Digital image analysis as a tool to estimate legume contributions in legume-grass swards

Summary: Productivity and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. For these objectives the botanical composition of the swards is of particular importance, especially, the content of legumes due to their ability to fix airborne nitrogen. As it can vary considerably within a field, a non-destructive detection method while doing other tasks would facilitate a more targeted sward management and could predict the nitrogen supply of the soil for the subsequent crop. This study was undertaken to explore the potential of digital image analysis (DIA) for a non destructive prediction of legume dry matter (DM) contribution of legume-grass mixtures. For this purpose an experiment was conducted in a greenhouse, comprising a sample size of 64 experimental swards such as pure swards of red clover (Trifolium pratense L.), white clover (Trifolium repens L.) and lucerne (Medicago sativa L.) as well as binary mixtures of each legume with perennial ryegrass (Lolium perenne L.). Growth stages ranged from tillering to heading and the proportion of legumes from 0 to 80 %. Based on digital sward images three steps were considered in order to estimate the legume contribution (% of DM): i) The development of a digital image analysis (DIA) procedure in order to estimate legume coverage (% of area). ii) The description of the relationship between legume coverage (% area) and legume contribution (% of DM) derived from digital analysis of legume coverage related to the green area in a digital image. iii) The estimation of the legume DM contribution with the findings of i) and ii). i) In order to evaluate the most suitable approach for the estimation of legume coverage by means of DIA different tools were tested. Morphological operators such as erode and dilate support the differentiation of objects of different shape by shrinking and dilating objects (Soille, 1999). When applied to digital images of legume-grass mixtures thin grass leaves were removed whereas rounder clover leaves were left. After this process legume leaves were identified by threshold segmentation. The segmentation of greyscale images turned out to be not applicable since the segmentation between legumes and bare soil failed. The advanced procedure comprising morphological operators and HSL colour information could determine bare soil areas in young and open swards very accurately. Also legume specific HSL thresholds allowed for precise estimations of legume coverage across a wide range from 11.8 - 72.4 %. Based on this legume specific DIA procedure estimated legume coverage showed good correlations with the measured values across the whole range of sward ages (R2 0.96, SE 4.7 %). A wide range of form parameters (i.e. size, breadth, rectangularity, and circularity of areas) was tested across all sward types, but none did improve prediction accuracy of legume coverage significantly. ii) Using measured reference data of legume coverage and contribution, in a first approach a common relationship based on all three legumes and sward ages of 35, 49 and 63 days was found with R2 0.90. This relationship was improved by a legume-specific approach of only 49- and 63-d old swards (R2 0.94, 0.96 and 0.97 for red clover, white clover, and lucerne, respectively) since differing structural attributes of the legume species influence the relationship between these two parameters. In a second approach biomass was included in the model in order to allow for different structures of swards of different ages. Hence, a model was developed, providing a close look on the relationship between legume coverage in binary legume-ryegrass communities and the legume contribution: At the same level of legume coverage, legume contribution decreased with increased total biomass. This phenomenon may be caused by more non-leguminous biomass covered by legume leaves at high levels of total biomass. Additionally, values of legume contribution and coverage were transformed to the logit-scale in order to avoid problems with heteroscedasticity and negative predictions. The resulting relationships between the measured legume contribution and the calculated legume contribution indicated a high model accuracy for all legume species (R2 0.93, 0.97, 0.98 with SE 4.81, 3.22, 3.07 % of DM for red clover, white clover, and lucerne swards, respectively). The validation of the model by using digital images collected over field grown swards with biomass ranges considering the scope of the model shows, that the model is able to predict legume contribution for most common legume-grass swards (Frame, 1992; Ledgard and Steele, 1992; Loges, 1998). iii) An advanced procedure for the determination of legume DM contribution by DIA is suggested, which comprises the inclusion of morphological operators and HSL colour information in the analysis of images and which applies an advanced function to predict legume DM contribution from legume coverage by considering total sward biomass. Low residuals between measured and calculated values of legume dry matter contribution were found for the separate legume species (R2 0.90, 0.94, 0.93 with SE 5.89, 4.31, 5.52 % of DM for red clover, white clover, and lucerne swards, respectively). The introduced DIA procedure provides a rapid and precise estimation of legume DM contribution for different legume species across a wide range of sward ages. Further research is needed in order to adapt the procedure to field scale, dealing with differing light effects and potentially higher swards. The integration of total biomass into the model for determining legume contribution does not necessarily reduce its applicability in practice as a combined estimation of total biomass and legume coverage by field spectroscopy (Biewer et al. 2009) and DIA, respectively, may allow for an accurate prediction of the legume contribution in legume-grass mixtures.

