Crop Height Research Articles

Plant weight determines secondary fibre development in fibre hemp (Cannabis sativa L.)

In fibre hemp (Cannabis sativa L.) grown for the production of high‒quality textile yarns the presence of secondary fibres is unwanted. These fibres are too short for spinning and their presence hampers the production of fine and homogeneous yarns from the primary or long fibres. Primary fibres are present along the stem from bottom to top and hemp for fibres is traditionally harvested around the time of flowering, when the cell walls of these fibres are sufficiently thickened with cellulose to be extracted. In literature indications are found that the height up to which secondary fibres are present, moves upwards along the stem during the growing season, and that this process accelerates around flowering. To optimise the length of the stem part with primary fibres, but without secondary fibres, the background of secondary fibre development should be elucidated. It can be hypothesised that either flowering or the increasing plant size accelerates the formation of secondary fibres. To investigate this, an indoor experiment was conducted in greenhouses with mobile covers in which the day–length sensitivity of hemp was used to create size ranges of flowering and non–flowering plants for a single cultivar, Futura 75. Secondary fibre formation was recorded using microscopic techniques. The height up to which secondary fibres were present, depended on plant weight. The higher secondary fibre front in flowering plants was most likely caused by the higher weight of these plants as compared with non–flowering plants of the same height. As seed carrying inflorescences contribute to plant weight, dual use of fibre hemp for seed and high–quality textile fibres is not an option. Results from a field experiment confirmed the correlation between plant size and the height of the secondary fibre front. Therefore, to optimise the length of the stem part with primary fibres, but without secondary fibres above stubble height, for Futura 75 a relatively short crop of around 1.3–1.4 m should be harvested before flowering. This ideal crop height is likely to differ between varieties.

Calculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2

Evapotranspiration is considered to be an important component of allocating water to agricultural sector; therefore, the more accurate this parameter is, the more optimized the water use can be. This study was conducted in order to evaluate the Landsat 8 and Sentinel-2 data (A and B), both separately and combined, in potential evapotranspiration (ETp) and single crop coefficient (Kc) estimations. Field measurements such as crop height, leaf area index (LAI), land surface temperature (LST), air temperature above canopy (AT), and spectral data were exploited in the evaluating process throughout the entirety of 2017–18 growing season under winter wheat and barley cultivations in the Agricultural Research Farms of the University of Tehran. The novel method of Multi-Sensor Data Fusion using the Priestly-Taylor equation was taken into practice for satellite-based ETp (MSDF-ET) calculation from the combination of MODIS thermal and Landsat 8 and Sentinel-2 multispectral data. Thermal images were downscaled by the means of the TsHARP algorithm. Thus, prior to ETp calculation, the thermal sharpening algorithm calculated using different spectral indices (SI) was assessed. The SI included NDVI, SAVI, SR, NDWI, NDWIg, and LSWI. The subsequent results were representative of the LSWI qualification under both Landsat 8 and Sentinel-2 conditions against thermal and spectral measurements. Also the satellite-based ETp strongly correlated with the ETp derived from the field data illuminating the promising accuracy of the MSDF-ET method in both Landsat 8 and Sentinel-2 data. In the end, the time series of Kc obtained from the combination of satellites were fairly indicative of the real-world variations under different vegetation cover and crop growth stages. Overall, using Landsat 8 and Sentinel-2 products in integration with each other could significantly result in more reliable decisions in agricultural water resources management.

