WO2025095769A1

WO2025095769A1 - Method for detecting ripeness of a predetermined object

Info

Publication number: WO2025095769A1
Application number: PCT/MY2024/050019
Authority: WO
Inventors: Wan Rusydiah W RUSIK; Amirul Al Hafiz ABDUL HAMID; Batrisyia AHMAD NAZRI; K.harikrishna -; Mohd Shiraz ARIS; Mohd Zulfahmi MOHD YUSOFF; Kok Sing LIM; Harith AHMAD; Wu Yi CHONG
Original assignee: Sime Darby Plantation Intellectual Property Sdn Bhd
Current assignee: Sime Darby Plantation Intellectual Property Sdn Bhd
Priority date: 2023-11-02
Filing date: 2024-03-04
Publication date: 2025-05-08
Anticipated expiration: 2026-05-02

Abstract

The present invention provides a method for detecting ripeness of a predetermined object (101) using a non-destructive and non-invasive sensing means, wherein the sensing means is a multi-wavelength remote sensing device comprising at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle (102), a single-core multimode fibre (108) and at least one band-pass filter (103).

Description

METHOD FOR DETECTING RIPENESS OF A PREDETERMINED OBJECT FIELD OF INVENTION The present invention relates generally to a method for detecting ripeness of a predetermined object. More specifically, the present invention pertains to a non-destructive and non-invasive sensing means to detect ripeness of fruits using a multi-wavelength optical sensing means. BACKGROUND OF INVENTION Oil palm fresh fruit bunches (FFB) can contain up to 2,000 fruits, with fruit colours ranging from very dark purple to orange depending on gene and ripeness. The correct classification of fresh oil palm fruits according to their maturity levels before processing is a major issue now confronting oil palm exporters and growers. The age or ripeness of the oil palm fruits determines both the quality and marketability of the palm oil produced. Before maturing, a fruit is normally yellow at the base and dark purple to black at the apex. A young palm produces 50 to 100 delicious red-violet fruits per bunch. The ratio of pigments in oil palm fruit, such as carotenoids and chlorophylls, influences the colour of the oil. The amount of oil extracted from the oil palm FFB indicates the optimum maturity of the oil palm FFB; thus, colour is an important aspect in measuring the ripeness of the oil palm FFB. According to reports, there is a positive association between the colour of oil palm fruits and their oil content, with under ripe fruit having the lowest oil content, ripe fruit having the highest oil content, and oil content deteriorating when the fruit reaches the overripe stage. Because the oil content of oil palm FFB fluctuates at different stages of ripening, it is critical that the oil palm FFB be collected at its optimum ripeness. The Malaysian Palm Oil Board (MPOB) has established 15 FFB classes in Malaysia. [Source: Intelligent Colour Vision System for Ripeness Classification of Oil Palm Fresh Fruit Bunch, Sensors 2012, 12, 14179-14195] Classification standards as established by MPOB is further shown below: Category Description Black (unripe) Bunch with complete fruits Hard (under ripe) Bunch with 1 to 9 fruits detached Ripe Bunch with 10% to 50% fruits detached Over Ripe Bunch with 50% to 90% fruits detached Empty Bunch Bunch with more than 90% fruits detached Rotten Bunch with all or part having turned back Source: The publication entitled “Oil palm fruit grading using a hyperspectral device and machine learning algorithm (O.M. Bensaeed et. al.) [IOP Conf. Series: Earth and Environmental Science 20 (2014) 0102017] The traditional technique of grading oil palm FFB includes the use of workers' experience to visually assess the state of the oil palm FFBs by cutting a small cut in the fruits to see the mesocarp colour and counting the number of loosened fruits per FFB. Manual grading is a time-consuming, labour-intensive process that is susceptible to biased evaluation and human mistake, potentially leading to increased harvesting and production costs. A fast, dependable, and accurate grading technique for detecting oil palm FFB maturity is required. To successfully automate the procedure, a system that can produce results comparable to human grading is required. [Source: Oil palm fruit grading using a hyperspectral device and machine learning algorithm (O.M. Bensaeed et. al.) [IOP Conf. Series: Earth and Environmental Science 20 (2014) 0102017]] Over the last decade, the Indonesian palm oil sector has grown to become the world's biggest producer, generating significant foreign export reserves. Despite this, difficulties exist in this industry, including low productivity due to raw material mismanagement in post-harvest processes. One of the primary reasons of this is manual oil palm grading/sorting. FFB is subject to inaccuracy and misjudgment, as well as subjectivity. The great demand for oil palm establishes its high price in the global market, driving the sector to extend its plantation area to improve output, compromising forests and agricultural land. Alternatively, existing plantation areas' oil extraction productivity can be increased by carefully selecting ^{optimal FFB for post-harvest processing via automation. Machine vision and spectral analysis have} been found to improve agricultural processing industry productivity. This study applies automated technology for FFB grading in oil palm mills, resulting in enhanced raw material quality, boosting oil extraction productivity, and contributing to reducing deforestation pressure by maintaining green agricultural regions. [Source: Towards Sustainable Green Production: Exploring Automated Grading for Oil Palm Fresh Fruit Bunches (FFB) Using Machine Vision and Spectral Analysis, International Journal on Advanced Science Engineering Information Technology Vol.3 (2013) No.1, ISSN 2088-5334] A study conducted by the Indonesian Oil Palm Research Institute (IOPRI) discovered significant potential revenue loss in the majority of Indonesian oil palm plantations, primarily owing to improper FFB harvesting practices. When harvesting was done, the labour misjudged raw or unripe FFBs and cropped them, whereas ripe FFBs were not harvested in some situations. Both errors result in plantation losses. As a result, it is critical to investigate methods of correctly identifying oil palm FFB during harvest. FFB changes physically throughout ripening, which is visible as a shift in colour due to pigment alteration and accumulation; nevertheless, human visual identification of colour is subjective and prone to errors due to mental and physical effects. Current technologies allow the use of photosensitive electro-sensor devices to accurately assess the colour of the fruit and track its physiological processes. Previous research used such technologies for FFB quality inspections, with the emphasis on the post- harvest condition of oil palm FFB prior to the milling process. [Source: International Journal on Advanced Science Engineering Information Technology, Vol.5 (2015) No. 3, ISSN: 2088-5334 – Optical Characteristics of Oil Palm Fresh Fruit Bunch (FFB) Under Three Spectrum Regions Influence for Harvest Decision]. Ripeness is a key aspect in determining the quality of harvested oil palm fresh fruit bunches (FFB). Traditional ripeness classifications based on FFB colour and number of loose fruit for harvesting have certain drawbacks, particularly for high oil palm plants. To replace the existing method, a laser-based imaging system is proposed. Ripeness detection simulation of oil palm FFBs was carried out in this work. The system consisted of two diode lasers with wavelengths of 532 nm and 680 nm, as well as a CMOS camera mounted on a revolving plate enabling easy adjustment of the laser beam hitting the FFB. The FFB samples were put on an aluminium platform at four different heights: 1.5 m, 2 m, 2.5 m, and 3 m. The relationships between the reflectance intensities represented by the FFB pictures; Red Green Blue (RGB) values and the height fluctuations and ripeness levels of FFBs with and without laser ^{beam were investigated. The Tenera samples came in four ripeness levels termed F0, F1, F3, and F4.} The results revealed that the red component of RGB values was prominent for both FFBs without and with red laser. The average RGB values for F3 (ripe) and F4 (overripe) levels are greater. Green laser imaging revealed consistency. Imaging methods based on lasers were able to distinguish ripeness degrees of oil palm fresh fruit bunches; this could be used for future remote detection of oil palm FFB freshness. [Source: Ripeness detection simulation of oil palm fruit bunches using laser-based imaging system January 2017AIP Conference Proceedings 1801(1):050003 DOI:10.1063/1.4973101] Publication entitled “Investigations on a Novel Inductive Concept Frequency Technique for the Grading of Oil Palm Fresh Fruit Bunches” [Source: Sensors 2013, 13(2), 2254-2266; https://doi.org/10.3390/s130202254] discusses a preliminary research of a novel oil palm fruit sensor for detecting oil palm fruit bunch maturity. The frequency characteristics of air coils of various diameters are researched to establish their inductance and resonant qualities in order to maximize the sensor's performance. Sixteen samples from two categories, ripe oil palm fruitlets and unripe oil palm fruitlets, are evaluated at frequencies ranging from 100 Hz to 100 MHz. The results showed that the inductance and resonant properties of the air coil sensors differ significantly between samples in each category. The frequency characteristics of sensor air coils are investigated to determine the influence of variations in coil diameter. The effect of coil diameter results in a significant 0.02643 MHz difference between unripe samples and air and 0.01084 MHz difference between ripe samples and air. The developed sensor has tremendous promise for assessing the ripeness of oil palm fruits. Publication entitled “A Portable Low-cost Non-destructive Ripeness Inspection for Oil Palm FFB, Agriculture and Agricultural Science Procedia 9 (2016) 230 – 240” describes an investigation into the maturity of oil palm FFB was measured via a portable and low-cost equipment that included a digital camera, a laptop, and a compact and lightweight chamber with independent LED lights. The recorded FFB image was then segmented and analyzed on the