Sensorische Erfassung von Grünlandbiomassen als Grundlage für ein teilflächenspezifisches Management im Ökologischen Landbau

Vor dem Hintergund der Integration des wissensbasierten Managementsystems Precision Farming in den Ökologischen Landbau wurde die Umsetzung bestehender sowie neu zu entwickelnder Strategien evaluiert und diskutiert. Mit Blick auf eine im Precision Farming maßgebende kosteneffiziente Ertragserfassung der im Ökologischen Landbau flächenrelevanten Leguminosen-Grasgemenge wurden in zwei weiteren Beiträgen die Schätzgüten von Ultraschall- und Spektralsensorik in singulärer und kombinierter Anwendung analysiert. Das Ziel des Precision Farming, ein angepasstes Management bezogen auf die flächeninterne Variabilität der Standorte umzusetzen, und damit einer Reduzierung von Betriebsmitteln, Energie, Arbeit und Umwelteffekten bei gleichzeitiger Effektivitätssteigerung und einer ökonomischen Optimierung zu erreichen, deckt sich mit wesentlichen Bestrebungen im Ökogischen Landbau. Es sind vorrangig Maßnahmen zur Erfassung der Variabilität von Standortfaktoren wie Geländerelief, Bodenbeprobung und scheinbare elektrische Leitfähigkeit sowie der Ertragserfassung über Mähdrescher, die direkt im Ökologischen Landbau Anwendung finden können. Dagegen sind dynamisch angepasste Applikationen zur Düngung, im Pflanzenschutz und zur Beseitigung von Unkräutern aufgrund komplexer Interaktionen und eines eher passiven Charakters dieser Maßnahmen im Ökologischen Landbau nur bei Veränderung der Applikationsmodelle und unter Einbindung weiterer dynamischer Daten umsetzbar. Beispiele hiefür sind einzubeziehende Mineralisierungsprozesse im Boden und organischem Dünger bei der Düngemengenberechnung, schwer ortsspezifisch zuzuordnende präventive Maßnamen im Pflanzenschutz sowie Einflüsse auf bodenmikrobiologische Prozesse bei Hack- oder Striegelgängen. Die indirekten Regulationsmechanismen des Ökologischen Landbaus begrenzen daher die bisher eher auf eine direkte Wirkung ausgelegten dynamisch angepassten Applikationen des konventionellen Precision Farming. Ergänzend sind innovative neue Strategien denkbar, von denen die qualitätsbezogene Ernte, der Einsatz hochsensibler Sensoren zur Früherkennung von Pflanzenkrankheiten oder die gezielte teilflächen- und naturschutzorientierte Bewirtschaftung exemplarisch in der Arbeit vorgestellt werden. Für die häufig große Flächenanteile umfassenden Leguminosen-Grasgemenge wurden für eine kostengünstige und flexibel einsetzbare Ertragserfassung die Ultraschalldistanzmessung zur Charakterisierung der Bestandeshöhe sowie verschiedene spektrale Vegetationsindices als Schätzindikatoren analysiert. Die Vegetationsindices wurden aus hyperspektralen Daten nach publizierten Gleichungen errechnet sowie als „Normalized Difference Spectral Index“ (NDSI) stufenweise aus allen möglichen Wellenlängenkombinationen ermittelt. Die Analyse erfolgte für Ultraschall und Vegetationsindices in alleiniger und in kombinierter Anwendung, um mögliche kompensatorische Effekte zu nutzen. In alleiniger Anwendung erreichte die Ultraschallbestandeshöhe durchweg bessere Schätzgüten, als alle einzelnen Vegetationsindices. Bei den letztgenannten erreichten insbesondere auf Wasserabsorptionsbanden basierende Vegetationsindices eine höhere Schätzgenauigkeit als traditionelle Rot/Infrarot-Indices. Die Kombination beider Sensorda-ten ließ eine weitere Steigerung der Schätzgüte erkennen, insbesondere bei bestandesspezifischer Kalibration. Hierbei kompensieren die Vegetationsindices Fehlschätzungen der Höhenmessung bei diskontinuierlichen Bestandesdichtenänderungen entlang des Höhengradienten, wie sie beim Ährenschieben oder durch einzelne hochwachsende Arten verursacht werden. Die Kombination der Ultraschallbestandeshöhe mit Vegetationsindices weist das Potential zur Entwicklung kostengünstiger Ertragssensoren für Leguminosen-Grasgemenge auf. Weitere Untersuchungen mit hyperspektralen Vegetationsindices anderer Berechnungstrukturen sowie die Einbindung von mehr als zwei Wellenlängen sind hinsichtlich der Entwicklung höherer Schätzgüten notwendig. Ebenso gilt es, Kalibrierungen und Validationen der Sensorkombination im artenreichen Grasland durchzuführen. Die Ertragserfassung in den Leguminosen-Grasgemengen stellt einen wichtigen Beitrag zur Erstellung einer Ertragshistorie in den vielfältigen Fruchtfolgen des Ökologischen Landbaus dar und ermöglicht eine verbesserte Einschätzung von Produktionspotenzialen und Defizitarealen für ein standortangepasstes Management.