Monitoring sugarcane growth response to varying nitrogen application rates: A comparison of UAV SLAM LiDAR and photogrammetry

The capabilities and utility of UAV LiDAR and surface from motion photogrammetry have been of wide discussion in the remote sensing community and assumptions made, often speculative, about the potential strengths and limitations of these systems. Here, we employ a side-by-side test of the CSIRO Hovermap LiDAR and Micasense RedEdge multispectral camera simultaneously mounted to a single UAV platform to acquire a time-series data set from both sensors over the growth cycle of a sugarcane crop in northeast Queensland, Australia. The primary aim was to compare the ability of each system to accurately measure crop height, over a single growing cycle. A secondary aim examined the correlation between these measures and the sugarcane biophysical parameters of stalk population (stalks·m−2), total fresh biomass (TFB, t·ha-1) and cane yield (Yield, t cane·ha-1). The experimental design included a randomised complete block design of four nitrogen fertiliser treatments (0, 70, 110, 150 and 190 Nkg·ha-1) with four replications to assess if either optical measure could detect significant effects of nitrogen application on crop growth. Both systems demonstrated similar capabilities for accurately measuring crop heights throughout the growth period with statistically significant coefficients of determination observed when comparing the maximum (AdjR2 = .885, F(1,118) = 910.806, p ≤ .001) and mean (AdjR2 = .929, F(1,118) = 1548.404, p ≤ .001) crop height estimations of both instruments. In addition, both systems responded similarly in the detection of differences in crop structural properties response to nitrogen treatments. Only Hovermap, however, demonstrated the capacity to obtain sufficient ground returns over the course of the growth period to enable comparisons to the biophysical samples using a ground-to-non-ground return ratio (Stalk Population:AdjR2 = .788, F(1,18) = 70.688, p ≤ .001, TFB: AdjR2 = .713, F(1,18) = 48.198, p ≤ .001, Yield:AdjR2 = .707, F(1,18) = 46.921, p ≤ .001) with the best results of RedEdge obtained when comparing mean height measures (Stalk PopulationAdjR2 = .502, F(1,18) = 20.172, p ≤ .001, TFB: AdjR2 = .309, F(1,18) = 9.481, p = 0.006, Yield: AdjR2 = .322, F(1,18) = 10.028, p ≤ .005). The results suggest that although both systems are comparable for accurate crop height measurements, and as such, provide early detection of potential problems, UAV LiDAR provided more consistent and significant correlations with optical remotely sensed data to the biophysical parameters of sugarcane.

Airflow assessment in a naturally ventilated greenhouse equipped with wind towers: numerical simulation and wind tunnel experiments

In this study, the air change rate and airflow distribution inside a greenhouse equipped with wind towers were analyzed using Computational Fluid Dynamics (CFD) simulations, considering different wind speeds (1–5 m/s) and incident angles (0–45°). The validation methods included smoke visualization, hot wire velocity point measurements, and Particle Image Velocimetry (PIV) measurements. The visualized and simulated flow regimes exhibited fair agreement. The average discrepancy between the hot wire velocity point measurements and simulated results was about 7.96%. The predicted vector fields in the inlet and outlet wind towers demonstrated good qualitative agreement with the corresponding PIV measurements. The discrepancy between the predicted and measured maximum air velocity in the inlet tower was 15%, while it was 3% in the outlet wind tower. At an external wind speed of 3 m/s and normal incidence angle, the average velocity of the airflow entering the greenhouse was 0.65 m/s (about one air change per minute), while the average air velocity in the greenhouse was 0.44 m/s. The average air velocity inside the greenhouse at a crop height (1 m) ranged from 0.3 to 1.8 m/s, which is within the optimum range of recommended air velocities for greenhouses.

Salinity Effect on the Crop Height, Root Depth and Leaf Index Area of Tomato Crop in Tunisia

Salinity Effect on the Crop Height, Root Depth and Leaf Index Area of Tomato Crop in Tunisia

