Optimum Harvest Date Research Articles

HARVEST MATURITY RELATED CHANGES AND THEIR INFLUENCE ON ANTIOXIDANT POTENTIAL IN ´GOLDEN SMOOTHEE´ APPLES

Changes in non-enzymatic antioxidant potential (DPPH, ascorbate content) and in enzymatic antioxidant potential (SOD, CAT and POX activity) were assessed in 'Golden Smoothee' apples in relation to harvest date. Fruits were harvested six times on a weekly basis (from 18 th august to 22 nd September) from two different orchards in the Lleida area (Spain). Changes in antioxidants were related to changes in maturity indexes for each orchard. The main purposes of the study were to investigate whether a delay in harvest date caused an increase in the level of active oxygen scavenging activity and to establish the optimal harvest date in order to maximise antioxidant potential and thereby improve fruit quality during postharvest storage. Total antioxidant potential increased significantly with increasing maturity for each orchard. In contrast, ascorbate levels remained stable during the first four weeks and then decrease during the last two weeks. This opposite behaviour of ascorbate and total antioxidant potential showed that ascorbate alone was not the most important antioxidant compound for determining the total antioxidant potential of the fruit. Others compounds such as phenols are involved and it is likely that changes in the solubility of these compounds during on-tree ripening which determine the apple total antioxidant potential. Changes in enzymatic antioxidant potential paralleled those of ascorbate, a result that showed the direct relationship between non-enzymatic and enzymatic antioxidant potential.

PREDICTING HARVEST LABOUR ALLOCATION IN BELL PEPPER PRODUCTION

In the production of tomatoes in greenhouses, a more or less constant number of tomatoes are ready for picking at each harvest time. In the production of bell peppers, however, large fluctuations exist in number of fruits ready to pick. This major problem in bell pepper production is called `flushing?: weeks with high yields are alternated by weeks with low yield. This irregular harvest pattern makes it difficult for growers to meet regular weekly demands. As this cyclic production pattern is more or less the same for all growers, it results in weeks with a high market supply and low prices alternating with weeks with a low market supply and high prices. Flushing also results in strong fluctuations in labour demand in the greenhouses. Hence, avoiding an irregular pattern of sweet pepper production is of great economic importance. Flushing makes it very difficult for the growers to allocate sufficient labour force at a certain time in production. Both allocating too many and too few pickers will have financial consequences for the grower. The aim of this study is to predict the optimal harvest date based on repeated colour measurements of the growing bell peppers. The fruit ripening of bell peppers has been followed by colour imaging in the greenhouse. A commercial digital camera was used to record the development of colour for two cultivars of bell peppers over time. The images were analysed by image processing to obtain the R, G and B values. At the same time the time to harvest was recorded for the same fruits. Using these data a model was developed, on the basis of an exponential function towards a fixed asymptotic end value, to describe the colour development during fruit growth in terms of R/G ratio and to predict the optimal harvest date of the fruits.

Texture changes of vegetable cultivars measured by non-destructive methods

According to our experiments the tested group of non-destructive methods offers a useful tool not only to follow the texture changes of vegetables during storage but to characterize the firmness and vision parameters during the growing period as well. Advantages of these methods are: they are mobile, easy to set up, easy to use and quick. The suitable maturity state — and so the optimum harvest date also - can be determined by these methods. In addition, these methods can be built into sorting lines making possible to sort and classify great amounts of produces. These methods help the producer to offer homogenous products of controlled quality. They can be used for measuring different effects on vegetable's quality parameters (fertilization by different microelements, different irrigation effects on the product) as well.

