带GPS的狗，电子鼻和可倾倒完美啤酒的机器人 (GPS-Wearing Dogs, an Electronic Nose, and a Robot That Pours the Perfect Beer)

Bushfires in Australia are as commonplace as kangaroos and koalas. A hot, dry climate regularly sets the stage for conflagrations that endanger human lives, property, and wildlife and threaten one of the country’s top economic industries: wine. Fires during summer 2019–2020 decimated entire vineyards in South Australia, Victoria and New South Wales, but smoke, which was far more widespread and insidious, seeped into grapes and into fermenting barrels, yielding unpleasant, unsaleable product. Although the full extent of the damage caused has not yet been calculated, analysis from the Australian Wine Research Institute indicates that smoke taint alone costs the country’s wine industry tens to hundreds of millions of dollars each time a high fire season occurs.

澳大利亚的丛林大火与袋鼠和考拉一样普遍。 炎热干燥的气候经常为引发大火的舞台，大火危及人类的生命，财产和野生生物，并威胁该国最重要的经济产业之一：葡萄酒。 2019-2020年夏季的大火烧毁了南澳大利亚，维多利亚和新南威尔士州的整个葡萄园，但烟尘更广泛，更阴险，渗入葡萄和发酵桶中，产生令人不愉快的，无法销售的产品。 尽管尚未计算出造成的破坏的全部程度，但澳大利亚葡萄酒研究所的分析表明，每当发生高火季节时，仅烟味就会使该国的葡萄酒业损失数千万至数亿美元。

Advances in a wide range of technologies could help growers and winemakers mitigate the negative impact of smoke taint and other unpredictable anomalies, such as frost, drought, pests, and disease — and not just in Australia, but around the world. The Vineyard of the Future, led by Associate Professor Sigfredo Fuentes, a plant physiologist at the University of Melbourne, is an international consortium of scientists conducting leading-edge research to amass high-resolution data from vine to glass and analyze it in meaningful ways. Drones, satellite imaging, video analysis, and plant and people sensors combined with artificial intelligence — collectively called “digital agriculture” — give producers and sellers of wine an advantage in an industry riddled with uncertainty.

广泛的技术进步可以帮助种植者和酿酒师减轻烟味和其他不可预测的异常现象的负面影响，例如霜冻，干旱，病虫害和疾病-不仅在澳大利亚，而且在世界范围内。 由墨尔本大学植物生理学家Sigfredo Fuentes副教授领导的“未来葡萄园”是一个国际科学家联盟，旨在进行前沿研究，以收集从葡萄到玻璃的高分辨率数据，并以有意义的方式进行分析。 无人机，卫星成像，视频分析以及植物和人体传感器与人工智能相结合(统称为“数字农业”)使葡萄酒的生产商和销售商在充满不确定性的行业中享有优势。

“This research could take out the guesswork from viticulture and winemaking, making them more predictable,” says Fuentes.

Fuentes说：“这项研究可以消除葡萄栽培和酿酒业的猜测，使它们更具可预测性。”

在藤上 (On the Vine)

Good wine starts on the vine. Delectable grapes depend on the weather and cultivation strategies, including irrigation, fertilization, pest control, and canopy management. Growers typically prefer smaller grape berries, which yield more grape skin and therefore more compounds, such as anthocyanins, tannins, resveratrol, and polyphenols, that influence flavor and aroma. Lower yields of grapes with top-quality traits may actually produce higher revenue per acre, so it’s essential to maintain the balance between the vegetative and reproductive sections of grapevines, says Fuentes. “No recipe fits all cases for viticulture, and here the implementation of new and emerging technologies is critical to assess all these factors to obtain good products,” he says.

好酒从葡萄藤开始。 美味的葡萄取决于天气和种植策略，包括灌溉，施肥，害虫控制和林冠管理。 种植者通常更喜欢较小的葡萄浆果，因为葡萄浆果会产生更多的葡萄皮，因此会产生更多影响风味和香气的化合物，例如花色苷，单宁，白藜芦醇和多酚。 富恩特斯说，具有顶级品质的葡萄单产降低实际上可能会增加每英亩的收入，因此保持葡萄的营养与生殖之间的平衡至关重要。 他说：“没有任何一种方法适合葡萄栽培的所有情况，在这里，实施新兴技术对于评估所有这些因素以获得优质产品至关重要。”

Fuentes and his colleagues have developed technologies that rely on infrared thermal imagery and near infrared spectroscopy (NIR) analysis coupled with supervised machine learning modeling to measure smoke contamination in leaves and assess smoke taint in the grapes. Infrared cameras reveal a vine’s heat signature, which is disrupted by smoke. Using MATLAB®, Fuentes and his team developed computer vision algorithms that use the heat signature to predict smoke contamination in canopies with 96% accuracy.