computer using image processing software. The colour of the FFB image was determined and specified by the software in RGB colour space. In this investigation, FFB colour observations via camera vision provided better consistency than expert observation results. Publication entitled “Potential Application of Colour and Hyperspectral Images for Estimation of Weight and Ripeness of Oil Palm (Elaeis guineensis Jacq. var. tenera) Phorntipha Junkwon et. al., ISSN: 0916- 9482 of Agricultural Information Research” describes the creation of a technique for estimating the weight and ripeness of oil palm bunches (Elaeis guieensis Jacq. var. tenera) from hyperspectral and RGB colour photographs. Colour and hyperspectral photos of the bunch were captured in the studies from four distinct perspectives, each 90 degrees apart. The RGB photos were transformed to HSI and L*a*b colour spaces. The area of the bunch and the area of space between the fruits were identified using gray-scale thresholds. The total number of pixels in the bunch and the available space were both counted. The total number of pixels in the bunch was also counted in the hyperspectral pictures from ^{an image composed of three wavelengths (560 nm, 680 nm, and 740 nm), while the total number of} pixels of space between fruits was obtained at a wavelength of 910 nm. Weight-estimation equations were derived from these data sets using linear regression (LR) or multiple linear regression (MLR). As a result, the coefficient of determination (R2) of real weight and anticipated weight for colour and hyperspectral pictures was 0.989 and 0.992, respectively. Oil palm FFB estimation was also evaluated. This study used bunches from four ripeness classes (overripe, ripe, under ripe, and unripe). Because estimating ripeness from a bunch of data was problematic, the focus was on the difference in colour or reflectivity of the region concealed and not-concealed with fronds. The Euclidean distances between the test sample and the conventional four ripeness classes were calculated, and the test sample was assigned to the ripeness class with the shortest distance from the sample. The average RGB values of concealed and not-concealed sections were used in colour picture classification, whereas the average intensity values of individual pixels from the concealed area were employed in hyperspectral images. Validation trials with the established estimation methods revealed acceptable estimation accuracy and the feasibility of practical application to measure the maturity of oil palm bunches. Chinese Patent CN106290220B describes a non-destructive and quick detection method and apparatus for flight time spectral fruit ripeness. The non-destructive and speedy flight time spectral fruit maturity detection method consists of the following steps: first, using a laser driving device to generate a laser pulse signal, wherein the laser pulse signal acts on the surface of a fruit, penetrates the epidermis of the fruit, collides with particles inside the fruit to scatter out, and scattered light beams are reflected out from the surface of the fruit; detecting a reflected pulse signal from the fruit with a high- speed response photoelectric detector, amplifying the pulse signal, performing A/D conversion on the amplified pulse signal, feeding into a microcontroller, and displaying the pulse signal processed by the microcontroller on an oscilloscope. Finally, based on the shape of an extended pulse signal, evaluate the scattering coefficient of the fruit; and judge the quality and maturity of the fruit based on the link between the scattering coefficient and the fruit age. Non-destructive detection of fruit quality and maturity can be implemented accurately and quickly by using the approach. Chinese Patent CN104515751 provides a flight time spectral fruit maturity non-destructive and quick detection technique and apparatus. The flight time spectral fruit maturity non-destructive and quick detection method consists of the following steps: first, driving a laser to generate a laser pulse signal via a laser driving device, wherein the laser pulse signal acts on the surface of a fruit, penetrates through the epidermis of the fruit, collides with particles inside the fruit to scatter out, and scattered light beams are reflected out from the surface of the fruit; detecting a pulse signal reflected from the fruit via a high- speed response photoelectric detector, amplifying the pulse signal, performing A/D conversion on the amplified pulse signal, feeding it into a microcontroller, displaying the microcontroller-processed pulse signal on an oscilloscope, and finally evaluating the scattering coefficient of the fruit based on the shape of an expanded pulse signal; judging the quality and maturity of the fruit based on the relationship between the scattering coefficient and the fruit maturity. Non-destructive detection of fruit quality and maturity can be implemented accurately and quickly by using the approach. Chinese Patent CN114594065 presents a system and method for detecting fruit maturity. A gas collection device collects N kinds of gas emitted by the fruits to be detected and inputs the N kinds of gas into a detection gas chamber, a light source device sequentially emits N kinds of different light based on the N kinds of gas, each kind of light passes through the detection gas chamber and an optical isolation device to reach a standard gas chamber, and the standard gas chamber is connected to the optical isolation device. The microphone detects each type of light absorbed by the standard gas in the standard gas chamber, obtains a sound pressure value corresponding to each type of light, and outputs the sound pressure value to the maturity detection device; and the maturity detection device determines the concentration of the corresponding gas based on the sound pressure value corresponding to each light, and determines the maturity of the fruit to be detected based on the concentration The application claims that the ripeness of the fruit may be recognized more accurately by sensing the concentration of several gases distributed across the fruit to be detected. Indian Patent IN202011045606 explains a method for manually identifying ripening fruits for harvesting. The gadget is shaped like a helmet with a strap around the head. The device communicated with the stakeholder using a microphone and speaker via a wireless communication-based edge device. The device has a pre-trained deep learning system for processing real-time images captured by the VGA camera with a predetermined delay. When the microcontroller sends a signal, a laser flash light leads the user to pluck the ripening fruit. When compared to manual grading, the IoT device delivers more accurate detail of the ripened fruit and reduces labour requirements during grading because only properly ripened fruit of a specific hue is harvested. Chinese Patent CN213986180 provides a fruit maturity detection system that includes a gas collection device, N gases emitted by a fruit to be detected are collected by the gas collection device and input into a detection gas chamber, a light source device sequentially emits N different lights based on the N gases, each light passes through the detection gas chamber and an optical isolation device to reach a standard gas chamber, and the standard gas chamber is used for detecting the maturity. After being absorbed by gas in the detection gas chamber, each kind of light enters the standard gas chamber through the optical isolation device and is absorbed by standard gas in the standard gas chamber, and the microphone detects each kind of light absorbed by standard gas in the standard gas chamber, obtains a sound pressure value corresponding to each kind of light, and outputs the sound pressure value to the maturity detection device. The application claims that the ripeness of the fruit may be recognized more accurately by sensing the concentration of several gases distributed across the fruit to be detected. Malaysian Patent MY162606 refers to an automated grading of oil palm fruits that includes grading and dividing oil palm fruits into several grades. The automated grading of oil palm fruits entails the use of several varieties of oil palm fruit, such as under ripe fruit, ripe fruit, and overripe fruit. The procedure begins by removing the oil palm fruit skin and scanning the oil palm fruits. The red light laser scanning ^{approach was used in this discovery. The fresh oil palm fruit brunches were transported and graded by} placing the oil palm fruits on the moving conveyor belt. The amount of reflected laser light is monitored and converted to digital values when the oil palm fruits pass through the laser light. This review looked at 48 articles in total. Each article presents a detection method for assessing the freshness of fresh fruit bunches, with the identical parts in each detection method. The first step entails employing a certain type of sensor, such as a camera—optical or inductive—to examine a specific area of the FFB, such as fruitlets or the full fruit. Second, the sensor data was subjected to feature selection or extraction processing, such as PCA, before being sent to a classifier. Finally, based on the input it received, the classifier made a final conclusion on whether the FFB was ripe or not. The classifier could be traditional (e.g., K-Nearest Neighbor) or more sophisticated (e.g., convolutional neural network). The sample data used in the literature varies amongst the various types of categorization maturity approaches. The sample data serve as the source material for the maturity analysis. Through feature extraction, both FFBs and oil palm fruitlets can be examined to determine developmental phases. The sample data, on the other hand, is dependent on the sensor application's limitations. The fruit battery method, for example, uses electrodes to pierce the oil palm fruitlet for measurement. Researchers are using both FFB and oil palm fruitlets in their studies for various approaches such as computer vision, LiDAR sensor, and optical sensor. These technologies allow information to be handled regardless of the object's capture distance or morphography. [Source: Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review - Agriculture 2023, 13(1), 