Spectral Measurements on ‘Elstar’ Apples during Fruit Development on the Tree

Monitoring of apple fruit development on the tree is necessary for determination of optimum harvest date. The current method is to pick several times during fruit development fruit samples and to analyse them in a destructive way. Sufficient experience is necessary to correctly interpret the results of analyses. Appreciable errors can occur, if an apple cultivar shows high variability in fruit maturation. However, reduction of errors by taking enlarged samples is not viable. More reliable results could be expected if non-destructive continuous monitoring of the same fruits during fruit development on tree would be possible. Measurements of fruit ripening on the tree were carried out by using portable equipment with a miniaturised spectrophotometric module. By means of a specific glass-fibre probe, the partial light transmittance through fruit was detected in wavelength range from 500 to 1000 nm. Tests were performed on ‘Elstar’ apples in a commercial orchard during pre-harvest and harvest period 2003. From the spectral data, different indices were derived to characterise the fruit pigment change and maturity progress in comparison with conventional laboratory analyses for fruit maturity analysis. The portable spectrophotometer worked reliably and indicated sensitively changes of the spectral signature of apple fruit during the measuring period. Spectral indices as well as laboratory data demonstrated very high variance of maturity progress between individual ‘Elstar’ fruits. The spectral indices of each single fruit changed continuously over the time. The red-edge as well as a normalised chlorophyll index exhibited moderate decline, while a normalised anthocyanin index increased sigmoidally. The results obtained with these indices showed the potential of non-destructive fruit maturity monitoring on the tree.

Effect of Harvest Time and Drying Method on Biomass Production, Essential Oil Yield, and Quality of Peppermint (Mentha × piperita L.)

In the period from 2000 to 2002, studies on peppermint (Mentha x piperita) herb and essential oil (EO) production have been conducted at Planteforsk, Apelsvoll Research Centre Div. Kise in Norway. The trials were aimed at finding the optimal harvest date and suitable drying methods to maximize EO yield and to obtain a desirable oil quality. Peppermint plants from the first production year (2000 and 2001) and the second production year (2002) were harvested during flowering at three developmental stages (early, full, and late bloom). Biomass and leaf production were recorded, and the water content of the plant material was detected after the application of different drying methods: instantaneous drying at 30, 50, and 70 degrees C and prewilting (ground drying) for 1 or 5 days followed by final drying at 30 degrees C. Finally, plant samples were transferred to The Plant Biocentre at NTNU, Trondheim, Norway, for hydrodistillation and gas chromatography-mass spectrometry (GC-MS) analyses of the EOs. Peppermint oil yield increased from early to full bloom and late bloom (average of all years and drying methods except for 50 and 70 degrees C: 2.95, 4.13 and 4.20 L/daa, respectively) as an effect of biomass production and leaf growth. The flavor-impact compounds, menthol and menthone, reached their optimum at full bloom (43-54 and 12-30%, respectively). Prewilting led to slight decreased EO levels after 1 day (7.7%) and 5 days of ground drying (1.5%) and no EO quality changes, compared to direct drying at 30 degrees C. The plant weight (H2O content) was drastically decreased to the average under 80 and 45% in all years, thus reducing the energy supply and costs for the necessary final drying step.

A new harvest time prognosis tool for forage maize production in Germany

Optimum harvest date of silage maize is crucial for exploiting the yield and forage quality potential of the crop, and for minimising losses during silage storage and the feedout phase. Simulation models are a useful tool for determining this optimal date. While numerous models are available for yield and some for quality, no comprehensive model deals simultaneously with yield and quality. The current project aims to fill this gap by (i) adapting the grass model FOPROQ to growth and quality of silage maize, and (ii) calibrating and validating the model for dry matter (DM) yield, DM content, and starch content. This allowed subsequently (iii) to perform a long-term simulation study for quantifying the climatic risk of silage maize grown under the marginal conditions of Northern Germany. Calibration was based on a field trial conducted at four sites over 3 years (1998–2000) in Germany, including six cultivars covering a wide range of maturity classes (early to mid-late) and maturity types (normal, dry-down, stay-green). Samples were taken every 2 weeks over the vegetation period. Validation was based on an independent data set collected during two years (2001, 2002) at two sites, however, with only one cultivar. No changes of algorithms were necessary to adapt the grass model to forage maize. Calibration results showed good agreement between observed and calculated data (RMSE values of 153.8 g DM m −2 for DM yield, 26.8 g DM kg −1fresh weight for DM content, and 33.5 g kg −1 DM for starch content). For severe drought stress situations the validation revealed some discrepancies between observed and simulated starch content. Model refinements by implementing environmental response as a function of developmental stage and by broadening the calibration database are discussed. A 25-year (1979–2003) simulation study was conducted for one mid-early and two early cultivars at Kiel, Northern Germany. The simulation results were in good agreement with corresponding regional mean values for DM content and starch content of maize silage samples. A climatic risk analysis for this long-term simulation showed a substantial likelihood of failure to reach silage maturity, with failure rates between 44 and 64% depending on cultivar. The last decade (1994–2003), characterised by considerable temperature increase, showed somewhat lower failure rates. The reliable results presented in this study support current efforts to develop FOPROQ into a harvest time prognosis tool for Germany.

