Enhancing the value of field experimentation through whole-of-block designs

Precision agriculture (PA) offers opportunities for the development of new approaches to on-farm experimentation to assist farmers with site-specific management decisions. Traditional agricultural experiments are usually implemented in fields with the least possible soil heterogeneity under the assumption that responses to inputs and inherent variation of the soil are additive components of yield variation. However, because the soil in typical fields is not homogeneous, PA has much to offer. Farmers faced with variable conditions need to optimize their management to the variation over space and time on their farm, a problem that is not solved by conventional approaches to experimentation. New designs for on-farm experiments were developed in the 1990s for cereal production in which the whole field was used for the experiment rather than small plots. We explore the extension of this type of experiment to a vineyard in the Clare Valley of South Australia aiming to evaluate options to increase grape yield and vine vigour. Manually sampled indices of vine performance measured on georeferenced ‘target’ grapevines were analysed geostatistically. The major advantage of such an approach is that the spatial variation in response to experimental treatments can be examined. Linear models of coregionalization, pseudo cross-variograms and standardized ordinary cokriging are used to map treatment responses over the experimental area and also the differences between them. The results indicate that both treatment responses and the significance of differences between them are spatially variable. Thus, we conclude that whole-of-block on-farm trials are useful in vineyards.     

Spatial econometric analysis of a field-scale site-specific nitrogen fertilizer experiment on wheat (Triticum aestuvum L.) yield and quality

Knowledge of site-specific response may help farmers to tailor their management decisions with the help of precision farming technologies. However, farmers often have only a vague idea of the economic potential for site-specific management of their fields, which is important for investment decisions on precision farming technologies. This study presents an on-farm experimental approach to identify the economic potential of site-specific fertilization strategies at low costs. A strip trial with winter wheat (Triticum aestivum, L.) was established with precision farming technologies. Twelve different nitrogen fertilizer rates split in two applications were applied to 30 plots over a total strip length of 1.5 km. Geo-referenced yield was recorded with the harvester. Furthermore, electrical conductivity of the soil was measured and grain quality was surveyed with hand selected samples. With the help of advanced spatial statistical methods, within-field site-specific response was modeled with sufficient accuracy at comparably low costs. Electrical conductivity of the soil, elevation above sea level, and derivates of a digital elevation model were used as covariates to identify a possible economic potential for site-specific fertilization. Yield and protein response was best predicted with spatially adjusted regression models with site-characteristics or their interaction with management variables. Protein content was essential for achieving best economic results. The economic potential for site-specific fertilization strategies for the analyzed field was below 2 €/ha. However, the approach to identify the potential may be transferred to other locations with greater potential for site-specific farming.     

Identifying the challenges of promoting ecological weed management (EWM) in organic agroecosystems through the lens of behavioral decision making

Ecological weed management (EWM) is a scientifically established management approach that uses ecological patterns to reduce weed seedbanks. Such an approach can save organic farmers time and labor costs and reduce the need for repeated cultivation practices that may pose risks to soil and water quality. However, adoption of effective EWM in the organic farm community is perceived to be poor. In addition, communication and collaboration between the scientific community, extension services, and the organic farming community in the US is historically weak. In order to uncover the most persistent obstacles to promoting effective weed management in organic agroecosystems, we use the mental models approach to generate an expert model based on interviews with experts (e.g., weed scientists, weed ecologists, and extension personnel) and theories from the behavioral sciences. The expert model provides two main insights: (1) EWM is a complex strategy that may cause farmers to use heuristics in management decisions and (2) the long-term benefits of EWM, rather than the risks, need to be emphasized in communication with and outreach to organic farmers. The basis for new research topics and outreach material that incorporates these insights from the expert model are discussed. We briefly explain how the expert model is an incomplete picture of on-farm practices, but provides the basis for the second step of our mental models research, the farmer interviews and farmer decision model development.     

