Combination of different methods for direct control of Vicia hirsuta in winter wheat

Combinations of three different direct methods for controlling Vicia hirsuta (kainite application, flame weeding and harrowing) were investigated in field experiments. They were based on different strategies at early growth stages of V. hirsuta and standardised harrowing at late growth stages. The highest efficacy of kainite application and flame weeding was achieved at the one leaf stage of V. hirsuta. Winter wheat regeneration from damage caused by both kainite and thermal control was satisfactory when treatments were applied at early growth stages (GS 23). Vicia hirsuta plants that survived kainite application or flame weeding were successfully controlled by repeated harrowing at later crop growth stages; crop growth was not affected. Seed production of V. hirsuta declined with increasing harrowing in all treatments; however the strongest and most reliable reduction was achieved when flame weeding had been previously applied. All combinations of direct measures reduced winter wheat grain-yield losses and enhanced thousand-grain weight more efficiently than the use of a single method only. The highest wheat-grain yield was gained after repeated harrowing (3 times) both with and without kainite application

Short-term effect of soil disturbance by mechanical weeding on plant available nutrients in an organic vs conventional rotations experiment

The question whether soil disturbance from mechanical weeding in organic systems affects nutrient release from organic matter in compost-amended soil was examined in a long-term organic-versus-conventional rotational cropping system experiment over three years. The experimental design included continuous snap beans, and a fully phased snap beans/fall rye crop rotation sequence. Treatments were combinations of yearly applied fertiliser (synthetic fertiliser, 1× compost, 3× compost) and weed control (herbicide, mechanical weeding). The 1× compost rate was calculated to deliver the equivalent of 50 kg N ha-1: equal to the rate ofN in the synthetic fertiliser treatments. Ion exchange membranes were buried for 24 hours following mechanical weeding in bean plots. Adsorbed ions were then eluted and quantified. Available ammonium-nitrogen was not affected byweeding treatment, but nitrate-nitrogen was consistently less in mechanically weeded plots than in plots treated with herbicide. Principal component analysis of NH4-N, NO3-N, P, K, Ca and Mg availabilities showed distinct groupings of treatments according to fertility treatment rather than weeding treatment. The effect of cropping sequence on available nutrients was pronounced (P ≤ 0.001) only in plots amended with synthetic fertilisers

Labour Demand and Labour-saving Options: A Case of Groundnut Crop in India

Groundnut is a labour-intensive crop, especially for operations like sowing, weeding, harvesting, and drying. But, of-late, due to timely unavailability of labour, many farmers are not able to exercise timely operations resulting in low yield realization. The present study conducted in two major groundnut-growing states, viz. Gujarat and Andhra Pradesh, has revealed that farmers employ more human labour in weeding and harvesting operations in groundnut than in other operations. The practise of manual decortication and stripping is followed by a larger number of farmers in Andhra Pradesh than in Gujarat, indicating less mechanization in the former. For weeding, though, the human labour-use in weedicide + bullock intercultivation + hand weeding technique is almost half of that of the bullock inter-cultivation + hand weeding, only 13 per cent of the farmers practise this labour-saving technique and hence this method should be disseminated in both the regions to reduce human-labour demand. In Andhra Pradesh, for all the operations in groundnut cultivation except harvesting, the cost as well as labour-use has been reduced substantially due to use of partial/complete mechanization methods. Hence, the necessary infrastructure (labour-saving machineries) should be created at the village or block level to reduce the human-labour demand.Labour demand, Groundnut cultivation, Labour-saving techniques, Agricultural and Food Policy, J23, J21,

Analysis and Definition of the close-to-crop Area in Relation to Robotic Weeding

The objective of this paper is to analyse and define the field conditions close to the crop plants of sugar beet (Beta vulgaris L.). The aim is to use this study for the choice and development of new physical weeding methods to target weeds at individual plant scale level. It was found that the close to crop area is like a ring structure, comprising an area between an inner- and outer-circle around the sugar beet seedling. Physical weeding should not be applied to the area within the inner circle. The radius of the inner circle increases with the appearance of young beet leaves during the growth season. It was also found, that no weeds were germinating within 1 cm around individual sugar beet seedlings. Therefore this distance should be added to the radius of the inner circle. The space between the inner and outer circle is termed the close to crop area where physical weeding should be applied. The size of this area is defined by the developmental stage of the sugar beet fibrous root system and foliage. Thus, the determination of the growth stage of individual crop plants is necessary before any physical weeding can take place in the close to crop area. Uprooting, cutting between stem and root or damage of main shoot can do the physical control of most weed species located in the close to crop area. However, the targeting of weeds from above and from different angels above ground is limited in the close to crop area. This is caused by the fact that sugar beet leaves do not leave much space between leaves and ground and that our own study indicate that 26.4% of sugar beet plants at the 4-6 leaf stage are covering the main shoot of weeds. The most problematic weeds are the species, which have their main shoot and leaves located close to ground level. These species can either be controlled by damage of the main shoot or with a combination of shallow surface cutting and burial. Discrimination between weed species is beneficial under certain circumstances. First, the efficiency of the physical control of individual weed species is depending on the timing. Secondly some weeds species do not have significant negative impact on the yield, but instead leaving these species uncontrolled could benefit to an increased bio-diversity and reduced time and energy input for a physical weeding process. This paper is contributing to the ongoing Danish research project Robotic Weeding

