Interpolation of Spatial Surfaces and Inferring Subsurface Transitions Using Electrical Conductivity

Precision agriculture techniques are becoming more popular within the agriculture community as producers demand more return from an ever-decreasing amount of farmland. Increased environmental regulations are forcing farmers to reduce the input of fertilizers and agrochemicals on their crops. Innovative techniques in precision agriculture are enhancing traditional decision-making processes by offering multiple layers of data for a production field. It is difficult to determine the complex interactions that exist between factors affecting crop growth and the resultant management decisions. Strategies in precision agriculture attempt to modify customary practices in order to address the known variability of field conditions. This case study evaluated some of the tools used to create spatial data maps and the relationship of those maps to various soil properties. Electromagnetic induction (EMI) and ground-penetrating radar (GPR) were used to examine the similarities and differences among spatial and temporal variations of soil water content, soil texture, and bulk soil electrical conductivity (ECa) on a large research watershed in southwestern Tennessee. A protocol was developed that identifies spatial variations in ECa patterns using geographical information system (GIS) maps. Soil cores were collected in areas of contrasting conductivity, which were identified by temporal ECa maps. Repeated spatial measurements of ECa, starting near field capacity and then progressing through the draining and drying process, supplied visually shifting patterns that correspond to dynamic soil moisture variations and subsurface morphology transitions. iv After several seasons of acquiring data for other studies, it was noted that spatial ECa patterns remained somewhat similar across data gathering events, shifting only in relative amplitude in relation to seasonal moisture levels. The overall ECa patterns remained somewhat similar, regardless of field moisture conditions. Soil morphology was considered constant over the data acquisition period, with subsurface moisture variations being the major influence in differing ECa maps during the same period. Follow-up soil coring analysis supported this assumption in this case study. The interpolation of spatial ECa maps creates a continuous surface that contains values at unsampled locations. Inverse distance weighted (IDW), ordinary kriging (OK), and radial basis function (RBF) were examined as potential interpolation algorithms. Data were gathered to investigate the influences of short-term conductivity shifts over the data collection period, as well as from travel route patterns and instrument orientation. Using root-mean-squared error (RMSE) to quantify the transformation accuracy of ECa maps, a data collection method and an appropriate geostatistical model were determined for this particular case study. Analysis showed that a bidirectional travel path produced the highest quality map, as transformation inaccuracies were reduced when measurements were obtained in a manner by which all measurements were temporally contiguous. A skilled application of ordinary kriging (OK) also increased map quality in comparison to the inverse distance weighted (IDW) and radial basis function (RBF) interpolation methods. Due to variability in our data, we are not able to recommend the use of a single interpolation algorithm for all data gathering scenarios

Green Technologies for a More Sustainable Agriculture

For U.S. agriculture to continue along a sustainable path of economic development, further production increases must be generated by technologies that are both profitable and more environmentally benign. In this context, we assess the role of these green or sustainable technologies in steering agriculture along a more sustainable path. However, the lack of markets for the environmental attributes associated with green technologies can limit their development. In addition, simply making a technology available does not mean it will be adopted. Experience with green technologies such as conservation tillage, integrated pest management, enhanced nutrient management, and precision agriculture demonstrates that even when technologies are profitable, barriers to adopting new practices can limit their effectiveness.sustainable agriculture, natural capital, nonrenewable resources, renewable resources, environmental services, green technology, integrated pest management, conservation tillage, enhanced nutrient management, precision agriculture, Environmental Economics and Policy, Farm Management,

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Algorithm Development of a Multi-Section Crop Detection System for a Corn Head

Over the next several decades the need for grain-based commodities will increase, due mostly to the demand for grain in developing countries and grain-based biofuels. To meet the increase in demand additional grain-based commodities will come from two likely sources: current land used for production and land yet to be developed. Increased spatial resolution of crop production is one way producers can grow more crops without more land development. If farmland productivity can be monitored on a smaller scale, producers can begin to implement better site-specific management decision at a higher resolution, such as variable-rate nitrogen application. The development of high resolution yield mapping techniques would provide producers the ability to evaluate if additional grain could be produced. Currently, yield mapping technology provides an average yield value for a discrete harvested area. Average yield values are the summation of grain harvested by a number of row units across a corn-head. The harvested area is a function of the number of row units on a corn-head. The primary goal of this research was to develop an ear detection system that could predict the number of ears that entered individual row units. By generating ear count prediction for individual row units, harvested grain could be spatially allocated across multiple section of the corn-head to produce higher resolution yield maps