Fuentes和他的同事开发了依靠红外热图像和近红外光谱(NIR)分析以及有监督的机器学习建模技术来测量叶片中烟气污染并评估葡萄中烟味的技术。 红外热像仪显示出葡萄树的热感，并被烟气打断。 Fuentes和他的团队使用MATLAB®开发了计算机视觉算法，该算法使用热量特征预测顶盖中的烟雾污染，准确度达到96％。

NIR data obtained using non-invasive handheld instruments reveals a chemical fingerprint from berries and wines that indicates specific smoke-related compounds and concentrations in near real time with high accuracy. Conventional methods available to growers require them to send grapes to a lab and wait six days or more for the results. But having the information in real time could help growers make decisions, such as whether to harvest untainted grapes separate from tainted ones, in order to minimize waste.

使用非侵入式手持式仪器获得的NIR数据揭示了浆果和葡萄酒中的化学指纹，可近乎实时地准确显示与烟有关的特定化合物和浓度。 种植者可以使用的传统方法要求他们将葡萄送到实验室，并等待六天或更长时间才能获得结果。 但是，实时获取信息可以帮助种植者做出决策，例如是否将未受污染的葡萄与受污染的葡萄分开收获，以最大程度地减少浪费。

Further research has been conducted into predicting quality traits of potential wines from vineyards even before harvest. By incorporating other variables such as weather data inputs and known aroma profiles from previous vintages as targets, machine learning models were trained to predict the aroma profile of the wine coming from the vines.

甚至在收获之前，已经进行了进一步的研究来预测来自葡萄园的潜在葡萄酒的品质特征。 通过合并其他变量(例如天气数据输入和来自先前年份的已知香气特征)作为目标，机器学习模型得到了训练，以预测来自葡萄藤的葡萄酒的香气特征。

An app called VitiCanopy uses a smartphone’s GPS and camera to help a grower measure a canopy’s size, density, and vigor. From an image, the app’s computer vision algorithm calculates the leaf area index with a snapshot. Known as LAI, this important metric correlates the amount of sunlight dappling the berries, the canopy’s microclimate, the grape’s composition, and ultimately yield. Wine growers are trying to create a balance between the leaves, the shoots, and the fruit, says Fuentes. “If you have too vigorous of a canopy, the flavor and aroma profiles of the final wine are going to have too much acidity and green respectively,” he says. The information from the app enables a grower to make decisions about trimming a canopy, applying fertilizer, and increasing or decreasing irrigation. “It’s all about balance,” says Fuentes.

名为VitiCanopy的应用程序使用智能手机的GPS和摄像头来帮助种植者测量树冠的大小，密度和活力。 该应用程序的计算机视觉算法从图像中计算出带有快照的叶子区域索引。 被称为LAI的这一重要指标与使浆果发出的阳光量，树冠的微气候，葡萄的成分以及最终产量相关。 富恩特斯说，葡萄酒种植者正在努力在叶子，枝条和果实之间建立平衡。 他说：“如果您的檐篷过于活跃，那么最终葡萄酒的风味和香气将分别具有太多的酸度和绿色。” 该应用程序提供的信息使种植者可以决定修剪树冠，施用肥料以及增加或减少灌溉量。 “这全都与平衡有关，” Fuentes说。

NIR and machine learning algorithms can also lend clues to grape ripeness. Fuentes explains that certain compounds, released from dying cells inside the grape as it ripens, influence its aroma and flavor. Different grapes require different percentages of cellular death to reach their peak ripeness. “We propose measuring the cell vitality of berries before doing the winemaking to predict the quality of the wine using digital tools developed,” he says.

NIR和机器学习算法也可以为葡萄成熟提供线索。 Fuentes解释说，葡萄成熟时从垂死的细胞中释放出来的某些化合物会影响其香气和风味。 不同的葡萄需要不同百分比的细胞死亡才能达到成熟高峰。 他说：“我们建议在酿酒前使用成熟的数字工具测量浆果的细胞活力，以预测葡萄酒的质量。”

鼻子上 (On the Nose)

Among the dozens of variables affecting — and potentially devastating — vineyards, an insect called phylloxera may be one of the most notorious. In the mid-19th century, French vintners unknowingly imported the insect from the United States when they brought American vine material, contaminated shoes or tools to Europe. Although phylloxera preferred to dine harmlessly on the leaves of American vines, when they discovered French vines, they went for the roots. The Great French Wine Blight nearly decimated the country’s wine industry in just a couple of decades. After several failed attempts to eradicate the insect, French vintners begrudgingly grafted their vines to American vine roots, creating plants that could thrive in French soils and resist phylloxera.

在影响甚至可能毁灭性葡萄园的数十种变量中，一种叫做根瘤蚜的昆虫可能是最臭名昭著的一种。 在19世纪中叶，法国葡萄酒商人在将美国的葡萄树材料，受污染的鞋子或工具带到欧洲时不知不觉地从美国进口了这种昆虫。 尽管根瘤蚜喜欢在美国葡萄藤的叶子上进行无害的用餐，但是当他们发现法国葡萄藤时，他们还是选择了根。 短短几十年间，法国葡萄酒大疫病几乎毁了该国的葡萄酒业。 经过几次失败的根除昆虫尝试，法国葡萄酒商将其藤蔓嫁接到美国藤蔓根上，创造出可以在法国土壤中生长并抵抗根瘤蚜的植物。

Today, phylloxera remains a threat that is difficult to detect. Early signs, such as leaf discoloration and general canopy wilting, are frequently confused for water and fertilizer stress, and vintners are motivated to find a more reliable identification method. One approach has gone to the dogs — in a good way. With a nose containing 300 million more smell receptors than a human’s, resulting in 100 times the sensitivity, dogs are being trained by researchers in the Vineyard of the Future to recognize the scent of pheromones released by phylloxera insects as well as other chemical compounds produced by the insect.

