Light levels influence on development and leaves reflectance index of imperial® zoysia grass / Influência de níveis de luz no desenvolvimento e índice de refletância das folhas de grama esmeralda imperial®

The lawn aesthetics is one of the most important aspect, which professionals need to observe. Shading influence on grass development may be harmful to plant physiology, which will have its photosynthetic processes reduced. A grass that receives less light may etiolate, and, in popular terms, it can fade making it less attractive, since what is expected for a lawn is its vibrant green colour. Therefore, the research aimed to study the influence of luminosity levels and changes in light spectrum in development and leaf reflectance indices of Imperial® Zoysia Grass var.. Grass was implanted in black plastic containers filled with substrate formed by, soil, sand and soil conditioner. Luminosity levels tested were: T1: full sun, T2: 50% black shading net and T3: 50% red solar spectrum manipulation net. The lawn height was assessed using the prism methodology. Digital images were obtained and red, green and blue (RGB) mean values components were reported. RGB results were converted to HSB values (Hue, Saturation and Brightness). After obtaining HSB values, Dark Green Colour Index (DGCI) was calculated. Treatments T2 and T3 interfered in the development and reflectance index of leaves of Zoysia grass Imperial®. For Hue component the cited treatments turn leaves to yellow, which means leaves chloroses caused by the reduction of chlorophyll concentration. Dark Green Colour Index, T2 and T3 influenced in leaves coloration turning them yellowish, proving hue results, which is symptom of chlorosis and etiolation

Potential for Interseeded Cover Crops in a Maize Cropping System in the U.S. Upper Midwest

University of Minnesota M.S. thesis. August 2019. Major: Applied Plant Sciences. Advisors: Axel Garcia y Garcia, Jeffrey Coulter. 1 computer file (PDF); ix, 70 pages.The incorporation of cover crops into the maize (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation in the U.S. upper Midwest may improve economic and environmental sustainability. For example, cover crops grown during the fallow period between maize harvest and planting can reduce the loss of essential plant nutrients like nitrogen (N) to ground and surface waters thereby reducing surface and subsurface quality. However, long, cold winters in the upper Midwest region make selection of successful cover crop species and associated management practices a challenge. This study was conducted to evaluate the establishment and growth of a variety of cover crop monocultures and mixtures across multiple environments and their effect on maize growth and yield and N fate in the cropping system. Two experiments were conducted in Grand Rapids, Lamberton, and Waseca, MN from fall 2016 through spring 2019 to examine whether six cover crop strategies interseeded into maize at the four- to six-leaf collar stage (spring-interseeded) and at physiological maturity (fall-interseeded) compromised maize growth or yield. Annual ryegrass (Lolium multiflorum L., AR) and cereal rye (Secale cereale L., CR) were evaluated as monocultures and in mixtures with crimson clover (Trifolium incarnatum L., CC) and forage radish (Raphanus sativus L., FR). Differences in cover crop canopy cover and biomass were observed at Waseca in 2018. Greater accumulated growing degree days resulting from an earlier interseeding that year did not translate into increased cover crop canopy coverage or biomass of fall-interseeded cover crops compared with 2017. Differences in cover crop canopy cover and biomass among spring-interseeded cover crop strategies were observed at fall frost at all locations in 2017 and at Grand Rapids in 2018. Cover crop canopy cover and biomass at cover crop spring termination, soil moisture at maize planting, maize aboveground biomass and yield were unaffected by the regrowth of fall-interseeded cover crop strategies with CR. Similarly, maize aboveground biomass or yield were not affected by spring-interseeded cover crop strategies. These results highlight the potential for a variety of cover crop strategies to be interseeded into maize without negatively influencing maize production in