Estimating the mass of mango fruit (Mangifera indica, cv. Chok Anan) from its geometric dimensions by optical measurement

Uniform fruit mass and shapes of mangoes for export are required in order to ease handling and transportation, and to help satisfy consumer preferences. However, with its irregular shape, one which cannot be approximated by using standard geometrical figures, the mango is not as easy to model as round or oval-shaped fruits.In this study, more than 1000 mango ‘Chok Anan’ fruit were measured with respect to their length, maximum width and maximum thickness, to within an accuracy of 1.0  mm, and their weight was determined to within an accuracy of 0.1  g. Pictures were taken of 30 fruit, through the use of digital cameras, manually rectified and analyzed by use of “Measure 2.1” a computer code.An equation was proposed in order to calculate the mass of the mangoes based on three geometric dimensions, which then showed a high level of explanatory power of R² = 0.97. The root mean standard error of 12.22 was determined, and the mean relative deviation found was 0.05. Based on measurements taken from the digital photos, the equation was then used to determine the estimated mass based on three dimensions. Estimated and measured values were plotted against each other. A high correlation (R² = 0.96) was found between measured and calculated mass.It was shown that the mass can be estimated based on data obtained from two orthogonally taken photographs.     

Estimating the variability of tillage forces on a chisel plough shank by modeling the variability of tillage system parameters

In this paper, a probabilistic approach is proposed for quantifying the variability of the tillage forces for the shank of a chisel plough with narrow tines and to estimate the failure probability. An existing three-dimensional analytical model of tool forces from McKyes was used to model the interaction between the tillage tools and the soil. The variability of tillage forces was modeled, taking into account the variability of soil engineering properties, tool design parameters and operational conditions. The variability of the soil engineering properties was modeled by means of experimental observations. The dispersion effect of each tillage system parameter on the tillage forces was determined by a sensitivity analysis. The results show that the variability of the horizontal and vertical forces follows a lognormal distribution (μ = 0.872, ξ = 0.449; μ = 0.004, ξ = 0.447) and the relationship between these forces is positive and quasi-linear (ρ(P_H, P_v) = 0.93).This lognormal variability was integrated into the estimation of the failure probability for the shank by using Monte Carlo simulation (MCS) and the first-order reliability method (FORM). The results obtained by these two methods, with the assumption of non-correlation between the horizontal and vertical forces, were almost identical. However, the FORM method was faster and simpler, compared to the MCS technique. Furthermore, the correlation between the horizontal and vertical forces has no significant effect on the failure probability, regardless of the correlation strength. Therefore, it is concluded that the FORM method can be used to estimate the failure probability without considering the correlation between horizontal and vertical forces.     

Assessment of forage mass from grassland swards by height measurement using an ultrasonic sensor

The non-destructive assessment of forage mass in legume-grass mixtures as a tool for yield mapping in precision farming applications has been investigated in two field experiments. An ultrasonic sensor was used to determine sward heights. Forage mass-height relationships were evaluated by carrying out static measurements on binary legume-grass mixtures of white clover (Trifolium repens L.), red clover (Trifolium pratense L.), and lucerne (Medicago sativa L.) with perennial rye grass (Lolium perenne L.) across a wide range of sward heights (5.0-104.2 cm) and forage mass (0.15-11.25 t ha⁻¹). Mobile measurements, hereafter referred to as “on-the-go” were conducted by mounting the ultrasonic sensor in combination with a high-precision Differential Global Positioning System (DGPS) on a vehicle. Data were recorded along experimental plots consisting of perennial rye grass and grass-clover mixtures similar to the mixtures that were used for the static experiment. The static experiment revealed a relationship between ultrasonic sward height and forage mass explaining 74.8% of the variance with a standard error (SE) of 1.05 t ha⁻¹ in a common dataset. The type of legume species, weed proportion, and growth period had a significant impact on the above mentioned relationship. Legume-specific regression functions had higher R²-values of up to 0.855 (white clover mixture). Datasets including legume-specific mixtures and pure swards of both components reached comparable R² values between 0.799 and 0.818 but exhibited higher SE values. The abundance of weeds resulted in increased ultrasonic sward heights for the same levels of forage mass. On-the-go measurements across experimental field plots yielded a sward height range of 1.4-70.4 cm. Abrupt forage mass changes at the transition from treatment plots to cut interspaces resulted in a significant deviation from stubble height within a distance of 50 cm to plot borders. When legume-specific equations derived from static measurements were applied to sward heights, forage mass was overestimated by 21.4% on average. Mean residuals from predicted forage mass ranged between 0.893 (pure grass) and 1.672 (red clover mixture) and increased significantly if the point sampling distance along the track was increased to more than 0.82 m on average across all plots. The prediction accuracy of forage mass from ultrasonic height measurements is promising; however, further modifications to the technique are necessary. One such improvement can be the use of spectral reflectance signatures in combination with the ultrasonic sensor.     