Geostatistical analysis of fruit yield and detachment force in coffee

The aim of this study was to use geostatistical analysis to evaluate the spatial variation in the detachment force of coffee fruit and coffee yield by variograms and kriging for precision agriculture. This study was conducted at Brej?o farm, Três Pontas, Minas Gerais, Brazil. The detachment force of green and mature coffee fruit was measured with a prototype dynamometer and georeferenced. The yield data were obtained from manual harvesting and were georeferenced. The data were evaluated by variograms estimated by residual maximum likelihood (REML), which provided a satisfactory approach for modeling all the variables with a small sample size. Spherical and exponential models were fitted, the first provided the better fit to mature fruit detachment force and the latter provided the better fit to coffee yield and green fruit detachment force. They were used to describe the structure and magnitude of spatial variation in the variables studied. Kriged estimates were obtained with the best fitting variogram models and mapped. The statistical and geostatistical analyses enabled us to characterize the spatial variation of the detachment force of green and mature coffee fruit and coffee yield and to visualize the spatial relations among these variables. The precision agriculture techniques used in this paper to collect, map and analyze the variables studied will help coffee farmers to manage their fields. Maps of coffee yield will enable farmers to apply nutrients site-specifically and manage harvesting either manually or mechanically. In addition, maps of detachment force of coffee fruit can enable farmers to harvest coffee selectively by choosing the appropriate places and the right time to start. This will improve the quality of the final product and also increase profits.     

Assessment of yield monitoring equipment for dry matter and yield of corn silage and alfalfa/grass

Whole farm evaluations have shown that accurate yield data are difficult to collect for alfalfa (Medicago sativa L.) and grass mixtures and corn (Zea mays L.) silage fields. Additionally, on-farm research, a recommended tool for adaptive management, is hindered by lack of practical ways to collect yield data. Recently, forage yield monitors have become available on self-propelled forage harvesters (SPFHs), but precision and accuracy of this technology are unknown. The objective of this project was to evaluate accuracy of yield and moisture sensing components of forage yield monitors for use in alfalfa/grass and corn silage. Moisture content, mass flow weights, total area harvested and total dry yield per hectare were measured on 11 farms in 2013; forage samples were collected for truck loads, analyzed for dry matter content, and compared to monitor-registered dry matter. Truck weights were used to compare monitor-derived yield to actual yield on two farms for alfalfa/grass and three farms for corn silage. Moisture sensors estimated crop moisture content within 3.7 % DM for alfalfa/grass and 3.0 % DM for corn silage of the oven dry value. Flow sensors estimated alfalfa/grass yield to ±0.5 and ±1.1 Mg DM/ha for corn silage. When calibrations are done regularly, forage yield monitors can provide an accurate and precise measure of dry yield for adaptive management. It is concluded that this technology can be used when plots are large and large treatment-driven yield differences are expected.     

Weed control practices on Costa Rican coffee farms: is herbicide use necessary for small-scale producers?

This paper presents research conducted during two coffee farming seasons in Costa Rica. The study examined coffee farmers?? weed management practices and is presented in the form of a case study of small-scale farmers?? use of labor and herbicides in weed management practices. Over 200 structured interviews were conducted with coffee farmers concerning their use of hired labor and family labor, weed management activities, support services, and expectations about the future of their coffee production. ANOVA and regression analyses describe the relationships between farm size, labor, and herbicide use, and three farm types (i.e., conventional, semi-conventional, and organic). Based on findings regarding the amount of labor used to manually control weeds on different types of farms (large farms, small conventional, semi-conventional, and organic farms) I am able to challenge small conventional farmers?? perceived need for herbicide use. Semi-structured interviews of coffee farmers and extension workers further revealed a dominant role played by agro-chemical companies in assisting farmers with production problems, and documented a high transaction cost for information provided from elsewhere. Chemical companies hire extension workers to visit farmers at their farms, free of charge, to offer recommendations on how to treat different pest problems, while government and cooperative extension agents charge for the service. There is a need to increase the amount of resources available to the National Coffee Institute to fund one-on-one farmer support services in order to balance the influence of agro-chemical company representatives and allow farmers to make better decisions regarding weed management.     

Participatory research in integrated pest management: Lessons from the IPM CRSP

Integrated pest management has emerged as an important means of managing agricultural pests. Since the mid-1980s, the emphasis in IPM has shifted toward biologically-intensive and participatory research and extension approaches. Finding better means for solving pest problems is high on the agenda for most farmers, and farmers often have significant pest management knowledge and interest in IPM experimentation. This paper describes an approach to participatory IPM research that is being implemented by the IPM Collaborative Research Support Program (IPM CSRP). The approach emphasizes on-farm research with an extrapolation domain beyond the single farm, and in some cases beyond the local region or country. It considers many factors beyond the farm and research station that influence the generation and adoption of IPM technologies and strategies. It emphasizes linkages among farmers, scientists, consumers, bankers, marketers/processors, and policy makers in IPM research priority setting, conduct, and evaluation. The interdisciplinary approach described in the paper is illustrated with a case study from the Philippines. Lessons and conclusions draw on its recent application in other sites as well.     