156; https://doi.org/10.3390/agriculture13010156] Ripeness is one of important factors for quality sorting of harvested oil palm fresh fruit bunches (FFB). Traditional ripeness classifications using FFB colour and number of fruit loose for harvesting have some disadvantages especially for high oil palm trees. A laser based imaging system is proposed to substitute the traditional method. In this study, ripeness detection simulation of oil palm FFBs was performed. The system composed of two diode lasers with 532 nm and 680 nm in wavelengths and a CMOS camera which was set on a rotating plate for easy adjustment of laser beam hitting FFB. The FFB samples were placed on an aluminium platform with 4 height variations, 1.5 m, 2 m, 2.5 m, and 3 m. The relations of reflectance intensities represented by Red Green Blue (RGB) values of the FFB images to the height variations and ripeness levels of FFBs with and without laser beam were analyzed. The samples were from Tenera variety with 4 ripeness levels called F0, F1, F3, and F4. The results showed that the red component of RGB values were dominant for FFBs without laser and with red laser. The average RGB values are higher for F3 (ripe) level and F4 (overripe). Imaging with green laser showed consistency. Imaging methods using laser was able to differentiate ripeness levels of oil palm fresh fruit bunch, it could be applied for future remote detection of oil palm FFB ripeness. [Source: Ripeness detection simulation of oil palm fruit bunches using laser-based imaging system - Conference: THE 6TH INTERNATIONAL CONFERENCE ON THEORETICAL AND APPLIED PHYSICS (THE 6th ICTAP)]

SUMMARY OF INVENTION The present invention relates generally to a method for detecting ripeness of a predetermined object. More specifically, the present invention pertains to a non-destructive and non-invasive sensing means to detect ripeness of fruits using a multi-wavelength optical sensing means. Accordingly, the present invention provides a method for detecting ripeness of a predetermined object using a non-destructive and non-invasive sensing means, wherein the sensing means uses a multi- wavelength optical sensing means which is a multi-wavelength remote sensing device, comprising at ^{least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic} bundle, a single-core multimode fibre and at least one band-pass filter. Further, the present invention provides a remote sensing device for detecting ripeness of a predetermined object using a non-destructive and non-invasive multi-wavelength optical sensing means whereby the multi-wavelength remote sensing device comprises at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle, a single-core multimode fibre and at least one band-pass filter.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates the configuration of the method of the present invention with the following reference numerals and alphabets: • a predetermined object (101); • at least one fibre optic bundle (102); • at least one band-pass filter (103); • a photodetector (104); • one converging lens (105); ^{• one reflective mirror (106);} • N-coupled laser modules (107); • a single-core multimode fibre (108); • optical axes (A); • focal length (B); • focal point (C); • field of view (D); • reflected light (E); and • emitted light beam (F). Figure 2 illustrates the field of view (D) of the photodetector which can be adjusted by manipulating the position of the lens, whereby the photodetector is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). The photodetector (104) is positioned at the parallel and overlapping optical axes (A). Figure 3 illustrates a discriminant analysis plot for oil palm FFB at various stages of maturity (under- ripe and unripe). This discriminant line varies according to the size of the remote sensing device made and the current parameters and settings. As a result, the value is set once the item is manufactured for use. Figure 4 illustrates the correlations between O/DM (oil / dry mesocarp) and moisture content for the I635/I808 ratio to validate the method and device of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE PRESENT INVENTION The present invention relates generally to a method for detecting ripeness of a predetermined object. More specifically, the present invention pertains to a non-destructive and non-invasive sensing means to detect ripeness of fruits using a multi-wavelength optical sensing means. Accordingly, the present invention provides a method for detecting ripeness of a predetermined object using a non-destructive and non-invasive sensing means, wherein the sensing means uses a multi-wavelength optical sensing means, is a multi-wavelength remote sensing device. ^{Further, the present invention provides a remote sensing device for detecting ripeness of a} predetermined object using a non-destructive and non-invasive multi-wavelength optical sensing means. The multi-wavelength remote sensing device comprises at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle, a single-core multimode fibre (108) and at least one band-pass filter (103). The correct classification of fresh oil palm fruits according to their maturity levels before processing is a major issue now confronting oil palm exporters and growers. The traditional technique of grading oil palm FFB includes the use of workers' experience to visually assess the state of the oil palm FFBs by cutting a small cut in the fruits to see the mesocarp colour and counting the number of loosened fruits per FFB. Manual grading is a time-consuming, labour-intensive process that is susceptible to biased evaluation and human mistake, potentially leading to increased harvesting and production costs. It can be appreciated that the parameters for the present invention are not obvious for a person skilled in the art and have been tested and determined by the inventors based on numerous trials conducted, observations, discussions and combined expertise, which would not be able to be determined without much efforts and analysis. All prior arts as listed and referred to above do not specifically describe the method and device of the present invention. The closest prior arts does not disclose or describe the method and device of the present invention as further described below: • Publication entitled ‘Ripeness detection simulation of oil palm fruit bunches using laser-based imaging system January 2017 AIP Conference Proceedings’ is the closest prior art to this present invention. However, in comparison to the method and device of the present invention, the prior s^{ystem: - is a biaxial system in which the work distance is highly dependent on the overlapping} between the light propagation and field of view, laser wavelengths used are limited to visible light regions only, does not address the problems associated with the work distance and the detected signal, is not portable and employs many filters in their system configuration. • Malaysian Patent MY-162606 is about laser scanning means which is used to cut and analyze fruit skins. This is not a non-invasive or remote evaluation per the method of this present invention. The process begins by removing the oil palm fruit skin and scanning the oil palm fruits and the amount of reflected light is measured using a red laser. The fresh oil palm FFBs were transported and graded by placing the oil palm fruits on a moving conveyor belt. Unlike distant sensing, this procedure is intrusive as the assessment is performed in close proximity. Plus, there is only one laser wavelength (red) employed for this purpose. • Chinese Patent CN106290220B addresses the issue of light scattering interference. The concentration of ethylene gas detected by laser photoacoustic spectroscopy is used to determine fruit maturity. Detection is only possible at close contact to the fruit. • Chinese Patent CN104515751 describes a detector which is only effective at close proximity. The detection involved light penetrating the fruit's surface and interacting with the particle and material inside and the scattered light from the fruit is distinct. • Fruit gas is collected and analyzed in a gas chamber for Chinese Patent CN114594065. Remote sensing is not possible for this invention. • The gases emitted by the fruits are collected and analysed for Chinese Patent CN213986180. Objectives of the present invention are as follows: A first object of the present invention is to provide a non-destructive and non-invasive sensing method for detecting fruit maturity utilizing a multi-wavelength remote sensing device, specifically real-time remote sensing in order to determine the ripeness of oil palm FFBs in oil palm estates. Because it is a non-invasive method and the laser light does not penetrate the skin of the fruitlets of the oil palm FFB, the oil palm FFBs are not harmed using the method and device of the present invention. ^{A second object of the present invention is to provide an accurate, simple, fast, effective, consistent,} and reliable means of detecting ripeness of oil palm FFBs in real-time in oil palm estates, as opposed to the manual approach which is time-consuming, labour-intensive, and susceptible to biased evaluation and human error, potentially leading to increased harvesting and production costs. A third object of the present invention is to provide a novel configuration of the multi-wavelength remote sensing device, in which only one converging lens is required or employed for this purpose, with the use of one reflective mirror and a photodetector positioned at the optical axis of the light source. The optical axis of the emitted light beam from the laser light and the optical axis of the reflected light beam from the oil palm FFBs to the photodetector are parallel and overlapping. This innovative configuration yields a coaxial laser light and photodetector arrangement suitable for the purposes of the present invention and such device per present invention has not been seen to be deployed in oil palm estates by others in the industry based on the inventor’s knowledge. A fourth object of the present invention is to provide a method and device with the coaxial laser and photodetector arrangement (in which the optical axes of the light source (laser light) and photodetector are parallel and overlapping) that can accommodate a long work distance which is