AUTOMATIC GENERATION OF GEOMETRIC PARAMETERS OF INDIVIDUAL CAULIFLOWER PLANTS FOR RAPID PHENOTYPING USING DRONE IMAGES

Abstract. Multitemporal drone surveys are a perfect tool to determine various geometric and spectral crop parameters for rapid phenotyping in field trials. Depending on the geometric resolution and the size of the crop, information at leaf level or canopy level can be obtained. The focus of this paper is to demonstrate which geometric properties can be automatically derived from high resolution drone imagery during the vegetation period. For this research approx. 1920 cauliflower with a large genetic variety were planted and monitored by five different drone surveys at an altitude of 20 m, using a high resolution 36 Mpix. RGB-camera. In order to minimize intensive radiometric calibration, BRDF effects and eliminate shade, flights were carried out at overcast skies. After photogrammetric image processing, detailed crop height models (CHM) were computed. 10 distinct crop parameters were derived from a combination of the orthophotos, the CHM and additional information. According to the phenological phase a specific set of parameters was developed for every flight. For instance, the position of the individual plants is computed right after the first flight. For the flight prior to harvesting, an algorithm for the head diameter and the curvature of the cauliflower heads was developed. Geometric parameters are generally better suited for automation, because they require less specific ground truth or reference information, than spectrally derived biophysical parameters.

Turbulent Kinetic Energy Distribution of Nutrient Solution Flow in NFT Hydroponic Systems Using Computational Fluid Dynamics

Hydroponics is crucial for providing feasible and economical alternatives when soils are not available for conventional farming. Scholars have raised questions regarding the ideal nutrient solution flow rate to increase the weight and height of hydroponic crops. This paper presents the turbulent kinetic energy distribution of the nutrient solution flow in a nutrient film technique (NFT) hydroponic system using the computational fluid dynamics (CFD) method. Its main objective is to determine the dynamics of nutrient solution flow. To conduct this study, a virtual NFT hydroponic system was modeled. To determine the turbulent kinetic energy distribution in the virtual NFT hydroponic system, we conducted a CFD analysis with different pipe diameters (3.5, 9.5, and 15.5 mm) and flow rates (0.75, 1.5, 3, and 6 L min−1). The simulation results indicate that different pipe diameters and flow rates in NFT hydroponic systems vary the turbulent kinetic energy distribution of nutrient solution flow around plastic mesh pots.

Phenomenon of Inbreeding Depression on Maize in Perspective of The Quran

The objectives of this study were to learn and prove the truth and scientific miracles of The Quran, specifically the prohibition of incest for humans, also applies and affects especially on the growth and yieldin particularly open pollinated plants such as maize through the process of inbreeding depression. The results of yield of each genotype of the tested inbred line showed yield reduction in all inbred lines tested from generation of S 1 to S 5 . Lamuru and Bisma which were generated with an open pollinated breeding produced relatively stable yield from generation of S 1 to S 5 . The entire tested inbred lines showed some trait changes, such as height of crop (cm) and yield of grains (t/ha) that tended to decline and die, while Lamuru and Bisma tended to be stable. It is implied in letters of The Quran, which forbid inbreeding for human that is very detrimental, not only on life sustainability of human beings and animals, but also on plants, particularly on the cross-pollinated plants . The scientific truth of The Quran which prohibits incest for humans are proven to be identical and also apply in maize.

Response of Immature Oil Palm Growth and CO2 emission on Intercropping System After Replanting

One of the problems in smallholder oil palm plantations was the financing for replanting and loss of revenues during immature oil palm period. One alternative to the problem was the development of an adaptive plant system through intercropping crops planted among immature oil palm crops. The research was conducted in banjar seminai village, dayun subdistrict, siak regency, Riau Province on May to October 2017. The study used a factorial randomized block design with three replications. Annual crops treatment consists of corn, soybean, eggplant and chili. The results showed that there was positive response of oil palm height on intercropping systems. Corn intercropping plants increased the height of oil palm crops. The intercropping plants had no significant effect on the number of leaf midrib and the width of oil palm canopy. Monoculture oil palm crops without intercropping produced average emissions of 8.78 t CO2 ha-1yr-1. Oil palm intercrop with eggplant and soybean produces the highest CO2 emissions of 10.4 and 10.2 t CO2 ha-¹yr-¹, while oil palm in intercrop with chili produced the lowest CO2 emissions of 8.66 t CO2 ha-1yr-¹.