The effect of genotype, environment and time of harvest on sugarcane yields in Florida, USA

Sugarcane ( Saccharum spp.) is grown across different production environments and is harvested over a 5-month (mid-October–mid-March) period in Florida. While many studies have examined genotype × environment interactions and their implications for breeding program design, knowledge is limited regarding interactions of genotype, environment and time of harvest and their implications for growers. Three non-confounded data sets (“case studies”) were analyzed to determine the effects of these three factors on kilograms of sugar per ton (KST), tons of cane per hectare (TCH) and tons of sugar per hectare (TSH) for recently released cultivars in south Florida. Cultivar (genotype), environment, time of harvest and their interactions had significant effects on KST, TCH and TSH. Sugarcane KST and TSH were reduced by 28 and 29%, respectively, when harvested in mid-October compared to optimum harvest dates in February. TSH varied from 2 to 46% across environments. The Lakeview “warmland” site near Lake Okeechobee recorded significantly higher TCH and TSH than other sites, and cultivars CP88-1508 and CP88-1834 recorded higher relative yields at Lakeview. Cultivar TSH varied up to 51% across the case studies. CP89-2143 had significantly higher KST than other cultivars in all 21 pairwise comparisons in the three case studies, and a remarkably high, stable KST ranking across environments. Growers in the Everglades Agricultural Area interested in improving sugarcane crop sucrose concentration should plant CP89-2143. However, significant genotype × environment interactions for other cultivars support continued multi-locational evaluation of sugarcane germplasm both during the breeding program and following cultivar release.

Evaluation of an electronic nose to assess fruit ripeness

The main goal of our study was to see whether an artificial olfactory system can be used as a nondestructive instrument to measure fruit maturity. In order to make an objective comparison, samples measured with our electronic nose prototype were later characterized using fruit quality techniques. The cultivars chosen for the study were peaches, nectarines, apples, and pears. With peaches and nectarines, a PCA analysis on the electronic nose measurements helped to guess optimal harvest dates that were in good agreement with the ones obtained with fruit quality techniques. A good correlation between sensor signals and some fruit quality indicators was also found. With pears, the study addressed the possibility of classifying samples regarding their ripeness state after different cold storage and shelf-life periods. A PCA analysis showed good separation between samples measured after a shelf-life period of seven days and samples with four or less days. Finally, the electronic nose monitored the shelf-life ripening of apples. A good correlation between electronic nose signals and firmness, starch index, and acidity parameters was found. These results prove that electronic noses have the potential of becoming a reliable instrument to assess fruit ripeness.

Taste Panel Perception of Sweetness and Sweetness Acceptability Compared to High Pressure Liquid Chromatography Analysis of Sucrose and Total Sugars Among Three Phenotypes (su, se, and sh2) at Varying Maturities of Fresh Sweet Corn

Increased value of fresh sweet corn (Zea mays) during the last decade has lead to increased interest into the characteristics that increase marketability. Sweetness was examined over three phenotypes (su, se, and sh2) to determine if there was an optimum phenotype or cultivar within a phenotype. Each phenotype was isolated to prevent cross-pollinization. Cultivars were grown on sandy loam soil located at the Clemson University Coastal Research and Education Center (Charleston, S.C.). Early, mature, and late harvest dates were also evaluated to determine the optimal harvest date(s) for maximum flavor. High performance liquid chromatography was used to determine sucrose, fructose, glucose, and total sugars. Panelists' evaluation of sweetness and its acceptability significantly correlated with the high performance liquid chromatography analysis for sucrose and total sugars (sweetness, R = 0.70 and 0.61; acceptability, R = 0.64 and 0.55). Sucrose correlated with the total sugars (R = 0.95). As maturity increased, the ability of the taste panel to identify differences in phenotypes also increased. Although sucrose and total sugar levels were different between se, sh2, and su, taste panelists indicated no difference between se and sh2. Sh2 cultivars were considered sweet and acceptable on all harvest dates, but su was only acceptable to panelists at early maturity.

