Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Grasshopper crop and midgut extract effects on plants: an example of reward feedback.

Acid extracts and a resultant fraction from solid-phase extraction (SPE) of Romalea guttata crop and midgut tissues induce sorghum (Sorghum bicolor var. Rio) coleoptile growth in 24-h incubations an average of 49% above untreated controls. When combined with plant auxin, indole-3-acetic acid (IAA), the SPE fraction shows a synergistic reaction, yielding increases in coleoptile growth that average 295% above untreated controls and 8% above IAA standards. The interaction lowered the point of maximum sensitivity of IAA 3 orders of magnitude, resulting in a new IAA physiological set point at 10(-7) g/ml. This synergism suggests that contents in animal regurgitants making their way into plant tissue during feeding may produce a positive feedback in plant growth and development following herbivory. Such a process, also known as reward feedback, may exert major controls on ecosystem-level relationships in nature.

Biofuels impact on crop and food prices : using an interactive spreadsheet /

Mode of access: Internet.

Crop and livestock report.

Publication suspended May 1-Nov. 1, 1921.

Federal-State crop and livestock reporting service: a chronology of development and progress, 1866-1966,

Mode of access: Internet.

The Crop and livestock reporting service of the United States /

Caption title.

Interregional adjustments in crop and livestock production; a linear programming analysis,

Prepared in cooperation with the Center for Agricultural and Economic Development. Iowa Agriculture and Home Economics Experiment Station, Iowa State University.

Crop and Livestock Report

Continued In Its General Bulletin No.379-

Experimental analysis of the influence of pest management practice on the efficacy of an endemic arthropod natural enemy complex of the diamondback moth.

Maximizing the contribution of endemic natural enemies to integrated pest management (IPM) programs requires a detailed knowledge of their interactions with the target pest. This experimental field study evaluated the impact of the endemic natural enemy complex of Plutella xylostella (L.) (Lepidoptera: Yponomeutidae) on pest populations in commercial cabbage crops in southeastern Queensland, Australia. Management data were used to score pest management practices at experimental sites on independent Brassica farms practicing a range of pest management strategies, and mechanical methods of natural enemy exclusion were used to assess the impact of natural enemies on introduced cohorts of P. xylostella at each site. Natural enemy impact was greatest at sites adopting IPM and least at sites practicing conventional pest management strategies. At IPM sites, the contribution of natural enemies to P. xylostella mortality permitted the cultivation of marketable crops with no yield loss but with a substantial reduction in insecticide inputs. Three species of larval parasitoids (Diadegma semiclausum Hellen [Hymenoptera: Ichneumonidae], Apanteles ippeus Nixon [Hymenoptera: Braconidae], and Oomyzus sokolowskii Kurdjumov [Hymenoptera: Eulophidae]) and one species of pupal parasitoid Diadromus collaris Gravenhorst (Hymenoptera: Ichneumonidae) attacked immature P. xylostella. The most abundant groups of predatory arthropods caught in pitfall traps were Araneae (Lycosidae) > Coleoptera (Carabidae, Coccinelidae, Staphylinidae) > Neuroptera (Chrysopidae) > Formicidae, whereas on crop foliage Araneae (Clubionidae, Oxyopidae) > Coleoptera (Coccinelidae) > Neuroptera (Chrysopidae) were most common. The abundance and diversity of natural enemies was greatest at sites that adopted IPM, correlating greater P. xylostella mortality at these sites. The efficacy of the natural enemy complex to pest mortality under different pest management regimes and appropriate strategies to optimize this important natural resource are discussed.

Simulating spray deposition on plant canopies within a wind tunnel

Three-dimensional computer modelling techniques are being used to develop a probabilistic model of turbulence-related spray transport around various plant architectures to investigate the influence of plant architectures and crop geometry on the sprayapplication process. Plant architecture models that utilise a set of growth rules expressed in the Lindenmayer systems (L-systems) formalism have been developed and programmed using L-studio software. Modules have been added to simulate the movement ofdroplets through the air and deposition on the plant canopy. Deposition of spray on an artificial plant structure was measured in the wind tunnel at the University of Queensland, Gatton campus and the results compared to the model simulation. Further trials are planned to measure the deposition of spray droplets on various crop and weed species and the results from these trials will be used to refine and validate the combined spray and plant architecture model.