ON THE DERIVATION OF CROP HEIGHTS FROM MULTITEMPORAL UAV BASED IMAGERY

Abstract. In this paper, we investigate the usage of unmanned aerial vehicles (UAV) to assess the crop geometry with special focus on the crop height extraction. Crop height is classified as a reliable trait in crop phenotyping and recognized as a good indicator for biomass, expected yield, lodging or crop stress. The current industrial standard for crop height measurement is a manual procedure using a ruler, but this method is considered as time consuming, labour intensive and subjective. This study investigates methods for reliable and rapid deriving of the crop height from high spatial, spectral and time resolution UAV data considering the influences of the reference surface and the selected crop height generation method to the final calculation. To do this, we performed UAV missions during two winter wheat growing seasons and generate point clouds from areal images using photogrammetric methods. For the accuracy assessment we compare UAV based crop height with ruler based crop height as current industrial standard and terrestrial laser scanner (TLS) based crop height as a reliable validation method. The high correlation between UAV based and ruler based crop height and especially the correlation with TLS data shows that the UAV based crop height extraction method can provide reliable winter wheat height information in a non-invasive and rapid way. Along with crop height as a single value per area of interest, 3D UAV crop data should provide some additional information like lodging area, which can also be of interest in the plant breeding community.

Winter Wheat Canopy Height Extraction from UAV-Based Point Cloud Data with a Moving Cuboid Filter

Plant height can be used as an indicator to estimate crop phenology and biomass. The Unmanned Aerial Vehicle (UAV)-based point cloud data derived from photogrammetry methods contains the structural information of crops which could be used to retrieve crop height. However, removing noise and outliers from the UAV-based crop point cloud data for height extraction is challenging. The objective of this paper is to develop an alternative method for canopy height determination from UAV-based 3D point cloud datasets using a statistical analysis method and a moving cuboid filter to remove outliers. In this method, first, the point cloud data is divided into many 3D columns. Secondly, a moving cuboid filter is applied in each column and moved downward to eliminate noise points. The threshold of point numbers in the filter is calculated based on the distribution of points in the column. After applying the moving cuboid filter, the crop height is calculated from the highest and lowest points in each 3D column. The proposed method achieved high accuracy for height extraction with low Root Mean Square Error (RMSE) of 6.37 cm and Mean Absolute Error (MAE) of 5.07 cm. The canopy height monitoring window for winter wheat using this method starts from the beginning of the stem extension stage to the end of the heading stage (BBCH 31 to 65). Since the height of wheat has limited change after the heading stage, this method could be used to retrieve the crop height of winter wheat. In addition, this method only requires one operation of UAV in the field. It could be an effective method that can be widely used to help end-user to monitor their crops and support real-time decision making for farm management.

Validation of digital surface models (DSMs) retrieved from unmanned aerial vehicle (UAV) point clouds using geometrical information from shadows.

Theoretically, the appearance of shadows in aerial imagery is not desirable for researchers because it leads to errors in object classification and bias in the calculation of indices. In contrast, shadows contain useful geometrical information about the objects blocking the light. Several studies have focused on estimation of building heights in urban areas using the length of shadows. This type of information can be used to predict the population of a region, water demand, etc., in urban areas. With the emergence of unmanned aerial vehicles (UAVs) and the availability of high- to super-high-resolution imagery, the important questions relating to shadows have received more attention. Three-dimensional imagery generated using UAV-based photogrammetric techniques can be very useful, particularly in agricultural applications such as in the development of an empirical equation between biomass or yield and the geometrical information of canopies or crops. However, evaluating the accuracy of the canopy or crop height requires labor-intensive efforts. In contrast, the geometrical relationship between the length of the shadows and the crop or canopy height can be inversely solved using the shadow length measured. In this study, object heights retrieved from UAV point clouds are validated using the geometrical shadow information retrieved from three sets of high-resolution imagery captured by Utah State University's AggieAir UAV system. These flights were conducted in 2014 and 2015 over a commercial vineyard located in California for the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program. The results showed that, although this approach could be computationally expensive, it is faster than fieldwork and does not require an expensive and accurate instrument such as a real-time kinematic (RTK) GPS.