Effect of natural variability among apples on the accuracy of VIS-NIR calibration models for optimal harvest date predictions

The prediction of the optimal harvest date of apples is of high importance as it controls the fruit quality after long-term storage in cooled and modified atmosphere conditions. As the present methodology to determine these dates is very time-consuming, the use of visible and near infrared (VIS-NIR) spectroscopy was examined to speed up the measurements. The root mean square error of prediction (RMSEP) of the near-infrared calibration models for the prediction of the optimal harvest date of individual fruit ranged, depending on the cultivar, from 5 to 9 days. In practice, the average prediction values of sample batches are used to predict optimal harvest dates of individual orchards rather than on a per fruit basis, and the accuracy of the calibration models then increases considerably. The accuracy of the calibration models to predict the optimal harvest date relative to the natural variability of the maturity of individual fruit has been assessed based on an analysis of the per fruit Streif index, a maturity index. The standard deviation of the physiological maturity defined as the days until the optimal picking date ranged from 2 to 8 days in 1999 and from 5 to 12 days in 2000 and was, therefore, of the same order of magnitude as the RMSEP of the VIS-NIR calibration models. As expected, the accuracy of the calibration models was better when the natural variability of the maturity between fruit was small and vice versa. The calibration models for Streif index were not very accurate, even after applying a logarithmic transformation.

수확시기가 사료용 벼의 초장, 건물수량 및 사료성분에 미치는 영향

Recently, there has been a growing tendency to use whole crop rice for feeds as there is an increased rice supply and a decrease in the demand for rice in Korea. Little information, however, is available about the management and utilization of whole crop rice for feeds. This study was conducted to decide the optimum harvest date through examining the plant height, dry matter(DM) yield and feed composition of whole crop rice harvested at different maturity. Field study was established early in May until October 7th on a rice field at Yupori, Sinbuk-yeup, Chunchon, Kangwon-Do. "Ilpum" mutant rice was sown at 52 kg/ha, and N, P and K were applied at 209, 113 and 81 kg/ha, respectively. The rice was harvested at six different mature stages for analysis; booting stage; 17 Aug., milk-ripe stage; 27 Aug., dough stage; 7 Sep., yellow ripe stage; 17 Sep., dead ripe stage; 27 Sep. and full ripe stage; 7 Oct. Plant height was 77 cm in booting stage (P<0.05) which was lower when compared to the other stages among which the heights did not differ with average range of 93∼97 cm. The highest dry matter yield was observed in yellow ripe stage (22.8 T/ha), which was followed by dead ripe stage (19.3 T/ha), full ripe stage (19.3 T/ha), and dough stage (15.1 T/ha). Crude protein (CP) and Neutral detergent fiber (NDF) concentrations consistently decreased with maturity. The highest concentrations of CP and NDF were obtained in booting stage with 9 and 73.6%, respectively (P<0.05), and lowest in full ripe stage with 5.8 and 64.6%, respectively (P<0.05). The concentration of total digestible nutrient (TDN) was highest in booting stage (59.7%); however no significant difference was found among other stages. The concentrations of Ca and P were not different among mature stages. According to these results, the yellow ripe period is appropriate to harvest the whole crop rice for forage considering dry matter yields, feed compositions and TDN concentrations.

Prediction of optimal harvest date for processing tomato based on the accumulation of daily heat units over the fruit ripening period

SummaryFor maximum yield of processing tomato by once-over mechanical harvesting, an optimum date for harvest has to be selected at the time when the factory-graded fruit yield is at its maximum. By recording the proportion of green, ripe (i.e. turning and red) and rotten (i.e. over-ripe and damaged) fruit over a period of about 20 d, the optimal harvest date can be identified. Based on observations taken from crops at four sites in the Mediterranean region over three years (1997-1999), the proportional change of fruit types (i.e. percentage total fruit weight) has been found closely related to the accumulation of daily maximum temperature (x, °Cd) during crop maturation. The change of percentage green fruit was y = 6172 l0–8 x2 – 768 l0–4 x + 25 (R2 = 0.882). Over the same period, the change in percentage ripe fruit was described less satisfactorily by y = – 12588 l0–8 x2 + 867 l0–4 x + 65.7 (R2 = 0.568). When heat units were calculated based on the daily maximum and minimum temperatures by six well-known methods, it was found that the reduction in percentage green fruit was significantly related to the sum of heat units calculated by all methods. The maximum percentage ripe fruit, about 80% of the total fruit weight, occurred soon after the percentage green fruit was equal to the percentage rotten fruit, both around 10% of total fruit weight.Therefore, the heat units required to reduce the green fruit from 25% to 10% of total fruit weight, calculated by different methods, can be used to predict accurately the optimal harvest date based on the accumulation of ambient temperature. In a range of likely temperature regimes, 7–9 days prediction for optimal harvest date can be made. However, the simplest method based on daily maximum temperature alone is as accurate as all the more complex methods and is likely to find wider application in the processing tomato industry.