Methods for short-term control of Imperata grass in Peruvian Amazon

The traditional control of Imperata brasiliensis grasslands used by farmers in the Peruvian Amazon is to burn the grass. The objective of this study was to compare different methods of short-term control. Biological, mechanical, chemical and traditional methods of control were compared. Herbicide spraying and manual weeding have shown to be very effective in reducing above- and below-ground biomass growth in the first 45 days after slashing the grass, with effects persisting in the longer term, but both are expensive methods. Shading seems to be less effective in the short-term, whereas it influences the Imperata growth in the longer term. After one year shading, glyphosate application and weeding significantly reduced aboveground biomass by 94, 67 and 53%; and belowground biomass by 76, 65 and 58%, respectively, compared to control. We also found a significant decrease of Imperata rhizomes in soil during time under shading. Burning has proved to have no significant effect on Imperata growth. The use of shade trees in a kind of agroforestry system could be a suitable method for small farmers to control Imperata grasslands.

Land use change from rainforests to oil palm plantations and food gardens in Papua New Guinea: Effects on soil properties and S fractions

Changes in soil sulfur (S) fractions were assessed in oil palm and food garden land use systems developed on forest vegetation in humid tropical areas of Popondetta in northern Province. The study tested a hypothesis that S in food gardens are limiting nutrient factor and are significantly lower than in plantations and forests. Subsistence food gardens are under long-term slash and burn practice of cropping and such practice is expected to accelerate loss of biomass S from the ecosystem. From each land use, surface soil (0–15 cm) samples were characterised and further pseudocomplete fractionated for S. Conversion of forest to oil palm production decreased (p<0.001) soil pH and electrical conductivity values. The reserve S fraction in soil increased significantly (p<0.05) due to oil palm production ( 28 %) and food gardening activity (∼ 54 %). However, plant available SO42--S was below 15 mg kg^(−1) in the food garden soils and foliar samples of sweet potato crop indicating deficiency of plant available S. Soil organic carbon content (OC) was positively and significantly correlated to total S content (r=0.533; p<0.001) among the land use systems. Thus, crop management practices that affect OC status of the soils would potentially affect the S availability in soils. The possible changes in the chemical nature of mineralisable organic S compounds leading to enhanced mineralisation and leaching losses could be the reasons for the deficiency of S in the food garden soils. The results of this study conclude that long-term subsistence food gardening activity enriched top soils with reserve S or total S content at the expense of soluble S fraction. The subsistence cropping practices such as biomass burning in food gardens and reduced fallow periods are apparently threatening food security of oil palm households. Improved soil OC management strategies such as avoiding burning of fallow vegetation, improved fallows, mulching with fallow biomass, use of manures and S containing fertilisers must be promoted to sustain food security in smallholder oil palm system.

Potential mitigation of midwest grass-finished beef production emissions with soil carbon sequestration in the United States of America

Beef production can be environmentally detrimental due in large part to associated enteric methane (CH4) production, which contributes to climate change. However, beef production in well-managed grazing systems can aid in soil carbon sequestration (SCS), which is often ignored when assessing beef production impacts on climate change. To estimate the carbon footprint and climate change mitigation potential of upper Midwest grass-finished beef production systems, we conducted a partial life cycle assessment (LCA) comparing two grazing management strategies: 1) a non-irrigated, lightly-stocked (1.0 AU/ha), high-density (100,000 kg LW/ha) system (MOB) and 2) an irrigated, heavily-stocked (2.5 AU/ha), low-density (30,000 kg LW/ha) system (IRG). In each system, April-born steers were weaned in November, winter-backgrounded for 6 months and grazed until their endpoint the following November, with average slaughter age of 19 months and a 295 kg hot carcass weight. As the basis for the LCA, we used two years of data from Lake City Research Center, Lake City, MI. We included greenhouse gas (GHG) emissions associated with enteric CH4, soil N2O and CH4 fluxes, alfalfa and mineral supplementation, and farm energy use. We also generated results from the LCA using the enteric emissions equations of the Intergovernmental Panel on Climate Change (IPCC). We evaluated a range of potential rates of soil carbon (C) loss or gain of up to 3 Mg C ha-1 yr-1. Enteric CH4 had the largest impact on total emissions, but this varied by grazing system. Enteric CH4 composed 62 and 66% of emissions for IRG and MOB, respectively, on a land basis. Both MOB and IRG were net GHG sources when SCS was not considered. Our partial LCA indicated that when SCS potential was included, each grazing strategy could be an overall sink. Sensitivity analyses indicated that soil in the MOB and IRG systems would need to sequester 1 and 2 Mg C ha-1 yr-1 for a net zero GHG footprint, respectively. IPCC model estimates for enteric CH4 were similar to field estimates for the MOB system, but were higher for the IRG system, suggesting that 0.62 Mg C ha-1 yr-1 greater SCS would be needed to offset the animal emissions in this case.