Mitigating the biodiversity footprint of energy crops – A case study on arthropod diversity

Rising demand for renewable resources has increased silage maize (Zea mays L.) production characterized by intensive soil management, high fertilizer and pesticide inputs as well as simplified crop rotations. Advantages of renewable biomass production may thus be cancelled out by adverse environmental effects. Perennial crops, like cup plant (Silphium perfoliatum L.), are said to benefit arthropods. Substituting silage maize could hence increase biodiversity and foster ecosystem services.This study aimed at comparing the attractiveness of both crops to arthropods, which are either flower-visiting or active in the crop canopy. Further, results were scaled to the landscape level to optimize crop partitioning concerning yields and species diversity.A field experiment with conventionally tilled annual and perennial no-tilled crops was established in 2015 near Munich (Germany). The crops chosen were insect-pollinated cup plant and wind-pollinated maize. Arthropods were sampled between June and September 2016. Four replicated UV-active pan traps, consisting of three bowls each, were used to catch arthropods at the actual crop height on five sampling dates. The collected arthropods were counted and taxonomically determined.In total 3810 individuals (Arachnida: 52; Insecta: 3758) from 9 orders (115 taxonomic groups) were collected. Silage maize mostly showed lower diversity values, indicating higher biodiversity in cup plant. However, the differences were small. Nevertheless, cup plant harbored more pollinators and parasitoids. Finding an optimal combination of both crops based on diversity gains is thus not straightforward. However, integrating cup plant to silage maize production systems allows increasing arthropod diversity by means of moderate yield reduction.

Irrigation Practices as Alternative Means of Supporting Rain-fed Agriculture: A Case Study of Potato (Solanum tuberosum L.)

Estimation of evapotranspiration is important for study, design, determining crop water requirement and management of irrigation systems. Also it’s important for determining irrigation water requirement during dry spell and water shortage i.e. when the evapotranspiration is greater than effective rainfall. Based on this, the study was conducted in Cheha district, Gurage Zone with determine crop water requirement of potato. In line to this, ten years climatological recorded data (2008-2017) for Indibir station on (sunshine duration hr /day), maximum and minimum temperature ( O C), humidity (%) and wind speed (km/day) at 2 meters height were used to determine ET o using Penman combination method. Secondary data were used to collect important soil parameters required for determination of crop water requirement. Lengths of growing periods, planting date and crop varieties data were received from the validation value of the local farmers and CDAO. Crop coefficients (kc), rooting depth, critical depletion fractions, yield response factors and crop height were obtained from food and agriculture organization of the United Nations guidelines (No. 56). The analyzed data indicated that reference crop evapotranspiration ranged from 2.40 to 4.73 mm with a mean of 3.56mm. The assessment has showed that the water requirement of potato is 63.2, 84.1, 145.8 and 77.2mm during initial, development, mid and late growth stages, respectively. The effective rainfall contribution throughout the growing stage of potato in the area is 8.5, 23, 187.2 and 158.1mm all through initial, development, mid and late growth stages, whereas the net irrigation requirement of potato throughout the dry spell period is 52.9, 61.3, 14.9 and 0mm in initial, development, mid and late growth stages, respectively. Soil and water conservation management practice, water harvesting technology and agronomic practices should be applied, principally mulching is very important to save soil moisture during high heat stress and dry spell or water shortage. Key terms: reference evapotranspiration, crop water requirement, potato DOI : 10.7176/JAAS/55-03 Publication date :May 31 st 2019

A functional diversity approach of crop sequences reveals that weed diversity and abundance show different responses to environmental variability