THE IMPORTANCE OF MULTIPLE DESTRUCTIVE HARVESTS ON YIELD ESTIMATION OF PROCESSING TOMATO FIELD TRIALS

In earlier studies we demonstrated how the yield of factory grade (red ripe) fruit followed a normal distribution over time. This emphasizes the importance of selecting the optimum harvest date for once-over harvesting if maximum factory yield is to be achieved. These studies emphasize the importance of taking a number of successive (destructive) harvests, if a true estimate of the yield potential of different cultivars is to be obtained. A similar need also occurs with different agronomic treatments (e.g. fertilizer levels, or irrigation treatments), which may modify the maturity characteristics of the treatment. Some doubt has been expressed on the relevance of such studies in arid environments, but data is presented from California to show that the model is equally applicable irrespective of environment. With the increasing interest in lycopene it would also be highly desirable to monitor how these levels (and pH, acidity and °Brix) are influenced by harvest date, agronomic treatment (and of course cultivar).

Electronic nose as a non-destructive tool to evaluate the optimal harvest date of apples

An electronic nose (E-nose) has been evaluated for use as a tool to predict the optimal harvest date of apples (Malus domestica Borkh.). The volatiles of ‘Jonagold’ and ‘Braeburn’ apples were assessed during the preclimacteric stage for two consecutive harvest years by means of an E-nose. A principal component data analysis indicated the presence of both a year and cultivar effect. Partial least square (PLS) models were constructed based on data of both harvest years. The cultivar effect made it difficult to build accurate and robust models for the two cultivars together. As a consequence, calibration models were constructed based on data of 2 years, but for each cultivar separately. The prediction of maturity, according to the Streif Index, showed a cross-validation correlation of 0.89 and 0.92 for ‘Jonagold’ and ‘Braeburn’ fruit, respectively. The calibration models for the prediction of the maturity, defined as the number of days before commercial harvest had a validation correlation of 0.91 for ‘Jonagold’ and 0.84 for ‘Braeburn’ fruit. Individual quality characteristics (soluble solids, acidity, starch and firmness) were predicted reasonably well. The calibration model for soluble solids content resulted in a consistent validation correlation over the results over 2 years (0.76 and 0.77). The starch and firmness were predicted with a validation correlation between 0.72 and 0.80. The prediction of the total acidity was poor (validation correlation of 0.66 and 0.69). It was also demonstrated that the type of validation influences the model prediction performance. Care should be taken when interpreting and using the models to predict the optimal harvest date for other years and cultivars.

DYNAMICS OF CHANGES OF SOME CHERRY FRUIT PROPERTIES AND QUALITY ATTRIBUTES DURING THE GROWING SEASON

Abstract The sour cherry is an important species for European fruit processing industry. The quality of cherry products depends primarily on soluble solids content (SSC) in fruits. Thus, the fruits should be harvested when SSC and mass of fruits are the highest possible. The fruits of sour cherry of two cultivars ‘English Morello’ and ‘Nefris’ were picked six times (in case of ‘English Morello’) and five times (in case of ‘Nefris’) before date of commercial maturity, in roughly weekly intervals. Each time 200 fruits were examined for peduncle detachment force and 150 of these fruits were used for measurements of firmness and SSC. Fitting the logistic curves to collected data showed that this function is not a reliable method for prediction of mean value changes of quality attribute measured destructively. Observation of frequency distribution can, however, much better evaluate the stage of fruit development. Thus analyses of batch data distribution can help prediction of optimal harvest date.

Ascorbic acid concentration in Cv. conference pears during fruit development and postharvest storage.