the U.S. upper Midwest. Next steps might include exploring the influence of the cover crop strategies on soybean production to identify the suitability and optimal placement of cover crops within the maize-soybean rotation. High variability characterized the effect of cover crops interseeded into maize on N fate. Interseeded cover crops had no effect on soil NO3-N in a well-drained loam soil but were found to reduce soil NO3-N relative to no cover in both the 0-20 cm and 20-40 cm layers on moderately well drained and somewhat poorly drained clay loam soils. Fall-interseeded cover crops with CR reduced NO3-N in the soil solution at all three study locations. However, at Grand Rapids, differences in NO3-N concentrations may be due to porous soils and there appear to be thresholds of cover crop growth at Lamberton and Waseca below which cover crops do not reduce NO3-N concentrations in soil solution. Highly variable cover crop N accumulation results make it unclear which cover crop strategy poses the greatest potential for immobilizing N at each location. At Grand Rapids, greater N accumulation occurred in spring-interseeded cover crops than in fall-interseeded cover crops likely because more growing degree days were accumulated when cover crops were interseeded at four- to six-leaf collar stage maize. Cover crops with AR at Grand Rapids accumulated more N than those with CR when spring-interseeded, and the AR monoculture accumulated more N than mixtures with AR. This suggests that spring-interseeding of AR into maize may hold the most promise for Grand Rapids. At Lamberton and Waseca, spring- and fall-interseeded mixtures with AR + CC + FR and CR + CC + FR accumulated more N than both monocultures and mixtures of AR + CC and CR + CC. However, they did not always accumulate significantly more N than other treatments. Thus, the 3-species mixtures may be as effective as or better than other cover crop treatments for N scavenging at Lamberton and Waseca. Future work could examine increasing the seeding rate and using a drill to interseed cover crops at the four- to six-leaf collar stage to enhance the capacity of cover crops to provide N loss reduction services to the maize cropping system

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Nitrogen (N) is one of the most limiting factors for maize (Zea mays L.) production worldwide. Over-fertilization of N may decrease yields and increase NO3− contamination of water. However, low N fertilization will decrease yields. The objective is to optimize the use of N fertilizers, to excel in yields and preserve the environment. The knowledge of factors affecting the mobility of N in the soil is crucial to determine ways to manage N in the field. Researchers developed several methods to use N efficiently relying on agronomic practices, the use of sensors and the analysis of digital images. These imaging sensors determine N requirements in plants based on changes in Leaf chlorophyll and polyphenolics contents, the Normalized Difference Vegetation Index (NDVI), and the Dark Green Color index (DGCI). Each method revealed limitations and the scope of future research is to draw N recommendations from the Dark Green Color Index (DGCI) technology. Results showed that more effort is needed to develop tools to benefit from DGCI

The adoption of agricultural machinery and its economic impacts in China

In modern agriculture, machinery plays an important role to substitute manual labor and to improve productivity and economic performance of farm households. Conventional agricultural machinery in crop production includes tractors, cultivators, tillers, combine harvesters, pumps, threshers, planters, fertilizer spreaders, seeders, etc. In recent years, as an innovative agricultural machinery, unmanned aerial vehicles (UAVs) have been adopted in precision agriculture for crop monitoring and crop spraying. However, factors influencing Chinese farmers adoption of agricultural machinery and the economic impacts of the adoption have not been adequately studied, especially regarding farm machinery in maize production and UAVs in precision agriculture. In addition, there is limited literature that systematically summarizes the use of UAVs in maize production. The development of UAV-based pattern management