Evaluation methodology for Post-facto assessment of watershed development project

Not AvailableWatershed Development Program that had been implemented in India since the 5th Five Year plan (FYP) (1974-79), has been the accepted strategy for agricultural development in rainfed regions in India. To assess and evaluate the impact of watershed development projects on agricultural sustainability in rainfed regions, a study was undertaken in four treated and four untreated micro-watersheds in the Telangana region of Andhra Pradesh falling under hot and moist semi-arid climate in Peninsular India. In view of the divergent conclusions published based on earlier impact studies on several watersheds, it was deemed fit to undertake the study of a few treated watersheds in this region to understand the critical issues that determine the sustainability of watershed projects. Selected micro-watersheds were located in four villages in the districts of Rangareddy and Nalgonda in Andhra Pradesh. The study used tools of Geomatics – GIS (Geographical Information System), remote sensing and DGPS (Differential Global Positioning system) along with conventional methods like soil survey and analysis, PRA (Participatory Rural Appraisal) and socio-economic survey, etc. to assess and evaluate sustainability of Watershed Development Programme (WDP). In all, fiftyone sustainability indicators (SI) were constructed to assess the impact of WDP and a methodology was developed to enable a quantitative evaluation of various aspects of sustainability of agricultural production system, viz., agricultural productivity, economic viability, livelihood security, environmental protection and social acceptability. This publication covers a detailed account of methodology and results of case studies. Application of GIS and remote sensing techniques has facilitated analysis of interand intra- temporal variations in the impact of WDP across the selected watersheds. The study was carried out under the ICAR National Fellow scheme awarded to the first author in February 2005. Authors strongly feel that the evaluation methodology described in this publication would be highly useful to the watershed project implementation agencies for development of watersheds and undertaking corrective measures as and when required. Further, funding and evaluating agencies will also find this book very useful to undertake an objective evaluation of ongoing and concluding projects.Not Availabl

Nonlinear parametric modelling to study how soil properties affect crop yields and NDVI

This paper explores the use of a novel nonlinear parametric modelling technique based on a Volterra Non-linear Regressive with eXogenous inputs (VNRX) method to quantify the individual, interaction and overall contributions of six soil properties on crop yield and normalised difference vegetation index (NDVI). The proposed technique has been applied on high sampling resolution data of soil total nitrogen (TN) in %, total carbon (TC) in %, potassium (K) in cmol kg−1, pH, phosphorous (P) in mg kg−1 and moisture content (MC) in %, collected with an on-line visible and near infrared (VIS-NIR) spectroscopy sensor from a 18 ha field in Bedfordshire, UK over 2013 (wheat) and 2015 (spring barley) cropping seasons. The on-line soil data were first subjected to a raster analysis to produce a common 5 m by 5 m grid, before they were used as inputs into the VNRX model, whereas crop yield and NDVI represented system outputs. Results revealed that the largest contributions commonly observed for both yield and NDVI were from K, P and TC. The highest sum of the error reduction ratio (SERR) of 48.59% was calculated with the VNRX model for NDVI, which was in line with the highest correlation coefficient (r) of 0.71 found between measured and predicted NDVI. However, on-line measured soil properties led to larger contributions to early measured NDVI than to a late measurement in the growing season. The performance of the VNRX model was better for NDVI than for yield, which was attributed to the exclusion of the influence of crop diseases, appearing at late growing stages. It was recommended to adopt the VNRX method for quantifying the contribution of on-line collected soil properties to crop NDVI and yield. However, it is important for future work to include additional soil properties and to account for other factors affecting crop growth and yield, to improve the performance of the VNRX model

Organizing historical agricultural data and identifying data integrity zones to assess agricultural data quality

