with I m spacing between trees. Cattle were rotationally grazed on the 2 replicates of each species, as well as on two I ha paddocks of a signal grass on y (Brachiaria decumbens) control, over a 243-day period at a stocking rate of 3 steers/ha. Mean presentation yield and herbage allowance of the Leucaena accessions over the grazing period were highest for L pallida (1100 kg/ha and 0.8 kg DM/kg LW, respectively), followed by L. leucocephala (700 kg/ha and 0.5 kg DM/kg LW), L. collinsii (700 kg/ha and 0.4 kg DM/kg LW) and L. trichandra (300 kg/ha and 0.2 kg DM/kg LW). Despite only moderate presentation yields and herbage allowances, steers grazing L. leucocephala and L. collinsii accessions produced the highest mean liveweight gains (LWG) of 0. and 0.56 kg/hd/d, respectively. While L. pallida produced the highest DM yields, it supported the lowest LWG of 0.36 kg/hd/d. The mean LWGs of steers grazing L. trichandra and the control (grass only) treatments were similar at 0.48 kg/ hd/d. The possible reasons for the differences in steer performance on the different Leucaena accessions are discussed.