Just small potatoes (and ulluco)? The use of seed-size variation in “native commercialized” agriculture and agrobiodiversity conservation among Peruvian farmers

Farmers of the Peruvian Andesmake use of seed-size variation as a source offlexibility in the production of ``nativecommercial' farmer varieties of Andeanpotatoes and ulluco. In a case study of easternCuzco, the use of varied sizes of seed tubers isfound to underpin versatile farm strategiessuited to partial commercialization (combinedwith on-farm consumption and the next season'sseed). Use of seed-size variation also providesadaptation to diverse soil-moistureenvironments. The importance and widespread useof seed-size variation among farmers isdemonstrated in the emphasis and consistency oflinguistic expressions about this trait. Smalland small-medium seed is typically sown in thecommunity's ``Hill' unit of sub-humid,upper-elevation agriculture. Seed tubers ofmedium-size and larger are needed fordrought-stressed locales in lower-elevationlandscape units. Farm-level preferences for theseed-size of tubers also suggest potentialrelations to resource endowments of farmhouseholds and gender-related management,although these tendencies were notstatistically significant in the study. Anintra-varietal, landscape-environmentalperspective on seed-size management, whichincludes an emphasis on within-fieldversatility, helps to strengthen the researchsupport of local seed production in policiesand programs aiming for in situagrobiodiversity conservation, marketingcapacity, and food security.     

Precision farming uses typology in arable crop-oriented farms in northern France

The adoption of precision farming techniques (PFTs) has been widely studied targeting specific PFT or farming systems along with the potential benefits of these PFTs in terms of yield or input use. However, few studies have examined how PFTs are adopted and used at the farm level. In this study a preliminary investigation was made of on-farm PFT uses in the Oise region (northern France). Three main PFTs were identified in the area: Global Navigation Satellite Systems (GNSS) guidance, section control, and variable rate (VR) application. For each farm, the use of every PFT was defined by the technical characteristics of the equipment, the field operation(s) concerned, the targeted crop(s), the aim of the use, the PFT adoption drivers, and the perceived impacts by the farmers. These different variables were combined into a typology of PFT uses. The results show that most of the farms combined GNSS guidance for all technical operations and section control, whereas VR application was less common. Section control was largely used by farmers for liquid fertilizers and phytochemical spraying. The typology shows three to five types of use for each PFT, which differ in terms of technique adoption drivers, e.g. reducing on-farm work or adaptation to field morphology. According to literature, economic impacts were found to be the most frequent, however farmers seemed unable to quantify them. Social impacts such as reduced work time and fatigue were also frequent and are becoming the main motivation for using PFT on farms studied. Further research is needed to assess the use trajectories of PFT along with the motivations of each PFT use.

     

Farm management optimization using chance constrained programming method

This paper presents a stochastic optimization model to determine the optimal number of acres of hay a farm should harvest for their own horses’ consumption, as well as how much hay to purchase and sell to maximize the total profit of the farm. This research is motivated by horse farmers who must make yearly decisions concerning the management of feeding horses. These decisions are affected by the cost to grow their own hay, the cost to buy hay, the cost associated with selling hay, and the stochastic nature of crop yield due to different weather conditions. The uncertainty of weather conditions is included in the mathematical model by including random variables in the model constraints. Optimal policies are obtained for a real world case study provided by a Kentucky horse farmer by applying chance constrained programming method. A sensitivity analysis is performed to show the effectiveness of the approach.     