As precision agriculture transitions into decision agriculture, data driven decision- making has become the focus of the industry and data quality will be increasingly important. Traditionally, yield data cleaning techniques have removed individual data points based on criteria primarily focused on the yield values. However, when these methods are used, the underlying causes of the errors are often overlooked and as a result, these techniques may fail to remove all of the inaccurate data or remove “good” data. As part of this research, an alternative to data cleaning was developed. Data integrity zones (DIZ) within each field were identified by looking at metadata which included data collected by the combine that reported the operating conditions of the machinery (i.e. travel speed, crop mass flow), data about the field environment (i.e. soil type, topography, weather), and data of field operations (e.g., field logs, as-applied maps). Ten years of historical data from the Southeast Purdue Agricultural Center (5 years of corn and 4 years of soybeans) and the Northeast Purdue Agricultural Center (1 year of corn) were used for analysis. Data in DIZ were isolated using buffers and the analysis of the reduced datasets was compared to the raw data. The amount of data that was removed depended on the amount of variation in the field, approximately 70% for the 14.5 acre SEPAC J4 field and 30% for the 25 acre NEPAC S13 field. Statistical comparisons of the data showed the mean yield estimate increased by an average of 22 bu/ac for corn and 3 bu/ac for soybeans when DIZ data was used compared to raw data. On average the standard deviation decreased by 24 bu/ac and 5 bu/ac for corn and soybeans, respectively, indicating that the data collected in these zones was more consistent and contained less noise and fewer errors. The average change in the standard error of the mean was 0.08 for corn and 0.09 for soybeans when the DIZ data was used. The temporal yield indices for each soil type zone showed that the yield responses were more stable when DIZ data was used for analysis instead of raw data. The estimates provided by these smaller, more accurate datasets are also more likely to be representative of the treatments that are being compared. The data collected in DIZ and the data collected outside of DIZ were compared for differences. The non-DIZ data contained much more variation in two key measurements that have been shown to affect data quality: combine travel speed (CV was 2.2x higher for corn non-DIZ data and 1.5x higher for soybean non-DIZ data) and crop mass flow rate (CV was 2.6x higher for corn non-DIZ data and 1.6x higher for soybean non-DIZ data). This alternative to data cleaning effectively removed errors and artifacts from yield data. When these reduced datasets are used to analyze historical yield data over time, they may provide a clearer picture of true yield effects; this will improve decisions on input and resource allocation, support wiser adoption of precision agricultural technologies, and refine future data collection