Hortibot: Feasibility study of a plant nursing robot performing weeding operations – part IV

Based on the development of a robotic tool carrier (Hortibot) equipped with weeding tools, a feasibility study was carried out to evaluate the viability of this innovative technology. The feasibility was demonstrated through a targeted evaluation adapted to the obtainable knowledge on the system performance in horticulture. A usage scenario was designed to set the implementation of the robotic system in a row crop of seeded bulb onions considering operational and functional constraints in organic crop, production. This usage scenario together with the technical specifications of the implemented system provided the basis for the feasibility analysis, including a comparison with a conventional weeding system. Preliminary results show that the automation of the weeding tasks within a row crop has the potential of significantly reducing the costs and still fulfill the operational requirements set forth. The potential benefits in terms of operational capabilities and economic viability have been quantified. Profitability gains ranging from 20 to 50% are achievable through targeted applications. In general, the analyses demonstrate the operational and economic feasibility of using small automated vehicles and targeted tools in specialized production settings

Weed management in organic echinacea (Echinacea purpurea) and lettuce (Lactuca sativa) production

Weed management is a major constraint in organic production. It can be expensive and time-consuming and severe crop yield losses may be incurred when weeds are not adequately controlled. Research on organic weed management (OWM) in herb and vegetable production is increasing internationally, although in Australia very little work has been done to assess current OWM knowledge among growers, and to test the efficacy and cost effectiveness of the weed management practices used by organic growers. The effect of hand weeding, tillage, hay mulch, pelletised paper mulch and an unweeded control treatment on weed growth, crop growth and cost effectiveness were evaluated in several field trials on the Northern Tablelands of New South Wales using lettuce (Lactuca sativa L.) and echinacea (Echinacea purpurea Moench. [L.]). Weed management in lettuce was cost-effectively achieved using cheaper weeding methods such as tillage. More expensive methods such as hand weeding and hay mulching controlled weeds well, but were less cost effective. For echinacea, cheaper in-crop weeding methods (e.g. tillage, unweeded control) had poor weed suppression and low crop yields, while the more expensive weeding methods, hand weeding and hay mulch, controlled weeds well and were cost effective. Paper mulch controlled weeds very well but, again, had lower yields and was therefore not cost effective. The results highlight several important advantages and disadvantages of currently used OWM methods in the field

Organic Farming Scenarios: Operational Analysis and Costs of implementing Innovative Technologies

The objective of this study has been to design a number of farm scenarios representing future plausible and internally consistent organic farming enterprises based on milk, pig, and plant production and use these farm scenarios as the basis for the generation of generalised knowledge on labour and machinery input and costs. Also, an impact analysis and feasibility study of introducing innovative technologies into the organic production system has been invoked. The labour demand for the production farms ranged from 61 to 253hha1 and from 194 to 396hLU1 (LU is livestock units) for work in the animal houses. Model validation results showed that farm managerial tasks amount to 14–19% of the total labour requirement. The impact of introducing new technologies and work methods related to organic farming was evaluated using two innovative examples of weed control: a weeding robot and an integrated system for band steaming. While these technologies increased the capital investment required, the labour demand was reduced by 83–85% in sugar beet and 60% in carrots, which would improve profitability by 72–85% if fully utilised. Profitability is reduced, if automation efforts result in insufficient weed removal compared to manual weeding. Specifically, the benefit gained by robotic weeding was sensitive to the weed intensity and the initial price of the equipment, but a weeding efficiency of under 25% is required to make it unprofitable. This approach demonstrates the feasibility of applying and testing operational models in organic farming systems in the continued evaluation and documentation of labour and machinery inputs