Predicting Cotton Lint Yield Maps from Aerial Photographs

It is generally accepted that aerial images of growing crops provide spatial and temporal information about crop growth conditions and may even be indicative of crop yield. The focus of this study was to develop a straightforward technique for creating predictive cotton yield maps from aerial images. A total of ten fields in southern Georgia, USA, were studied during three growing seasons. Conventional (true color) aerial photographs of the fields were acquired during the growing season in two to four week intervals. The aerial photos were then digitized and analyzed using an unsupervised classification function of image analysis software. During harvest, conventional yield maps were created for each of the fields using a cotton picker mounted yield monitor. Classified images and yield maps were compared quantitatively and qualitatively. A pixel by pixel comparison of the classified images and yield maps showed that spatial agreement between the two gradually increased in the weeks after planting, maintained spatial agreement of between 40% and 60% during weeks eight to fourteen, and then gradually declined again. The highest spatial agreement between a classified image and a yield map was 78%. The highest average agreement was 52% and occurred 9.9 weeks after planting. The visual similarity between the classified images and the yield maps were striking. In all cases, the dates with the best visual agreement occurred between eight and ten weeks after planting, and generally, during July for southern Georgia. This method offers great potential for offering cotton farmers early-season maps that predict the spatial distribution of yield. Although these maps can not provide magnitudes, they clearly show the resulting yield patterns. With inherent knowledge of past performance, farmers can use this information to allocate resources, address crop growth problems, and, perhaps, improve the profitability of their farm operation. These maps are well suited to be offered to farmers as a service by a crop consultant or a cooperative.     

交易方式对养猪场户生猪质量安全控制行为的影响

基于北京市、辽宁省和河北省养猪场户的调查数据,实证分析了交易方式对养猪场户的质量安全控制行为的影响。研究发现,由于生猪质量属性和安全属性的经济学内涵不同,交易方式对养猪场户的质量安全控制行为的影响具有差异:相对于市场交易,与屠宰加工企业签订契约对于养猪场户在质量控制和安全控制的多个方面都有显著改善作用,而与生猪收购商签订契约有助于养猪场户的质量控制提升,但不利于其安全控制。另外,养猪场户的个体特征、生产特征、外部环境、预期回报和认知水平都对养猪场户的质量安全控制行为产生了影响。据此提出注重政府监管与市场治理协同,加强对生猪购销商监管,提高养猪场户组织程度等建议。     

The multi-dimensional nature of environmental attitudes among farmers in Indiana: implications for conservation adoption

Attempts to understand farmer conservation behavior based on quantitative socio-demographic, attitude, and awareness variables have been largely inconclusive. In order to understand fully how farmers are making conservation decisions, 32 in-depth interviews were conducted in the Eagle Creek watershed in central Indiana. Coding for environmental attitudes and practice adoption revealed several dominant themes, representing multi-dimensional aspects of environmental attitudes. Farmers who were motivated by off-farm environmental benefits and those who identified responsibilities to others (stewardship) were most likely to adopt conservation practices. Those farmers who focused on the farm as business and were most concerned about profitability were less likely to adopt practices. The notion of environmental stewardship in particular was found to be much more complex than the way it is traditionally measured in quantitative studies. The interplay between on-farm and off-farm benefits to practice adoption is an issue that quantitative studies largely do not address. This study seeks to increase understanding of farmers’ environmental attitudes and the connections to conservation behavior.     

Adoption of new technologies by smallholder farmers: the contributions of extension,research institutes,cooperatives, and access to cash for improving tef production in Ethiopia

Agricultural intensification and extensification are standard responses to ecological and economic vulnerability among smallholder communities. Climate change has exacerbated this vulnerability and thrown the complexity of and critical need for managing a healthy natural resource base while increasing on-farm productivity into sharp light. Sustainable intensification is one of many mechanisms for accomplishing this balancing act. This study examines the adoption of sustainable intensification practices, namely input packages focused on tef row planting—designed to boost yield and promote more efficient use of inputs. This study utilized a mix methods approach to survey 115 smallholder farmers in the South Wollo zone of the Amhara region in Ethiopia. This study found that cash and capital, more so than contact with the AIS, influenced farmers’ decisions to adopt row planting input packages. Khat production was an important source of cash for inputs and was more likely to be available to farmers with irrigation schemes. Long-term, farmers who cultivate khat may not successfully engage in SI, as khat replaces traditional food crop production in the region. Yet, for farmers who do not grow khat, long-term investment in SI practices is unlikely unless access to affordable credit options is improved.     