required for detecting ripeness of the oil palm FFBs in oil palm estates in real-time. The work distance means the distance between the device of the present invention and the predetermined objects (101) (oil palm FFBs) which can be in a range of between 4m to 8m or more depending on the preference of the user of the present ^{invention. Manually determining the ripeness of oil palm FFBs by a worker / harvester is not practicable} since it may be difficult to see the FFBs that are too high on the oil palm trees. A fifth object of the present invention is to provide a remote sensing device that employs at least one laser light as its light source (i.e. laser remote sensor). Laser light is favoured because it is concentrated, monochromatic, has a fixed wavelength, is coherent, directed, and can travel vast distances. Laser light is also preferred because it does not require the use of ambient light to detect the ripeness of the oil palm FFBs, allowing the device to operate in a variety of lighting circumstances such as cloudy, sunny, and night time. The present invention makes use of more than one laser light wavelength. The laser light employed has different wavelengths (multi-wavelengths approach) ranging from 400nm to 1,000nm, primarily relating to the visible and infrared light ranges. A sixth object of the present invention is to provide a means to detect ripeness of oil palm FFBs in real time by a microcontroller using a ratiometric means. It is found that the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the ripe oil palm FFB is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the under-ripe oil palm FFB with a same distance between the one converging lens and the predetermined object. The ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the under-ripe oil palm FFB is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the unripe oil palm FFB with a same distance between the one converging lens and the predetermined object. A seventh object of the present invention enables the size of the device of the present invention to be determined and manufactured depending on preference and needs of an user of the present invention in order to have a device which is portable, light and small for easy usage by the workers in oil palm estates which yields the same accurate results despite of its size when detecting ripeness of the oil palm FFBs in the estates. The unique configuration remains constant regardless of the size of the laser remote sensing device. Other characteristics of the method and device, depending on the size required by the user of the present invention, can be varied and customized accordingly without compromising the new optical arrangement of the present invention. An eighth object of the present invention enables the field of view of the photodetector to be adjusted by manipulating the position of the lens, whereby the photodetector is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes. The photodetector is positioned at the parallel and overlapping optical axes. The first position is whereby a distance between the photodetector and the converging lens is the focal length of the converging lens. The second position is whereby a distance between the photodetector and the converging lens is longer than the focal length of the converging lens. The third position is whereby a distance between the photodetector and the converging lens is shorter than the focal length of the converging lens. The field of view for the third position is larger than the field of view for the first position. The first position has a ^{larger field of view than the second position.} While the present invention is described in detail using illustrative drawings and embodiments, it should be understood that the detailed description is not intended to limit the invention to the embodiments of drawings or drawings described, nor is it intended to limit the invention to the particular form disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the scope of the present invention. The present invention is described in various embodiments with reference to accompanying figures, where reference numerals in the drawing correspond to the features specified in the description. However, the present invention can take many various forms and should not be interpreted as restricted to the examples described herein. As a result, embodiments are described so that this disclosure is thorough and complete, and that those knowledgeable in the art can fully understand the scope of the invention. The numerical values, ranges, and materials described in the comprehensive description are supplied as examples only and are not intended to limit the scope of the present invention's claims. The terminology and phraseology used herein are only for descriptive reasons and are not meant to be restrictive in scope. Words like "including", "comprising", "having", "containing" or "involving" and other variations are meant to be broad and embrace the subject matter as specified, including equivalents and extra subject matter not recited, such as other components or steps. The details of the present invention will now be described in relation to the accompanying Figures 1 and 2. The present invention provides a method for a method for detecting ripeness of a predetermined object (101) using a non-destructive and non-invasive sensing means, wherein the sensing means is a multi- wavelength optical sensing means. The multi-wavelength optical sensing means is a multi-wavelength remote sensing device. The multi-wavelength remote sensing device comprises at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle (102), a single-core multimode fibre (108) and at least one band-pass filter (103). The at least one sensor is a photodetector (104). The at least one lens is one converging lens (105). The at least one mirror is one reflective mirror (106) with reflectivity of more than 90%. The at least one light source is concentrated, monochromatic, has a specific wavelength, coherent, directional and able to travel long distances. The first optical axis is an optical axis of an at least one emitted light beam (F) from the at least one light source. The second optical axis is an optical axis of an at least one reflected light beam (E) from the predetermined object (101) to the photodetector (104). The first optical axis and the second optical axis are parallel and overlapping axes (A). The at least one band-pass filter (103) is an optical band-pass filter positioned in front of the photodetector (104) on the parallel and overlapping first and second optical axes (A). The reflective mirror (106) is positioned on the parallel and overlapping first and second optical axes (A) in between the converging lens (105) and a focal point (C) of the converging lens (105). The photodetector (104) is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). The first position is whereby a distance between the photodetector (104) and the one converging lens (105) is a focal length (B) of the one converging lens (105). The second position is whereby a distance between the photodetector (104) and the one converging lens (105) is longer than the focal length (B) of the one converging lens (105). The third position is whereby a distance between the photodetector (104) and the one converging lens (105) is shorter than the focal length (B) of the one converging lens (105). The at least one light source comprises N-coupled laser modules (107) consisting of N-to-1 fibre optic bundle (102) to emit N-laser beams with N-emission wavelengths. The single-core multimode fibre (108) directs and guides the emitted N-laser beams with N-emission wavelengths in sequence to the reflective mirror (106). The N is at least 2. The reflective mirror (106) reflects the emitted N-laser beams with N-wavelengths in sequence toward ^{an optical axis of the converging lens (105), whereby the converging lens (105) expands the reflected} N-laser beams with the N-wavelengths toward the predetermined object (101). The N-wavelengths is in a range of between 400nm to 1,000nm. The wavelength of the at least one band-pass filter (103) is in a range of between 600nm to 850nm. The photodetector (104) detects N-reflected power of the N- wavelengths of the at least one reflected light beam (E) from the predetermined object (101) in sequence. The ripeness of the predetermined object (101) is detected in real time by a microcontroller using a ratiometric means. The ratiometric means refer to a ratio of a first reflected power of a first wavelength from the N-emission wavelengths of the at least one reflected light beam (E) to a second reflected power of a second wavelength from the N-emission wavelengths of the at least one reflected beam. The first wavelength is in a range of between 400nm to 750nm. The second wavelength is in a range of between 751nm to 1,000nm. The predetermined object (101) refers to a first fruit, a second fruit and a third fruit. The first wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. The second wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. The first reflected power of the first wavelength of the third fruit is greater than the first reflected power of the first wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101). The first reflected power of the first wavelength of the second fruit is greater than the first reflected power of the first wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). The second reflected power of the second wavelength is identical for the first fruit, second fruit and the third fruit. The first reflected power of the first wavelength to the second reflected power of the second wavelength of the third fruit is greater than the ratio of the first reflected power of the first wavelength to the second ^{reflected power of the second wavelength of the second fruit with a same distance between the one} converging lens (105) and the predetermined object (101). The ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). The first fruit refers to unripe oil palm fresh fruit bunches (FFB). The second fruit refers to under-ripe oil palm FFB. The third fruit refers to ripe oil palm FFB. The present invention also provides a remote sensing device for detecting ripeness of a predetermined object (101) using a non-destructive