Use of ground based hyperspectral remote sensing for detection of stress in cotton caused by leafhopper (Hemiptera: Cicadellidae)

Detection of crop stress is one of the major applications of hyperspectral remote sensing in agriculture. Many studies have demonstrated the capability of remote sensing techniques for detection of nutrient stress on cotton with only few on pest damage but none so far on leafhopper (LH) severity. Subsequent to introduction of Bt cotton, leafhopper is emerging as a key pest in several countries. In view of its wide host range, geographical distribution and damage potential, a study was initiated to characterise leafhopper stress on cotton, identify sensitive bands, and derive hyperspectral vegetation indices specific to this pest. Cotton plants with varying levels of LH severity were selected from three locations across major cotton growing regions of India. About 57-58 cotton plants from each location exhibiting different levels of LH damage symptoms were selected. Reflectance measurements in the spectral range of 350-2500 nm were made using hyperspectral radiometer. Simultaneously chlorophyll (Chl) and relative water content (RWC) were also estimated from the selected plants. Reflectance from healthy and leafhopper infested plants showed a significant difference in VIS and NIR regions. Decrease in Chl a pigment was more significant than Chl b in the infested plants and the ratio of Chl a/b showed a decreasing trend with increase in LH severity. Regression analysis revealed a significant linear relation between LH severity and Chl (R² = 0.505^∗∗), and a similar fit was also observed for RWC (R² = 0.402^∗∗). Plotting linear intensity curves between reflectance at each waveband with infestation grade resulted in six sensitive bands that exhibited maximum correlation at different regions of the electromagnetic spectrum (376, 496, 691, 761, 1124 and 1457 nm). Regression analysis of several ratio indices formulated with two or more of these sensitive bands led to the identification of new leaf hopper indices (LHI) with a potential to detect leafhopper severity. These new indices along with 20 other stress related hyperspectral indices compiled from literature were further tested for their ability to detect LH severity. Two novel indices LHI 2 and LHI 4 proposed in this study showed significantly high coefficients of determination across locations (R² range 0.521 to 0.825^∗∗) and hence have the potential use for detection of leafhopper severity in cotton.     

Digital image analysis to estimate the live weight of broiler

Computer assisted digital image analysis was performed to investigate the possibility of estimating body weight of live broiler. To achieve the stated objective, 100 Arbor acres broiler chicks were reared under standard rearing condition and 1200 digital images were captured from 20 randomly selected broilers during the 7-42 days growing period. The captured images were analyzed by raster image analysis software (IDRISI 32) to determine the broiler body surface area and developed a linear equation to estimate weights of the broiler from its body surface-area pixels. The developed weight predicted equation based on surface-area pixels was log W = 1.060406(log P) + 0.173756(log A) − 2.029268 (W = estimated body weight, P = surface-area pixels and A = age at weighing) and the degree of goodness of fit of this equation was 0.999. The relative error in weight estimation of broiler chicken by image analysis, expressed in terms of percent error of the residuals from surface-area pixels was in between 0.04 and 16.47. On the other hand, the estimated body weights were not significantly (p > 0.05) difference from manually measured body weights up to 35 days of age. Thus, the development of a practical imaging system for weighing live broiler is feasible.     

Quantitative analysis of minerals and electric conductivity of red grape homogenates by near infrared reflectance spectroscopy

The use of near infrared (NIR) reflectance spectroscopy to measure the concentration of minerals and electric conductivity (EC) in red grape homogenates was investigated. Wine grape samples (n = 209) from two vintages, representing a wide range of varieties and regions were analysed by Inductively Coupled Plasma Optical Emission Spectrometry (ICPOES) for the concentrations of calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), sulphur (S), iron (Fe), and manganese (Mn) and scanned in reflectance in a NIR instrument (400-2500 nm). The spectra were pre-processed using multiple scatter correction (MSC) before developing the calibration models using partial least squares (PLS) regression and cross validation. Coefficients of determination in cross validation (R²) and the standard errors of cross validation (SECV) obtained were for Fe (0.60 and 1.49 mg kg⁻¹), Mn (0.71 and 0.41 mg kg⁻¹), Ca (0.75 and 60.89 mg kg⁻¹), Mg (0.84 and 12.93 mg kg⁻¹), K (0.78 and 285.34 mg kg⁻¹), P (0.70 and 40.19 mg kg⁻¹), S (0.88 and 14.45 mg kg⁻¹) and EC (0.87 and 7.66 mS). The results showed that Mg, S and EC in grape berries might be measured by NIR reflectance spectroscopy.     