Paikkakohtainen säätö kasvintuotannossa

The aims of this work were to get answers to the following three questions: (1) What are the potentialities of coordinate-based field crop production? (2) What are the requirements for the method of attaching field crop information to a coordinate system? (3) What are the possible solutions? The work was focused on the effects of positioning quality. In PDC (Position Dependent Control) positioning is needed to target the inputs and to relate inputs and outputs accurately to each other. Systems analysis was used to accomplish a mathematical model of the position dependent control system. The model developed describes a system which consists of models for the positioning method and the target. An accuracy requirement of ±5 meters for N-fertilization was set with the developed model. The results from Keimola gave information on the variability of soil and wheat yield. Regressions for individual input variables and multiple regressions calculated for whole sample lines (á 50 m) were low (r2Koordinaattiin sidotussa peltoviljelyssä kaikki tuotannon suunnitteluun ja toteutukseen liittyvä tieto kohdistuu paikkakoordinaateilla rajattuihin alueisiin, tuotantopaikkoihin. Tutkimuksen tavoitteena oli saada vastaukset seuraaviin kysymyksiin: 1. Millainen potentiaalinen käyttö on koordinaattiin sidotulla peltoviljelyllä? 2. Mitä vaatimuksia koordinaattiin sidontaan käytetyn menetelmän tulee täyttää? 3. Mitä mahdollisia ratkaisumalleja voidaan käyttää? Pellolla kasvuolosuhteet vaihtelevat lyhyilläkin etäisyyksillä. Keimolassa tehdyn kenttäkokeen perusteella normaalissa, näennäisesti hyvin tasaisessa kevätvehnäkasvustossa sato vaihteli voimakkaasti. Mittauksessa käytettiin 0,25 x 0,25 metrin näytealaa, jolta sato kerättiin kokonaisnäytteinä. Samasta kohdasta otettiin viljavuusnäytteet. Satonäytteitä otettiin kahdesta 50 metrin mittaisesta linjasta 0,5 metrin välein, ts. näytteeseen tuli puolet linjan vehnästä. Saatu aineisto osoittautui erittäin vaihtelevaksi. Koordinaattiin sitomisen vaikutusta simuloitiin valiten Keimolasta saadusta aineistosta alueita, joiden aineistoille laskettiin paikalliset matemaattiset mallit. Yhtenä koejäsenenä oli satotasoon perustuva alueen valinta. Selvästi parhaat ennusteet saatiin kuitenkin matkaan sidotulla alueen valinnalla. Tästä voitiin päätellä, että satotasot eivät ennusta maaperän ominaisuuksia vaan päinvastoin: tietty paikka maassa tuottaa sille ominaisen sadon. Tutkimuksessa käytettiin matemaattisia malleja simuloitaessa erilaisten tuotantopanosten kohdentamistarkkuuden vaikutusta. Kohteena oleva alue pellolla, tuotantopaikka, mallinnettiin sadonmuodostuksen ja huuhtoutuman suhteen. Mallissa tuotantopaikkaan annettava käsittely kuvattiin vaikutuskuvioiden avulla, Paikannusvirheen ansiosta vaikutuskuvion kohdentamisessa esiintyy virheitä, joiden ansiosta tuotantopaikat saavat vääriä käsittelyn tasoja. Simuloinnissa selvitettiin erilaisten paikannusvirheiden vaikutusta tuotantopaikasta saatavaan sato- ja huuhtoumatulokseen. Tulosten perusteella saadaan maksimi paikannusvirheet eri tilanteissa. Paikannuslaitteet ovat keskeisessä asemassa koordinaattiin sidotussa viljelyssä, Paikannuslaitekokeissa käytettiin satelliittinavigointilaitteistoja. Vuonna 1990/1991 kokeissa oli geodeettinen GPS (Global Positioning System) laitteisto jossa käytettiin differentiaalilaskentaa jälkikäteen. Vuosina 1993 ja 1994 kokeissa olivat reaaliaikaiseen differentiaalikorjaukseen kykenevät laitteet. Laitteet testattiin tarkoitusta varten tarkasti mitatulla koeajoreitillä Viikissä. Lisäksi vuonna 1993 tehtiin maantie- ja kaupunkiajoja. Vuonna 1994 laitteistoa testattiin edellisten lisäksi käytännön kylvötyön yhteydessä. Tulosten mukaan DGPS (Differential Global Positioning System) on tarpeeksi tarkka koordinaattiin sidottuun viljelyyn. Paikannustarkkuus on normaaliolosuhteissa nykyisellä satelliittikonstellaatiolla parempi kuin vaatimuksena ollut ±5 metriä. Kirjallisuuden ja tutkimustulosten perusteella on selvää, että pellon vaihtelun hallinta ei ole mahdollista muutoin kuin siten, että peltoa viljellään paikkakoordinaattiin sidottuina tuotantopaikkoina. Viljelyyn liittyvät tiedot sidotaan paikkoihin ja työkoneita säädetään näihin kohteisiin yksilöllisesti tehdyn suunnitelman mukaisesti. Tekniikassa on tähän käyttökelpoisia ratkaisuja. Eräs toimiva ratkaisumalli on paikkatietojärjestelmä (GIS) yhdistettynä tiedonkeruuseen, laskentaan ja paikkakohtaiseen säätöön. DGPS satelliittinavigointi sopii tämän järjestelmän paikannusmenetelmäksi. Peltoviljelyssä esiintyviin eri paikannustehtäviin on saatavilla tarpeeksi tarkkoja GPS-laitteita. Paikkakohtainen säätö edellyttää normaalia huomattavasti joustavammin säädettäviä työkoneita. Lisäksi tarvitaan suunnitteluohjelmistoja, jotka käyttävät tuotantopaikkamalleja. Potentiaalisia laitteita ja menetelmiä on jo nyt olemassa kaikkiin paikkakohtaisen säädön osiin. Ongelmaksi muodostuukin niiden yhteenliittäminen toimivaksi järjestelmäksi, joka on myös taloudellisesti kestävällä pohjalla. Tämän jälkeenkin jäämme miettimään, miten tuotantopaikkoja tulisi käsitellä aikaansaadulla järjestelmällä. Kysymys voidaan muotoilla esimerkiksi seuraavasti: mikä on kestävän kehityksen periaatteen mukaista säätöä