and non-invasive multi-wavelength optical sensing means. The multi-wavelength remote sensing device comprises at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle (102), a single-core multimode fibre (108) and at least one band-pass filter (103). The at least one sensor is a photodetector (104). The at least one lens is one converging lens (105). The at least one mirror is one reflective mirror (106) with reflectivity of more than 90%. The at least one light source is concentrated, monochromatic, has a specific wavelength, coherent, directional and able to travel long distances. The first optical axis is an optical axis of an at least one emitted light beam (F) from the at least one light source. The second optical axis is an optical axis of an at least one reflected light beam (E) from the predetermined object (101) to the photodetector (104). The first optical axis and the second optical axis are parallel and overlapping axes (A). The at least one band-pass filter (103) is an optical band- pass filter positioned in front of the photodetector (104) on the parallel and overlapping first and second optical axes (A). The reflective mirror (106) is positioned on the parallel and overlapping first and second optical axes (A) in between the converging lens (105) and a focal point (C) of the converging lens (105). The photodetector (104) is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). The first position is whereby a distance between the photodetector (104) and the one converging lens (105) is a focal length (B) of the one converging lens (105). The second position is whereby a distance between the photodetector (104) and the one converging lens (105) is longer than the focal length (B) of the one converging lens (105). The third position is whereby a distance between the photodetector (104) and the one converging lens (105) is shorter than the focal length (B) of the one converging lens (105). The at least one light source comprises N-coupled laser modules (107) consisting of N-to-1 fibre optic bundle (102) to emit N-laser beams with N-emission wavelengths. The single-core multimode fibre (108) directs and guides the emitted N-laser beams with N-emission wavelengths in sequence to the reflective mirror (106). The N is at least 2. The reflective mirror (106) reflects the emitted N-laser beams with N-wavelengths in sequence toward an optical axis of the converging lens (105), whereby the converging lens (105) expands the reflected N-laser beams with the N-wavelengths toward the predetermined object (101). The N-wavelengths is in a range of between 400nm to 1,000nm. The wavelength of the at least one band-pass filter (103) is in a range of between 600nm to 850nm. The photodetector (104) detects N-reflected power of the N- wavelengths of the at least one reflected light beam (E) from the predetermined object (101) in sequence. The ripeness of the predetermined object (101) is measured in real time by a microcontroller using a ratiometric means. The ratiometric means refer to a ratio of a first reflected power of a first wavelength from the N-emission wavelengths of the at least one reflected light beam (E) to a second reflected power of a second wavelength from the N-emission wavelengths of the at least one reflected beam. The first wavelength is in a range of between 400nm to 750nm. The second wavelength is in a range of between 751nm to 1,000nm. The predetermined object (101) refers to a first fruit, a second fruit and a third fruit. The first fruit refers to unripe oil palm fresh fruit bunches (FFB). The second fruit refers to under-ripe oil palm FFB. The third fruit refers to ripe oil palm FFB. The first wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. The second wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. The first reflected power of the first wavelength of the third fruit is greater than the first reflected power of the first wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101). The first reflected power of the first wavelength of the second fruit is greater than the first reflected power of the first wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). The second reflected power of the second wavelength is identical for the first fruit, second fruit and the third fruit. The ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the third fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit with a same distance between ^{the one converging lens (105) and the predetermined object (101). The ratio of the first reflected power} of the first wavelength to the second reflected power of the second wavelength of the second fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). This invention provides a quantitative assessment which is an innovative means of identifying or detecting the ripeness of oil palm FFBs which is more consistent and successful than the traditional method of physical assessment by estate workers to determine fruit maturity. Traditionally, the operator will rely solely on the number of oil palm loose fruits on the ground to determine whether or not there are ripe oil palm FFBs on the oil palm trees. The current invention has been shown to be beneficial, efficient and effective in determining ripeness of oil palm FFBs. According to the present inventors' knowledge, the coaxial laser and photodetector (104) arrangement (in which the optical axes (A) of the laser light and photodetector (104) are parallel and overlapping) per current invention has never been documented in detecting ripeness of oil palm FFBs. The primary advantages of this technology are the long working distance (the distance between the device of the present invention and the oil palm FFBs) and the portable / compact form of device for easy and convenient use in estates. It is pertinent and important that oil palm fresh fruit bunches (FFB) are harvested at the optimum ripeness as the oil content of oil palm FFB is very much linked to the degree of ripeness. Conventional practice of quality inspection and grading of oil palm FFB is via human inspection (manual inspection) at the palm oil mill is labour intensive and time consuming. Moreover, the accuracy of grading results may be jeopardized by subjective human judgments. The use of laser light is preferred and suitable for long work distance which is required for use in the oil palm estates. Aside from that, the laser light is coherent and can be collimated to illuminate a target (i.e. the oil palm FFB) from a greater distance. The laser beam can also be enlarged using a beam expander to illuminate a broader surface area of the oil palm FFB and provide a more homogenous measurement. The present invention's inventors prefer to employ a wavelength in the region of 400nm to 1,000nm because it provides a wider range for more thorough information about the ripeness of the oil palm FFBs. The said range shows a strong relationship between the power of the reflected light beam (E) from the oil palm FFB and its ripeness. Aside from that, the inventors chose this range because it has the least amount of interference from natural light. The remote sensing device emits laser light in N various wavelengths successively, resulting in a multi- wavelength technique in determining the ripeness of the oil palm FFBs. A microcontroller is used to test the ripeness of oil palm FFBs in real time using a ratiometric method. Multi-wavelengths, at least two or more, in the range of two to ten, are used. The inventors examined and discovered that at least three ^{is required and sufficient to offer effective results in measuring the ripeness of the oil palm FFB using} ratiometric assessment means. The novel optical architecture of the remote sensing device is innovative and has never been employed for real-time detection of ripeness of oil palm FFBs in oil palm estates. There is no such device in use in the industry, and no prior art document is known to reference it Ratiometric assessment refers to a ratio of a first reflected power of a first wavelength from the reflected light beam (E) to a second reflected power of a second wavelength of the reflected light beam (E). The first wavelength is in a range of between 400nm to 750nm which is found by the inventors of the present invention to be sensitive toward fruit ripeness. It is known that the reflected light from the surface of the oil palm FFB varies with its ripeness and this characteristic is wavelength dependant. The reflected power of a specific wavelength increases with increasing fruit ripeness. It has been discovered that the: • reflected power of a first wavelength of a ripe oil palm FFB is greater than the reflected power of a first wavelength of an under-ripe oil palm FFB; and • reflected power of a first wavelength of an under-ripe oil palm FFB is greater than the reflected power of a first wavelength of an unripe oil palm FFB. However, the reflected power of a second wavelength of a ripe oil palm FFB, under-ripe oil palm FFB and unripe oil palm FFB remains the same. The inventors have tested and determined that the second wavelength is not sensitive towards fruit ripeness, whereby there is no change to the reflected power of the second wavelengths based on the fruit ripeness. The second wavelength is in a range of between 751nm to 1,000nm. The inventors have further determined the following: The ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of a ripe oil palm FFB is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of an under-ripe oil palm FFB. The reflected light beam (E) is wavelength dependant, for example I635 refers to the detected power of the reflected light beam (E) at the wavelength of 635nm. The ratio of the first reflected power of the first wavelength to the second reflected power of the second ^{wavelength of an under-ripe oil palm FFB is greater than the ratio of the first reflected power of the first} wavelength to the second reflected power of the second wavelength of an unripe oil palm FFB. The first wavelength, second wavelength and the distance between the converging lens (105) and the predetermined object (101) must be the same in order to determine accurately ripeness of the oil palm FFBs. The novel configuration of the remote sensing device is a compact and low-cost portable device which provides a long work distance. The coaxial laser