Abstract Combining several crop species and associated agricultural practices in a crop sequence has the potential to control weed abundance while promoting weed diversity in arable fields. However, how the variability in environmental conditions that arise from crop sequences affects weed diversity and abundance remains poorly understood, with most studies to‐date simply opposing weed communities in monoculture and in crop rotation. Here, we describe crop sequences along gradients of disturbance and resource variability using a crop functional trait and associated agricultural practices. We tested the hypothesis that in disturbances reduces weed abundance, whereas variability in resources promotes weed diversity. We used functional Hill's numbers to compute crop sequence functional diversity based on sowing date, herbicide spectrum and crop height—these are the respective proxies of disturbance timings, disturbance types and light availability. Using a large‐scale weed monitoring database, we assessed crop sequence diversity for 1,045 crop sequences of five consecutive cropping seasons. We computed weed richness and abundance at pluri‐annual (pool of weeds observed across five cropping seasons) and annual (pool of weeds observed during a winter cereal cropping season preceded by five cropping seasons) scales. We also accounted for herbicide and tillage intensities to test whether management intensity affects the response of weed diversity and abundance to crop sequence diversity. At the pluri‐annual scale, weed richness increased with the diversity of crop height and sowing date, whereas weed abundance decreased with sowing date diversity. Annual weed richness decreased with sowing date diversity, whereas annual weed abundance poorly relied on crop sequence diversity. Synthesis and applications. This study establishes a scientific basis for designing crop sequences according to specific weed management goals. We show that farmers may enhance arable weed diversity on a pluri‐annual scale by sequentially sowing crop species that differ in their competitive ability and sowing date. They may also achieve a better control of weed abundance by increasing the diversity of crop sowing dates across the crop sequence.

Effects of ameliorant and fertilizer on the growth and yield of maize grown in peatlands soil of West Kalimantan Indonesia

The use of agricultural lime ameliorant or rice husk charcoal combined with inorganic fertilizers is one of the agricultural intensification efforts in peatlands. This study aimed to find out the influence of various ameliorant types and nitrogen, phosphorus, and potassium inorganic fertilizer doses application on growth and yield of maize in peatlands soil was conducted in Siantan Hulu Village, Pontianak City, West Kalimantan used. This study used a split-plot design with the main plot of ameliorant types (A) consisting of three treatments i.e. without ameliorant (A0), agricultural lime of 3 t/ha (A1) and rice husk charcoal of 3 t/ha (A2). The subplot was inorganic fertilizer doses (B) consisting of three treatments i.e. B1 = 50% of N, P, and K inorganic fertilizers, B2 = 75% of N, P, and K inorganic fertilizer, and B3 = 100% of N, P, and K inorganic fertilizers. Observation on crop growth consisted of crop height, number of leaves, leaf area, crop total fresh weight, crop total dry weight, and crop growth rate. Yield observation consisted of ear length, ear diameter, 100-dry seed weight, seed yield weight per hectare, and harvest index (IP). The results of the study indicated that rice husk charcoal application of 3 t/ha gave seed yield weight of 7.25 t/ha that was higher than that of agricultural lime that produced 6.34 t/ha seed yield and without ameliorant that produced the lowest seed yield of 4.18 t/ha. Application of N, P, and K inorganic fertilizer dose of 75% produced an insignificant difference seed yield compared to the dose of 100%, which were 6.32 t/ha and 6.69 t/ha, respectively. Therefore, the application of N, P, and K inorganic fertilizer dose of 75% is recommended as a basic of maize fertilization.

Tolerance of flax (Linum usitatissimum) to fluthiacet-methyl, pyroxasulfone, and topramezone

AbstractFlax yield can be severely reduced by weeds. The combination of limited herbicide options and the spread of herbicide-resistant weeds across the prairies has resulted in a need for more weed control options for flax producers. The objective of this research was to evaluate the tolerance of flax to topramezone, pyroxasulfone, flumioxazin, and fluthiacet-methyl applied alone as well as in a mix with currently registered herbicides. These herbicides were applied alone and in mixtures at the 1X and 2X rates and compared with three industry standards and one nontreated control. This experiment was conducted at Carman, MB, and Saskatoon, SK, as a randomized complete block with four replications. Data were collected for crop population, crop height, yield, and thousand-seed weight. Ratings for crop damage (phytotoxicity) were also taken at three separate time intervals: 7 to 14, 21 to 28, and 56+ d after treatment. Crop tolerance to these herbicides varied between site-years. This was largely attributed to differences in spring moisture conditions and the differences in soil characteristics between sites. Herbicide injury was transient. Hence, no herbicide or combination of herbicides significantly impacted crop yield consistently. Flumioxazin was the least promising herbicide evaluated, as it caused severe crop damage (>90%) when conditions were conducive. Overall, flax had excellent tolerance to fluthiacet-methyl, pyroxasulfone, and topramezone. Flax had excellent crop safety to the combination of pyroxasulfone + sulfentrazone. However, mixing fluthiacet-methyl and topramezone with MCPA and bromoxynil, respectively, increased crop damage and would not be recommended.