Growth and competition model for organic weed control

There is a more detailed Executive Summary at the top of the attached document, which is the final report for Defra Project OF0177. The project aimed to examine the organic extension of a simple mechanistically-based growth and competition model, calibrated to data originally gained from conventional vegetable production. Essentially the model simulation follows the growth of each crop and weed plant as they compete for space and light during and after canopy closure. The growth and competition model has been modified to simulate crop and weed growth of multiple cohorts so that the onset of crop weed competition can be predicted. This onset of competition marks the point when it is essential to remove weeds (i.e. critical weeding time); otherwise, there will be a penalty to crop yield. The model can be applied to determine the onset of competition between competing species (i.e. crop and weed). In organic crops this would be the time when physical removal of the weeds (either by means of mechanical or hand weeding methods) was essential to prevent yield loss. To test the ability of the model to identify critical weeding times, model predictions were compared with historical experimental data. The inputs to the model are starting plant weights and the numbers of individuals per unit area of the crop and weed species for each cohort at each day of the simulation. Solar radiation was used to drive the model. All the growth parameters were species specific and where a number of weed species are competing with the crop in a mixed population, then a general set of parameters representing the mean of a range of parameterised weed species were used. Repeatedly running the simulation with different starting inputs from a range of historical data sets indicated that the observed critical weeding time was described well by the model. To examine the applicability of the principle of the growth model to an organic cropping situation, the predicted optimum timing of weed removal simulated by the model was incorporated as a treatment into an existing organic carrot trial. The aim was to see whether the weeding time simulated by the model achieved comparable or better results than the weeding by the unaided judgement of the grower.The results demonstrated that there was certainly no disadvantage to using the model in that year to aid in the decision making process. A small-scale trial was made in year 3, incluing cabbage plus three previously unparameterised crops; broccoli, cauliflower and leeks. The crop parameters for cabbage were used to drive the cauliflower and broccoli simulations and onion parameters for leeks. Three treatments were; weeding once as recommended by advisors at HDRA, weeding once as predicted by the model and left weedy throughout to test the competitive level of the weed flora. Inputs into the model were solar radiation, crop transplant weights and numbers, and weed weights and numbers during the early weeks of crop growth. Adjustment of the model using the final crop weights was related to the different relative growth rates of the crops in organic soils, compared with the higher N levels in conventional soils from where the parameters had been originally derived. After recalibration, the model re-confirmed the mid-August onset of competition, but tended to over predict the degree of weed competition. The notable exception was the leek crop which was more sensitive to competition than its brassica counterparts and gave a good illustration of the potential power of the model. As part of the project several presentations have been made to growers during the final year, which have allowed a dialogue and awareness to develop highlighting the practical and scientific implications of the model

Seed mapping of sugar beet to guide weeding robots

Individual plant care in agriculture will lead to new opportunities in crop management. Not only the weeding operation is in focus here but it will be more in general for individual chemical or physical treatments of individual weed or crop plants. For the application of fertilizers and chemicals in small dose rates and accurately targeted advanced sensor information e.g. based on spectral responses can be used to consider the individual plant needs ('the speaking plant'). This will have a significant effect on the reduction of inputs and increase the general efficiency rates of agricultural means. The objective of this project was to provide high accuracy seed position mapping of a field of sugar beet to allow subsequent physical weeding as inter- and within-row treatments. By knowing where the seeds were placed the assumption was that the plants will show up close by. This information about where the individual plants are can be used to show where the crop rows are. Therefore, this can be used as an appropriate information for guiding tractors and/or implements. At least for steering operations for inter-row weeding this procedure can be sufficient. A high accurate, cm-level, RTK GPS, optical seed detectors and a data logging system were retrofitted on to a conventional sugar beet precision seeder to map the seeds as they were planted (Nørremark et al., 2003). The average error between the seed map and the actual plant map was between 16 mm and 43 mm depending on vehicle speed and seed spacing (Griepentrog et al., 2003). Both parameters influenced the plant position estimates significantly. The seed spacing was particularly important because of its influence on the potential of seed displacements in the furrow after passing the seed detecting sensors. The results showed that the overall accuracy of the estimated plant positions were acceptable for the guidance of vehicles and implements for weeding purposes as well as for individual plant treatments. This research is contributing to the ongoing Danish research project Robotic Weeding as a cooperative research project of The Royal Veterinary and Agricultural University (KVL), Frederiksberg and the Danish Institute of Agricultural Sciences (DIAS), Horsens

Hop Weed Management Trial

As the acreage of hops continues to grow in the northeast, there is increasing need for regionally specific agronomic information. The majority of hop production and research is conducted in the Pacific Northwest, a region that has a much drier climate than our own. The University of Vermont (UVM) has carried out a number of trials to build relevant experience on small scale hop production in our wet and cool climate. The results and observations from our hops research can be found on the UVM Extension Northwest Crops and Soils website: www.uvm.edu/extension/cropsoil/hops. As for any perennial crop, managing weeds can require significant time and resources. Growers are looking for weed management methods that are effective, quick, and affordable. There are few herbicides labeled for use in hop production for VT and the region. Hence, growers are looking for alternative strategies to control weeds in hops. The main methods of control for weeds in the UVM hop yard have been hand weeding and mulch applications. While relatively effective, hand weeding has taken as much as 200 cumulative hours of labor per acre per year. In 2015, four alternative weed management methods were compared in the UVM hop yard including steam weeding, mulching, tilling, and applying a certified organic citrus-based herbicide