in Chinese agriculture and the prerequisites for adopting and implementing this approach remain unclear. By utilizing farm household data, qualitative methods, and econometric quantitative methods, this dissertation aims to (i) identify the factors influencing the adoption of farm machinery and UAVs by Chinese farmers; (ii) estimate the economic impacts of adopting farm machinery and UAVs; (iii) provide an overview of UAV applications in maize production; (iv) study the prerequisites for adopting and implementing UAV-based pattern management in Chinese agriculture; (v) outline and recommend policy instruments to promote the use of farm machinery and UAVs in China. The empirical results indicate that the determinants of farm machinery adoption and UAV adoption can be attributed by three major aspects: farmer characteristics (e.g., age, education level, and perceptions about agricultural machinery), farm characteristics (e.g., farm size, land fragmentation, and cooperative membership), and other external socio-economic factors (e.g., subsidies, technical assistance, and labor shortages). The adoption of farm machinery and UAVs has shown significantly positive economic effects. However, the effects vary among farm household types due to the heterogeneous farm characteristics and socio-economic conditions. Farm machinery use significantly increased maize yield by 0.216 tons/ha and improved labor productivity by 18.65%. Young, male, and better-educated farmers benefit more from adopting farm machinery, and farms located in plain regions with cooperative membership and rented land can gain higher economic benefits from machinery use. In addition, the impacts of farm machinery adoption on maize yield and labor productivity slightly decrease with farm size. The adoption of UAVs in pesticide application significantly increased revenue and reduced the time spent on pesticide application by approximately 434-488 USD/ha and 14.4-15.8 hours/ha, respectively. In terms of marginal revenue and marginal time spent on pesticide application, the optimal area for using UAVs in pesticide spraying is estimated to be 20 hectares of arable land, suggesting that small and medium-scale farmers are the main beneficiaries of UAV adoption. For the wide application of UAV-based pattern management in precision agriculture, certain socio-economic and technical prerequisites are necessary. These include farmers possessing adequate UAV-related capabilities, relatively large farm sizes, availability of UAV-related subsidies, and superior UAV performance. Balancing the pros and cons, the effective promotion of farm machinery in maize production and UAVs in precision agriculture requires the establishment of a comprehensive socio-economic institution. This institution should integrate strategies from both the public and private sectors such as the implementation of land consolidation, the establishment of agricultural machinery cooperatives for benefit-risk sharing, the provision of practical training and education on agricultural machinery, and subsidies for the purchase of agricultural machinery. Due to the heterogeneous effects of farm machinery adoption and UAV adoption, it is necessary to develop customized extension services tailored to various types of farm households to prevent inequity among farmers.In der modernen Landwirtschaft spielen Maschinen eine wichtige Rolle, indem sie manuelle Arbeit ersetzen, sowie Produktivität und wirtschaftliche Leistungsfähigkeit verbessern. Konventionelle Landmaschinen umfassen Traktoren, Kultivatoren, Pflüge, Mähdrescher, Pumpen, Dreschmaschinen, Pflanzmaschinen, Düngerstreuer, Sämaschinen usw. In den letzten Jahren wurden unbemannte Luftfahrzeuge (Unmanned Aerial Vehicles, UAVs) als innovative landwirtschaftliche Maschinen in der Präzisionslandwirtschaft eingesetzt, sowohl zur Überwachung von Pflanzen als auch zur Schädlingsbekämpfung. Jedoch wurden die Faktoren, die die Akzeptanz landwirtschaftlicher Maschinen durch chinesische Landwirte und die ökonomischen Auswirkungen ihrer Übernahme, nicht ausreichend untersucht, insbesondere im Hinblick auf Landmaschinen in der Maisproduktion und unbemannte Luftfahrzeuge in der Präzisionslandwirtschaft. Darüber hinaus gibt es nur wenig Literatur, die den Einsatz von UAVs in der