Sunflower Type Influences Yield Prediction using Active Optical Sensors

Core Ideas Confection sunflower yield was related to active optical sensor readings. Oilseed sunflower yield was not related to active optical sensor readings. Oilseed sunflower yield was related to crop height measurements. Active‐optical (AO) sensors have been used in several crops as a yield‐prediction tool for N management, but not in sunflower (Helianthus annuus). The need for in‐season N and its rate can be determined through using a yield and AO relationship. By comparing predicted yield from an area of sufficient N to another area of the field, the yield difference multiplied by the N required for the additional yield results in the fertilizer N rate. This study was conducted to determine what parameters, including plant height and plant stand, would be most useful in relating AO sensor readings to sunflower yield. The experiments were conducted in 2015 and 2016 on a total of 20 locations in North Dakota. The experimental design was a split‐plot randomized complete block, with six N rates as the main plot treatments and P rate (four in 2015 and two in 2016) as split plot treatment. Since P had no influence on yield, it was ignored in this study. The AO sensors were the GreenSeeker and Holland Crop Circle. The AO sensors were used when the sunflower was at the V6 and V12 growth stages. Manual height and an acoustic height sensor were used on most sites at the time of AO sensor readings. Sensor readings with and without consideration of crop height were subjected to regression analysis with crop yield. The AO sensor readings were related to confection sunflower yield, but not oilseed sunflower yield. Oilseed sunflower yield was most related to crop height.

Design of rice intelligent water-saving irrigation system based on agricultural internet of things

In order to realize the real-time remote monitoring and accurate management of the paddy field environment, the intelligent water-saving irrigation system based on the agricultural Internet of things was designed. The data packet consists of water level, soil moisture, soil fertilizer, crop height, real scene photos and so on, which are collected by the terminal monitoring equipment group, and is forwarded to the gateway through the main controller. The gateway transmits the processed data packets to the cloud server through GPRS, and then sends to the user app or the Internet web page. App and the internet can set the upper and lower threshold of the terminal node water level. According to the comparison results between the water level and the threshold set by the water level sensor, the node solenoid valve is controlled to open or close the gate of the rice field intake, and the automatic irrigation is realized. The system can set a fixed number for each monitoring node to find fault units quickly and enhance system reliability. The system gets the advantages of simple implementation, low power consumption, perfect function, and high reliability.

Caracterización y diferenciación de cafés, a partir de espectroscopía infrarroja

Coffee is the second most consumed beverage in the world after water, the Colombian coffee production contributes with 9% of total world production and Colombian coffee is recognized by quality and mild coffee. Today, there is not enough evidence on the influence of altitude in sensory quality and coffee chemical composition. In this sense, we sought to characterize and differentiate coffees by infrared spectrum analysis (FTIR) and sensory evaluation. 62 specialty coffees samples were harvested at different altitudes, obtained in two harvest periods. The spectra obtained allowed finding differentiation in the peaks associated with chlorogenic acids (1600-1650cm-1) between green and roasted coffee beans, although no differences were observed in the peaks according to the harvest period; by itself. The sensory evaluation, according to the SCA methodology, 2015 did not generate statistically significant differences between harvest periods and evaluated varieties. When jointly considering the sensory analysis and the infrared spectrum analysis, there were statistically significant differences between harvest periods, attributable to the caffeine content and the total cup score. The results found show that there is no correlation between the height of the coffee crop and the final quality of the beverage.