and photodetector (104) arrangement (in which the optical axes (A) of the light source (laser light) and photodetector (104) are parallel and overlapping) is able to accommodate a long work distance which is required for detecting ripeness of the oil palm FFBs in oil palm estates. Only one converging lens (105) is used for the present invention. This results in that the optical axis of an at least one emitted light beam (F) from the at least one light source and the optical axis of an at least one reflected light beam (E) from the predetermined object (101) to the photodetector (104) are parallel and overlapping axes (A). Fresnel lens was used by the developers of the current technology because it is light, thin, and has a high lens diameter to focal length ratio. A bigger lens diameter is desirable to capture more reflected light (E) for detection at the photodetector (104). This functionality is required for the laser remote sensor to have a large operating range. However, the laser remote sensor dimensions are smaller and more compact, hence a shorter focal length (B) is preferred for the purposes of the present invention. For this invention, only one reflective mirror (106) is employed, and hence only one reflection occurs at the mirror. A mirror with a high reflectivity of greater than 90% is desirable for this innovation, which can be used for any wavelength between 400nm and 1,000nm. The reflective mirror (106) is positioned on the parallel and overlapping first and second optical axes (A) in between the converging lens (105) and a focal point (C) of the converging lens (105). The photodetector (104) is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). The first position is whereby a distance between the photodetector (104) and the one converging lens (105) is a focal length (B) of the one converging lens (105). The second position is whereby a distance between the photodetector (104) and the one converging lens (105) is longer than the focal length (B) of the one converging lens (105). The third position is whereby a distance between the photodetector (104) and the one converging lens (105) is shorter than the focal length (B) of the one converging lens (105). Referring to Figure 2, these three positions are critical in altering the field of view (D) based on the ^{user's preferences for the present invention. The first position is chosen since the field of view (D) is} not too large or too small. Too small is not desirable since less light will be gathered by the converging lens (105) and photodetector (104), resulting in inaccurate findings. If the field of view (D) is excessively large, too much light is captured by the photodetector (104) resulting in increased noise and lower accuracy of results in detecting the ripeness of the oil palm FFBs. A band-pass filter (103) is an optical band-pass filter positioned in front of the photodetector (104) on the parallel and overlapping first and second optical axes (A). This filter assists in reducing the noise, increasing the accuracy of ripeness detection based on the power of reflected light beam (E) from the oil palm FFBs. The inventors have used the following parameters to test and demonstrate the method and device of the present invention: The present invention has the following components: • a predetermined object (101); • at least one fibre optic bundle (102); • at least one band-pass filter (103); • a photodetector (104); • one converging lens (105); • one reflective mirror (106); • N-coupled laser modules (107); • a single-core multimode fibre (108); • optical axes (A); • focal length (B); • focal point (C); • field of view (D); • reflected light beam (E); and • emitted light beam (F). The work distance here refers to the distance between the converging lens (105) and the predetermined object (101) which is in a range of between 4m to 8m or more depending on the preference of the user of the present invention. To obtain effective and sufficient results for this purpose in a range of between 4m to 8m, a laser in a power range of between 80mW to 100mW is sufficient. If the distance if longer than this, detected power of the reflected light will be reduced, therefore, the power of the device needs to be increased accordingly. The power required can be chosen depending on the distance required by an user of the present invention. The distance between the converging lens (105) and the photodetector (104) is in a range of between 0.13 m to 0.15 m. The focal length (B) of the converging lens (105) is the distance from the optical ^{centre of the converging lens (105) to the focus of the converging lens (105) whereby the focal length} (B) is preferably more than 5cm. The photodetector (104) is positioned at the focal point (C) of the converging lens (105) to detect the power of the reflected laser beam. Noise (unwanted light) of the detected reflected laser beam is reduced or cancelled with the band-pass filter (103) with a wavelength in a range of between 600nm to 850nm which is sufficient for visible and infra-red wavelengths (400nm to 1,000nm). Based on a ratiometric assessment, the inventors of the present invention discovered and evaluated the following six laser wavelengths (635±5nm, 658±5nm, 733±5nm, 808±5nm, 825±5nm, 950±5nm). N= 3 for the purposes of this present invention. A minimum of three different laser wavelengths are required to generate two ratios/variables for purposes of the ratiometric assessment in order to determine the ripeness of the oil palm FFBs. However, the number of wavelengths can be determined and decided by the user of the present invention. The light source of this present invention comprises 3-coupled laser modules (107) consisting of 3-to-1 fibre optic bundle (102) to emit 3-laser beams with 3-emission wavelengths. The single-core multimode fibre (108) directs and guides the emitted 3-laser beams with 3-emission wavelengths in sequence to the reflective mirror (106). The 3-wavelengths fall within the visible to infra-red region, specifically in the range of between 400nm to 1,000nm. The wavelengths here can be chosen and determined by the user depending on the preference of the user of the present invention. The first wavelength in a range of between 400nm to 750nm is sensitive toward fruit ripeness. The 3- wavelengths chosen by the inventors are 635nm, 658nm and 733nm. The second wavelength in a range of between 751 nm to 1,000 nm is found to be not sensitive toward fruit ripeness. The 3-wavelengths chosen by the inventors are 808nm, 825nm and 950nm. The reflective mirror (106) reflects the emitted 3-laser beams with 3-wavelengths in sequence toward an optical axis of the converging lens (105), whereby the converging lens (105) expands the reflected 3-laser beams with the 3-wavelengths toward the oil palm FFB. The photodetector (104) detects 3- reflected power of the 3-wavelengths of the at least one reflected light beam (E) from the oil palm FFB. The detection in done sequentially, one by one. A fused silica multimode fiber that has low attenuation loss is used for the purposes of the present invention. The single-core multimode fibre (108) enables one laser beam to be propagated at a time. Multimode fibres are preferred because the fibre core size is bigger and it has larger damage threshold, ^{therefore able to handle higher laser power.} The inventors have tested the diameter of the converging lens (105) in a range of between 13am to 23cm which is sufficient for the work range of between 4m to 8m. The larger the lens diameter, the higher the optical intensity of the reflected laser beam (X). The coaxial laser and photodetector (104) arrangement (in which the optical axes (A) of the laser light and photodetector (104) are parallel and overlapping which relies on only one converging lens (105) for expanding the laser beam and reflected beam to be collected by photo detector. The diameter of the emitted laser beam (F) on the oil palm FFB is in a range of between 20cm to 25cm. The ratiometric assessment is calculated in real-time by an Arduino microcontroller whereby the calculated ratios are variables for a discriminant analysis. Ripeness of the oil palm FFBs can be determined from the calculated ratios as long as the calibrated data for the ratios for different ripeness are known. The discriminant analysis are based on the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength. As an example: • I635 refers to the detected power of the reflected light beam (X) at a wavelength of 635nm • ratios for the discriminant analysis are a) I635/I825 and b)I733nm/I825 The novel configuration of the multi-wavelength remote sensing device, in which only one converging lens (105) is required or employed for this purpose, with the use of one reflective mirror (106) and a photodetector (104) positioned at the optical axis of the light source which results in the optical axis of the emitted light beam (F) from the laser light and the optical axis of the reflected light beam from the oil palm FFBs to the photodetector (104) are parallel and overlapping. This innovative configuration yields a coaxial laser light and photodetector (104) arrangement suitable for the purposes of the present invention and such device per present invention has not been seen to be deployed in oil palm estates by others in the industry based on the inventor’s knowledge. The user of the present invention can manufacture the laser remote sensing device any size they choose in order to make it as compact as feasible for effective application in oil palm estates with a long work range or distance. The unique configuration remains constant regardless of the size of the laser remote sensing device and yields the same accurate results despite of its size when detecting ripeness of the oil palm FFBs in the estates. Other characteristics of the method and device, depending on the size required by the user of the present invention, can be varied and customized accordingly without compromising the new optical arrangement of the present invention, such as: - diameter of the lens; - first wavelength; - second wavelength; - calibrated data for ratios (ratiometric assessment); - diameter of the emitted laser beam (F); - field of view (D); - focal length (B); -^{distance between converging lens (105) and photodetector (104); and} - others.