Can public GAP standards reduce agricultural pesticide use? The case of fruit and vegetable farming in northern Thailand

In response to the chronic overuse and misuse of pesticides in agriculture, governments in Southeast Asia have sought to improve food safety by introducing public standards of good agricultural practices (GAP). Using quantitative farm-level data from an intensive horticultural production system in northern Thailand, we test if fruit and vegetable producers who follow the public GAP standard use fewer and less hazardous pesticides than producers who do not adhere to the standard. The results show that this is not the case. By drawing on qualitative data from expert interviews and an action research project with local litchi (“lychee”) producers we explain the underlying reasons for the absence of significant differences. The qualitative evidence points at poor implementation of farm auditing related to a program expansion that was too rapid, at a lack of understanding among farmers about the logic of the control points in the standard, and at a lack of alternatives given to farmers to manage their pest problems. We argue that by focusing on the testing of farm produce for pesticide residues, the public GAP program is paying too much attention to the consequences rather than the root cause of the pesticide problem; it needs to balance this by making a greater effort to change on-farm practices.     

Grain Yield Mapping: Yield Sensing,Yield Reconstruction,and Errors

Research findings are reviewed focusing on yield sensing methods, yield reconstruction, mapping, and errors. Yield sensing methods were explained and yield mapping process was briefly introduced. Grain flow through different combines was explained and the effects of combine dynamics on yield measurement accuracy were discussed. Other errors caused by various sensors that are utilized by a yield monitor were included. It was concluded that with proper installation, calibration, and operation of yield monitors, sufficient accuracy can be achieved in yield measurements to make site-specific decisions. Nevertheless, attention must be paid when interpreting yield maps since yield measurement accuracy can vary depending upon the measurement principle, combine grain flow model, size of management area chosen, and the operator's capabilities and carefulness in following instructions to obtain the best accuracy possible under varying field operating conditions. Some of the errors can be filtered out by careful analysis of the raw yield (or flow rate) data provided by yield monitors. Researchers have focused on crop flow models to improve yield reconstruction process. A yield reconstruction algorithm that effectively handles non-linear combine dynamics has not been developed by researchers yet. More efforts towards yield reconstruction should be encouraged.     

Investigating geostatistical methods to model within-field yield variability of cranberries for potential management zones

Cranberry harvesting methods give only one yield value per field making characterization of within-field variation, the usual first step in precision farming, difficult. Time-consuming berry count yield and fruit rot estimations are the best “ground truth” indication of yield variation within fields. Correlations and coincidence of binary classifications based on less expensive methods such as enhanced vegetation index (EVI) from imagery, and area to point (AtoP) kriging of useable, poor quality and trash yields were compared with this “ground truth”. In general AtoP kriged values gave higher correlations and kappa statistic values with berry counts and fruit rot than EVI. Geostatistical disaggregation of per field yield totals using AtoP kriging with EVI as an external drift (AtoP^KED) was also investigated. Factorial kriging was used to separate the several scales of variation in “ground truth” and EVI data and determine which ones were most spatially coherent/manageable and which related best to the AtoP kriged data. The spatial trend component of pre-harvest berry counts and AtoP kriging of yields both gave a good initial definition of spatially coherent, relatively permanent management zones. They were related to topography and depth of water table in the soil which are key factors governing cranberry yield. AtoP kriging or AtoP^KED are recommended for defining management zones as they are less expensive than berry counts. The value of AtoP kriging to precision farmers for other crops to map soils at the farm scale with some imagery and just one bulked soil sample per field or use nutrient levels associated with each polygon of traditional soil survey maps is discussed in the conclusions.     

Evaluation of an analytical method to identify determinants of rice yield components and protein content

Modern information technologies have facilitated the collection of data to assess various aspects of rice production such as yield, quality, soil properties and growth conditions. Currently, farmers can identify any variation of these indicators within a field, between fields or with other farmers. However, a comprehensive analytical method to identify the determinants of variability has not been developed, and the data collected are not efficiently utilized to diagnose and improve the production skills of farmers. Our study focused on the development of an analytical method that can identify the determinants of rice yield and quality. The analytical method used applied cluster analysis (Ward method) to assess the data from 82 paddy fields where rice is produced in various environments and with various management styles. Initially, the 82 paddy fields were classified into 11 clusters based on five indicators of yield components and rice quality; number of panicles, number of spikelets, percentage of ripened grains, 1000-grain weight (GW) and protein content of brown rice. Then, 9 of 11 clusters (two clusters were excluded due to insufficient data to form a cluster) were divided into four groups based on yield capacity. As a result, common characteristics of fertilizer application, meteorological environment and growth conditions were extracted from each cluster. Furthermore, determinants of yield components and protein content were efficiently identified based on the common characteristics extracted.