Maisproduktion systematisch zusammenfasst. Die Entwicklung eines auf UAVs basierenden Managements in der chinesischen Landwirtschaft und die Voraussetzungen für die Übernahme und Umsetzung dieses Ansatzes bleiben unklar. Unter Verwendung von Daten zu landwirtschaftlichen Haushalten, von qualitativen Methoden und ökonometrischen quantitativen Methoden zielt diese Dissertation darauf ab, (i) die Faktoren zu identifizieren, die die Akzeptanz von landwirtschaftlichen Maschinen und UAVs durch chinesische Landwirte beeinflussen; (ii) die wirtschaftlichen Auswirkungen der Einführung von landwirtschaftlichen Maschinen und UAVs zu schätzen; (iii) einen Überblick über die Anwendungen von UAVs in der Maisproduktion geben; (iv) die Voraussetzungen für die Implementierung eines UAV-basierten Managements in der chinesischen Landwirtschaft zu untersuchen; (v) Politikinstrumente zur Förderung des Einsatzes von landwirtschaftlichen Maschinen und UAVs in China zu formulieren. Die empirischen Ergebnisse deuten darauf hin, dass die Determinanten der Akzeptanz von landwirtschaftlichen Maschinen und UAVs auf drei Hauptaspekte zurückzuführen sind: die Eigenschaften der Landwirte (z. B. Alter, Bildungsniveau und Wahrnehmung von Landmaschinen), die Merkmale des landwirtschaftlichen Betriebs (z. B. Betriebsgröße, Landfragmentierung und Mitgliedschaft in einer Genossenschaft) sowie andere externe sozioökonomische Faktoren (z. B. Subventionen, technische Unterstützung und Arbeitskräftemangel). Der Einsatz von landwirtschaftlichen Maschinen und UAVs hat deutlich positive wirtschaftliche Auswirkungen gezeigt. Allerdings variieren die Effekte aufgrund der unterschiedlichen Merkmale der landwirtschaftlichen Betriebe und der sozioökonomischen Bedingungen von Haushalt zu Haushalt. Der Einsatz landwirtschaftlicher Maschinen hat den Maisertrag und die Arbeitsproduktivität signifikant erhöht. Der Maisertrag hat sich um 0,216 Tonnen pro Hektar erhöht und die Arbeitsproduktivität um 18.65%. Junge, männliche und besser gebildete Landwirte profitieren mehr von der Akzeptanz von Landmaschinen, und Betriebe in ebenen Regionen mit Genossenschaftsmitgliedschaft und höherem Pachtanteil können höhere wirtschaftliche Vorteile durch den Maschineneinsatz erzielen. Darüber hinaus nehmen die Auswirkungen der Akzeptanz von landwirtschaftlichen Maschinen auf den Maisertrag und die Arbeitsproduktivität leicht mit der Betriebsgröße ab. Die Akzeptanz von UAVs bei der Pestizidanwendung hat den Ertrag signifikant um etwa 434-488 USD pro Hektar erhöht und die für die Pestizidanwendung aufgewendete Zeit um 14,4-15,8 Stunden pro Hektar reduziert. In Bezug auf den marginalen Ertrag und die marginale Zeit für die Pestizidanwendung wird der optimale Bereich für den Einsatz von UAVs bei der Pestizidapplikation auf 20 Hektar Ackerland geschätzt, was darauf hinweist, dass kleine und mittelgroße Betriebe die Hauptnutznießer der Akzeptanz von UAVs sind. Für den breiten Einsatz des auf UAVs basierenden Muster-Managements in der Präzisionslandwirtschaft sind bestimmte sozioökonomische und technische Voraussetzungen erforderlich. Dazu gehören Betriebe, die über ausreichende Fähigkeiten im Umgang mit UAVs verfügen, relativ große Flächenausstattung aufweisen, die Verfügbarkeit von UAV-bezogenen Subventionen und eine ausreichende Leistung der UAVs. Bei der Abwägung der Vor- und Nachteile, erfordert die wirksame Förderung des Einsatzes von Landmaschinen in der Maisproduktion und UAVs in der Präzisionslandwirtschaft die Einrichtung einer umfassenden sozioökonomischen Institution. Diese Institution sollte Strategien aus beiden Sektoren, dem öffentlichen und privaten Sektor, wie die Umsetzung der Flurbereinigung, die Gründung von landwirtschaftlichen Maschinenkooperativen zur Vorteils- und Risikoteilung, die Bereitstellung von praktischer Schulung und Ausbildung im Umgang mit landwirtschaftlichen Maschinen sowie Subventionen für den Kauf von landwirtschaftlichen Maschinen integrieren. Aufgrund der unterschiedlichen Ergebnisse bei der Übernahme von landwirtschaftlichen Maschinen und UAVs in den Betrieben, ist es notwendig, maßgeschneiderte Beratungsdienste zu entwickeln, die auf die verschiedenen Arten von landwirtschaftlichen Haushalten zugeschnitten sind, um Ungleichheiten unter den Landwirten zu vermeiden