EXAMPLES Example 1 It is known that ripe oil palm FFB fruitlets have the highest oil content and oil content deteriorates when the oil palm FFB fruitlets becomes overripe. The moisture and lipid content of oil palm fruitlets have become indications for evaluating their maturation stage. Unripe fruitlets have more moisture and lipids than ripe fruitlets, accounting for 80.1% and 5.9% of the total content, respectively. The moisture content of fruitlets shifts to fatty content as they mature. Only 24.7% and 58.3% of the mature fruitlet are present. [Source: Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review, MDPI Open Access Journals] The following six laser wavelengths are investigated: 635nm, 658nm, 733nm, 808nm, 825nm and 950nm. The first wavelengths are 635nm, 658nm, 733nm. The second wavelengths are 808nm, 825nm, 950nm. The following two ratios are tested to detect ripeness of the oil palm FFB: •^{I635 / I808} • I980 / I808 It is found that these two ratios are sensitive to the ripeness of the oil palm FFB. A discriminant analysis plot for oil palm FFB for different ripeness levels are obtained per Figure 3. At I635/I808 = 0.66, a clear discriminant line separating the unripe and under-ripe groups may be visible. This discriminant line varies according to the size of the remote sensing device made and the current parameters and settings. As a result, the value is set once the item is manufactured for use. The user of the present invention can manufacture the laser remote sensing device any size they choose in order to make it as compact as feasible for effective application in oil palm estates with a long work range or distance. The unique configuration remains constant regardless of the size of the laser remote sensing device and yields the same accurate results despite of its size when detecting ripeness of the oil palm FFBs in the estates. Figure 4 illustrates the correlations between O/DM (oil / dry mesocarp) and moisture content for the I635/I808 ratio. The oil content data were collected from the evaluated oil palm FFBs immediately following the measurement with the device of the present invention. It can be shown that O/DM is linearly proportional to I635/I808, however it approaches saturation when I635/I808 > 0.6. The moisture content of the oil palm FFBs on the other hand, decreases with increasing I635/I808 ratio and reaches below 40% when I635/I808 > 0.6. These findings are congruent with the visual inspection results and proofs that the method and device of the present invention provides an accurate, simple, fast, effective, consistent, and reliable means of detecting ripeness of oil palm FFBs in real-time in oil palm estates, as opposed to the manual approach which is time-consuming, labour-intensive, and susceptible to biased evaluation and human error, potentially leading to increased harvesting and production costs. Summary: To the best of the inventors' knowledge and based on prior arts available, the method and device of the present invention is not currently used in the industry. All of the prior arts mentioned above do not precisely disclose the method of the present invention. Apart from that, it is not obvious for experts in the field of interest to derive at the method of the present invention simply by reading the prior art documents and/or information as listed above, as the method has been determined by the inventors based on numerous trials / testing conducted, observations and discussions with combined expertise and experience in this field, which parameters and/or combination could not be determined without much effort, testing, and/or a combination As a result, there is still a need in the art for the present invention's approach. As a result, to the best of the inventors' knowledge, the current invention is novel and inventive. The novel optical architecture of the remote sensing device is innovative and has never been employed for real-time detection of ripeness of oil palm FFBs in oil palm estates. There is no such device in use in the industry, and no prior art document is known to reference it. The description and accompanying illustrations show that various modifications to the embodiments described herein are obvious to those knowledgeable in the art. The description is not meant to be limited to the embodiments depicted in the accompanying figures, but rather to provide the fullest extent possible in accordance with the innovative and creative features disclosed. As a result, all other such alternatives, modifications, and variants that come within the scope of the present invention and appended claims are expected to be retained by the invention.

Claims

CLAIMS 1. A method for detecting ripeness of a predetermined object (101) using a non-destructive and non-invasive sensing means, wherein the sensing means is a multi-wavelength optical sensing means. 2. The method of Claim 1, wherein the multi-wavelength optical sensing means is a multi- wavelength remote sensing device. 3. The method of Claim 2, wherein the multi-wavelength remote sensing device comprises at least ^{one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle} (102), a single-core multimode fibre (108) and at least one band-pass filter (103). 4. The method of Claim 3, wherein the at least one sensor is a photodetector (104). 5. The method of Claim 3, wherein the at least one lens is one converging lens (105). 6. The method of Claim 3, wherein the at least one mirror is one reflective mirror (106) with reflectivity of more than 90%. 7. The method of Claim 3, wherein the at least one light source is concentrated, monochromatic, has a specific wavelength, coherent, directional and able to travel long distances. 8. The method of Claim 3, wherein a first optical axis is an optical axis of an at least one emitted light beam (F) from the at least one light source. 9. The method of Claim 4, wherein a second optical axis is an optical axis of an at least one reflected light beam (E) from the predetermined object (101) to the photodetector (104). 10. The method of Claims 8 and 9, wherein the first optical axis and the second optical axis are parallel and overlapping axes (A). 11. The method of Claim 3, wherein the at least one band-pass filter (103) is an optical band-pass filter positioned in front of the photodetector (104) on the parallel and overlapping first and second optical axes (A). 12. The method of Claim 6, wherein the reflective mirror (106) is positioned on the parallel and overlapping first and second optical axes (A) in between the converging lens (105) and a focal point (C) of the converging lens (105).