Extended-altitude, aerial mapping of crop NDVI using an active optical sensor: A case study using a Raptor™ sensor over wheat

Recently reported testing of active, optical crop sensors in low-level aircraft have demonstrated a new class of airborne sensing system that can be deployed under any ambient illumination conditions, including at night. A second-generation, high-powered, light-emitting diode system has been assembled and tested over a 80 ha field of wheat (Triticum aestevum) by mapping the normalised difference vegetation index (NDVI) at altitudes ranging from 15 to 45 m above the canopy; significantly higher altitudes than existing systems. Comparisons with a detailed on-ground NDVI survey indicated the aerial sensor values were highly correlated to the on-ground sensor (0.79 < R² < 0.85), with close to unity slope and zero offset. The maximum average deviation between aerial and on-ground NDVI values was 0.04. Sample calculations involving two exemplar algorithms, one for estimating monoculture pasture biomass and the other for estimating wheat yield, indicate such deviations to have no significant effect on prediction accuracy. The subsequent NDVI maps proved to be invariant to sensor height over the 15-45 m altitude range meaning this new sensor configuration can be deployed over undulating crops and pastures and in areas with nearby obstacles such as trees and buildings.     

A web-based model for simulating whole-farm beef cattle systems

This paper details the rationale and procedures included in a web-based simulator containing production of beef cattle and cash crops. All biophysical and economical definitions including management in terms of rules constitute user-defined scenarios, which can be saved, retrieved, modified and deleted. Herbage growth may be either provided by the user or estimated from daily climate information. Scenarios are simulated and their outcomes are sent to the user's e-mail as a spreadsheet file, including data and pre-designed graphs to facilitate the interpretation of results. An example simulation study of a grazing-based finishing beef steers with a cycle of 12 months is presented, where new weaners enter the system in the autumn. Increased stocking rates, SR (150, 170, 190 and 210 heads in a 100-ha farm) and different summer maize feeding (SMF) rates were compared (SMF₀ = control and SMF₁ = intermittent rule-driven maize feeding during summer). In this simulation study, “deviations” from user-defined targets are simplified into two associated rules (a) average farm herbage mass deviation to adjust herbage allowance, and (b) target animal live weight deviation, associated to SMF₁. The proportion of unfinished steers at 28th February increased linearly (p ≤ 0.01) with higher stocking rates and became zero at any stocking rate where the SMF rule was operating (SMF₁). The economic response of SR × SMF interaction was significant for gross margin, indicating a positive linear association (p ≤ 0.05) of SMF₁ treatment (rule activated) when SR increases. The potential use of the web simulator as a flexible tool for investigation, training and decision making are discussed.     

The vegetation classification in coal mine overburden dump using canopy spectral reflectance

The canopy spectral characteristics of typical plants in the overburden of the Fuxin coal mine dump were measured and analyzed. The reflectance of Leymus chinensis was affected by the soil, with a slight shift from green (550 nm) to the near infrared (NIR) region. Changes in chlorophyll and water absorption were not significant in the red (670 nm) and NIR bands, respectively. The reflectance curve trend for Artemisia lavandulaefolia was similar to those of Sophora japonica and Ulmus pumila, while the reflectance of S. japonica and U. pumila fluctuated in the NIR region (760-1200 nm), especially with greater water absorption around 930 and 1120 nm. In contrast, the reflectance of A. lavandulaefolia fluctuated slightly around 930 nm and a significant peak appeared at 1127 nm. In addition, the spectral reflectance of S. japonica was lower than for the other species in the visible band (400-700 nm). However, it was higher than for L. chinensis in the NIR region (780-1200 nm). Three classifiers, the self-organizing map (SOM), learning-vector quantization (LVQ), and a probabilistic neural network (PNN), were used to classify the vegetation and the results of all classifiers were compared based on total spectral reflectance data from 400 to 1200 nm. The PNN was the best classifier in terms of training and testing accuracy. The first difference reflectance was calculated, and the red edge parameter was able to classify the herbs (L. chinensis and A. lavandulaefolia) and the arbores (S. japonica and U. pumila) with an accuracy of 77 and 84%, respectively, although it did not perform as well for detail species. A mixing parameter matrix was built based on the sensitive wavelengths (550, 674, 810, 935, and 1125 nm), the vegetation indices (SAVI and NDGI), and the water absorption slope. High classification accuracy was obtained by applying the mixing parameter matrix. This method could be used for revegetation monitoring and in decision making.     

The Estimation of Soil Trace Elements Distribution and Soil-Plant-Animal Continuum in Relation to Trace Elements Status of Sheep in Huangcheng Area of Qilian Mountain Grassland,China

The purpose of the present study was to survey contents of trace elements of Cu, Mn, Fe, and Zn in the surface layer (0-20 cm) in the soil, pasture and serum of sheep in Huangcheng area of Qilian mountain grassland, China. Also the soil-plant-animal continuum was analyzed. Soil (n=300), pasture (n=60), and blood serum samples from sheep (n=480) were collected from Huangcheng area of Qilian mountain grassland, China. The contents of trace element in the samples were analyzed by atomic absorption spectrophotometer after digestion. The soil trace elements density distribution shows a ladder-like pattern distribution. Equations developed in the present study for prediction of Fe (R²=0.943) and Zn (R²=0.882) had significant R² values.