L-ascorbic acid (L-AA) concentration changes during the development of cv. Conference pears and the influence of postharvest handlings (gas condition, cooling rate, cooling duration) on L-AA breakdown were studied. L-AA concentration fluctuates in young fruits, remains stable during fruit maturation, and starts to decline 1 week before commercial harvest. The most rapid decrease in L-AA concentration was found during immediate controlled atmosphere. During short-term storage, only the gas condition was found to influence L-AA breakdown; no significant difference between gradually or immediately cooled pears was determined. Under air conditions, both cooling strategies did not differ from the L-AA breakdown in pears allowed to ripen on the tree up until 3 weeks after the optimal harvest date. During long-term storage, the cooling duration (1-3 weeks) had no effect whereas both O2 and CO2 had a significant effect on L-AA retention. After 7 months of storage, no difference was found in dehydroascorbic acid concentration; the L-AA and total L-AA concentrations, in contrast, were significantly lower in the 5% CO2 conditions.

Simultaneous measurement of oxygen and carbon dioxide diffusivity in pear fruit tissue

Diffusion and respiration characteristics of pear tissue are needed to estimate the composition of the internal atmosphere of a pear fruit. In this contribution, a methodology is described to measure diffusion characteristics of tissue. The experimental set-up consists of two thermostatted chambers separated with a slice of fruit tissue. A gradient was established over the sample by applying different gas concentrations to both chambers. Due to this gradient, gas diffused from one chamber into the other through the tissue sample. A mathematical model consisting of six differential equations (two for each atmospheric gas) was used to describe this gas transport process through the tissue taking into account diffusion, loss of gas due to sampling, pressure-driven bulk transport, and gas consumption and production due to respiration and oxidation. The diffusion parameters of different respiratory gases in pear fruit tissue could be accurately estimated. The CO2-diffusivity in the fruit flesh (19.2×10−9 m2 s−1) was found to be larger than in the skin (1.15×10−9 m2 s−1) and larger than the O2-diffusivity (2.10×10−9 m2 s−1 in the fruit flesh and 1.03×10−9 m2 s−1 in the skin). The gradient in CO2-diffusivity in the fruit was significant, with the smallest CO2-diffusivity in the skin and the highest near the core of the pear fruit. There was no change in diffusivity in the weeks prior to and after the optimal harvest date for long-term storage.

Uncertainty analysis and modelling of the starch index during apple fruit maturation

Starch conversion into sugars is one of the most important indicators for predicting the optimal harvest dates for apples. The starch conversion is usually assessed using an iodine test, in which cut fruit are dipped in iodine solution and stain patterns are rated. A methodology based on the image analysis of iodine-treated apple slices was used to quantify the uncertainty on the traditional starch index measurements. Considering the subjective interpretation of different inspectors, the errors for certain image assignments were up to 60%. The averaged values of index assignments of groups of images, however, were for most starch indices not significantly different. It was noticed that the subjective interpretation was related to the high number of indices on the chart, the non-linear scale and a sequence disorder of the reference chart. A modified logistic model was proposed to represent the sigmoidal starch index pattern during the preharvest period by two model parameters. Based on these two parameters, and the recommended starch index at harvest, the optimal harvest date was determined. With this technique, the orchard and cultivar effects were analysed.

Alkaloids in Meadow Saffron, Colchicum autumnale L.

ABSTRACT The alkaloids colchicine and colchicoside contained in meadow saffron (Colchicum autumnale L.) seeds are used, respectively, in drugs to treat gout and relax muscles. A two year study at two sites demonstrated the concentration and yields of these two seed constituents involves the transformation of colchicine into colchicoside during plant growth. The optimum harvest date for meadow saffron could be selected for the highest total alkaloid or colchicoside content and for the highest dry matter, and alkaloid yields. Differences in alkaloid yields and concentrations in different plant parts strongly suggest that alkaloids can be translocated in the plant.

Computer-Assisted Color Classification of Peanut Pods1

Abstract Mesocarp color classification in the Hull Scrape Maturity Method is the most important step in determining peanut maturity and optimum harvest date. This research involved the development of an image acquisition system and a software procedure for color classification. Images of peanut pods that had been sorted manually into color classes and subclasses were used in computer training. After training with sorted color classes, the computer-assisted procedure correctly identified and classified the peanut pods, with a 99% precision for the same sample in different alignment, and with a 95% precision for different size samples taken from the same population. Pod size measurement with a resolution of 0.1 mm was also performed using image processing techniques.