13. The method of Claim 4, wherein the photodetector (104) is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). 14. The method of Claim 13, wherein the first position is whereby a distance between the photodetector (104) and the one converging lens (105) is a focal length (B) of the one converging lens (105). 15. The method of Claim 13, wherein the second position is whereby a distance between the photodetector (104) and the one converging lens (105) is longer than the focal length (B) of the one ^{converging lens (105).} 16. The method of Claim 13, wherein the third position is whereby a distance between the photodetector (104) and the one converging lens (105) is shorter than the focal length (B) of the one converging lens (105). 17. The method of Claim 3, wherein the at least one light source comprises N-coupled laser modules (107) consisting of N-to-1 fibre optic bundle (102) to emit N-laser beams with N-emission wavelengths. 18. The method of Claim 17, wherein the single-core multimode fibre (108) directs and guides the emitted N-laser beams with N-emission wavelengths in sequence to the reflective mirror (106). 19. The method of Claim 17, wherein the N is at least 2. 20. The method of Claim 18, wherein the reflective mirror (106) reflects the emitted N-laser beams with N-wavelengths in sequence toward an optical axis of the converging lens (105), whereby the converging lens (105) expands the reflected N-laser beams with the N-wavelengths toward the predetermined object (101). 21. The method of Claim 17, wherein the N-wavelengths is in a range of between 400nm to 1,000nm. 22. The method of Claim 3, wherein a wavelength of the at least one band-pass filter (103) is in a range of between 600nm to 850nm. 23. The method of Claim 17, wherein the photodetector (104) detects N-reflected power of the N- wavelengths of the at least one reflected light beam from the predetermined object (101) in sequence. 24. The method of Claim 1, wherein the ripeness of the predetermined object (101) is detected in real time by a microcontroller using a ratiometric means. 25. The method of Claim 24, wherein the ratiometric means refer to a ratio of a first reflected power of a first wavelength from the N-emission wavelengths of the at least one reflected light beam to a second reflected power of a second wavelength from the N-emission wavelengths of the at least one reflected beam. 26. The method of Claim 25, wherein the first wavelength is in a range of between 400nm to 750nm. 27. The method of Claim 25, wherein the second wavelength is in a range of between 751nm to ^1,000nm. 28. The method of Claim 1, wherein the predetermined object (101) refers to a first fruit, a second fruit and a third fruit. 29. The method of Claim 25, wherein the first wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. 30. The method of Claim 25, wherein the second wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. 31. The method of Claim 25, wherein the first reflected power of the first wavelength of the third fruit is greater than the first reflected power of the first wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101). 32. The method of Claim 25, wherein the first reflected power of the first wavelength of the second fruit is greater than the first reflected power of the first wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). 33. The method of Claim 25, wherein the second reflected power of the second wavelength is identical for the first fruit, second fruit and the third fruit. 34. The method of Claim 25, wherein the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the third fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101). 35. The method of Claim 25, wherein the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). 36. The method of Claim 28, wherein the first fruit refers to unripe oil palm fresh fruit bunches (FFB). 37. The method of Claim 28, wherein the second fruit refers to under-ripe oil palm FFB. 38. The method of Claim 28, wherein the third fruit refers to ripe oil palm FFB. 39. A remote sensing device for detecting ripeness of a predetermined object (101) using a non- destructive and non-invasive multi-wavelength optical sensing means. 40. The device of Claim 38, wherein the multi-wavelength remote sensing device comprises at least one sensor, at least one mirror, at least one light source, at least one lens, at least one fibre optic bundle (102), a single-core multimode fibre (108) and at least one band-pass filter (103). 41. The device of Claim 40, wherein the at least one sensor is a photodetector (104). 42. The device of Claim 40, wherein the at least one lens is one converging lens (105). 43. The device of Claim 40, wherein the at least one mirror is one reflective mirror (106) with reflectivity of more than 90%. 44. The device of Claim 40, wherein the at least one light source is concentrated, monochromatic, has a specific wavelength, coherent, directional and able to travel long distances. 45. The device of Claim 40, wherein a first optical axis is an optical axis of an at least one emitted light beam (F) from the at least one light source. 46. The device of Claim 41, wherein a second optical axis is an optical axis of an at least one reflected light beam (E) from the predetermined object (101) to the photodetector (104). 47. The device of Claims 45 and 46, wherein the first optical axis and the second optical axis are parallel and overlapping axes (A). 48. The device of Claim 40, wherein the at least one band-pass filter (103) is an optical band-pass filter positioned in front of the photodetector (104) on the parallel and overlapping first and second optical axes (A).

49. The device of Claim 43, wherein the reflective mirror (106) is positioned on the parallel and overlapping first and second optical axes (A) in between the converging lens (105) and a focal point (C) of the converging lens (105). 50. The device of Claim 41, wherein the photodetector (104) is positioned at a first position, second position or a third position on the parallel and overlapping first and second optical axes (A). 51. The device of Claim 50, wherein the first position is whereby a distance between the photodetector (104) and the one converging lens (105) is a focal length (B) of the one converging lens ^(105). 52. The device of Claim 50, wherein the second position is whereby a distance between the photodetector (104) and the one converging lens (105) is longer than the focal length (B) of the one converging lens (105). 53. The device of Claim 50, wherein the third position is whereby a distance between the photodetector (104) and the one converging lens (105) is shorter than the focal length (B) of the one converging lens (105). 54. The device of Claim 40, wherein the at least one light source comprises N-coupled laser modules (107) consisting of N-to-1 fibre optic bundle (102) to emit N-laser beams with N-emission wavelengths. 55. The device of Claim 54, wherein the single-core multimode fibre (108) directs and guides the emitted N-laser beams with N-emission wavelengths in sequence to the reflective mirror (106). 56. The device of Claim 54, wherein the N is at least 2. 57. The device of Claim 55, wherein the reflective mirror (106) reflects the emitted N-laser beams with N-wavelengths in sequence toward an optical axis of the converging lens (105), whereby the converging lens (105) expands the reflected N-laser beams with the N-wavelengths toward the predetermined object (101). 58. The device of Claim 54, wherein the N-wavelengths is in a range of between 400nm to 1,000nm. 59. The device of Claim 40, wherein a wavelength of the at least one band-pass filter (103) is in a range of between 600nm to 850nm. 60. The device of Claim 54, wherein the photodetector (104) detects N-reflected power of the N- wavelengths of the at least one reflected light beam from the predetermined object (101) in sequence. 61. The device of Claim 39, wherein the ripeness of the predetermined object (101) is measured in real time by a microcontroller using a ratiometric means. 62. The device of Claim 61, wherein the ratiometric means refer to a ratio of a first reflected power of a first wavelength from the N-emission wavelengths of the at least one reflected light beam to a second reflected power of a second wavelength from the N-emission wavelengths of the at least one reflected beam. ^{63. The device of Claim 62, wherein the first wavelength is in a range of between 400nm to 750nm.} 64. The device of Claim 62, wherein the second wavelength is in a range of between 751nm to 1,000nm. 65. The device of Claim 39, wherein the predetermined object (101) refers to a first fruit, a second fruit and a third fruit. 66. The device of Claim 62, wherein the first wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. 67. The device of Claim 62, wherein the second wavelength is identical to determine the ripeness of the first fruit, the second fruit and the third fruit. 68. The device of Claim 62, wherein the first reflected power of the first wavelength of the third fruit is greater than the first reflected power of the first wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101). 69. The device of Claim 62, wherein the first reflected power of the first wavelength of the second fruit is greater than the first reflected power of the first wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). 70. The device of Claim 62, wherein the second reflected power of the second wavelength is identical for the first fruit, second fruit and the third fruit. 71. The device of Claim 62, wherein the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the third fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit with a same distance between the one converging lens (105) and the predetermined object (101).

72. The device of Claim 62, wherein the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the second fruit is greater than the ratio of the first reflected power of the first wavelength to the second reflected power of the second wavelength of the first fruit with a same distance between the one converging lens (105) and the predetermined object (101). 73. The device of Claim 33, wherein the first fruit refers to unripe oil palm fresh fruit bunches (FFB). 74. The device of Claim 33, wherein the second fruit refers to under-ripe oil palm FFB. 75. The device of Claim 33, wherein the third fruit refers to ripe oil palm FFB.