如今，根瘤菌仍然是一种难以发现的威胁。 早期迹象，例如叶片变色和一般冠层萎缩，经常会因水分和肥料压力而混淆，酿酒师也被激励寻找更可靠的鉴定方法。 一种方法很好地解决了问题。 鼻子的气味感受器比人类的气味感受器多3亿，灵敏度达到人类的100倍，未来的葡萄园的研究人员正在对狗进行训练，以认识到根瘤蚜虫释放的信息素以及由其产生的其他化学物质的气味。昆虫。

Wearing a backpack equipped with GPS-enabled smartphone, a dog will traverse a vineyard, its nose to the ground. Tracking algorithms developed using MATLAB Mobile™ detect the dog’s location as well as its motion. Different actions such as running, walking, and sitting when a scent is detected are added to a map to pinpoint problems in vineyard. “The app creates a log file for all of the points where the dog signals the handler by sitting, crouching or scratching,” says Claudia Gonzalez Viejo, a postdoctoral fellow working with Fuentes. The grower can then target inspections to those locations, saving time.

一只狗戴着配备有GPS功能的智能手机的背包，将穿越葡萄园，其鼻子直指地面。 使用MATLAB Mobile™开发的跟踪算法可以检测狗的位置及其运动。 在检测到气味时，可以将跑步，步行和坐姿等不同动作添加到地图中，以查明葡萄园中的问题。 与Fuentes合作的博士后研究员Claudia Gonzalez Viejo说：“该应用程序会为狗通过坐着，蹲下或抓挠向操作员发出信号的所有点创建一个日志文件。” 然后，种植者可以将检查目标对准那些位置，从而节省时间。

While the dogs were highly skilled at locating pests, they weren’t very good at determining the perfect beer aroma. To supplement the expert dog noses, Fuentes and his team have developed a low-cost, portable electronic nose, or e-nose, that has an array of sensors that are able to detect nine different gases, including ethanol, carbon dioxide, carbon oxide, methane, and hydrogen peroxide. Gonzalez Viejo helped design the e-nose to scrutinize beer samples and predict aromas. But, she says, it has a wide range of applications, and could be tweaked to detect smoke damage in vineyards. Gonzalez Viejo envisions the technology being combined with a dog detector, used as a handheld device, or mounted to a drone and flown down rows. “We can take the e-nose anywhere,” she says.

尽管这些狗在定位害虫方面非常熟练，但是它们并不能很好地确定啤酒的香气。 为了补充专业的狗鼻，Fuentes和他的团队开发了一种低成本的便携式电子鼻或电子鼻，该鼻具有一系列传感器，能够检测九种不同的气体，包括乙醇，二氧化碳，二氧化碳，甲烷和过氧化氢。 Gonzalez Viejo帮助设计了电子鼻，以仔细检查啤酒样品并预测香气。 但是，她说，它的应用范围很广，可以对其进行调整以检测葡萄园中的烟气损害。 Gonzalez Viejo设想将这项技术与狗探测器结合使用，用作手持设备，或者安装在无人机上并向下飞行。 她说：“我们可以在任何地方使用电子鼻”。

在玻璃上 (In the Glass)

For all of the work growers and producers do to make a quality wine, what constitutes good is subjective. “The best wine is the wine that you like,” says Fuentes.

对于种植者和生产者为制作优质葡萄酒所做的所有工作，构成良好的东西都是主观的。 “最好的葡萄酒是您喜欢的葡萄酒，” Fuentes说。

Ultimately, understanding consumer reaction is key to selling wine, and Vineyard of the Future researchers have developed technology for that, too. The system, which was refined using beer but applies to wine and sparkling wine, incorporates a robotic arm, cameras, and the e-nose. It begins with a perfect pour from the robotic arm, designed to fill a glass the same way each time without tiring. High-definition cameras trained on the beer capture visual data, including color, foam formation and dissipation, and bubble size. An e-nose, positioned over the top of the glass, measures the gases released. Computer vision and machine learning algorithms crunch the camera and sensor information and position the beer amid a library of 250 others that have been previously analyzed.

最终，了解消费者的React是销售葡萄酒的关键，“未来葡萄园”的研究人员也为此开发了技术。 该系统使用啤酒精制而成，但适用于葡萄酒和起泡酒，该系统集成了机械臂，摄像头和电子鼻。 它从机器人手臂的完美倾倒开始，每次倾倒时都以相同的方式填充玻璃而不会产生疲劳。 经过啤酒训练的高清摄像机可以捕获视觉数据，包括颜色，泡沫的形成和消散以及气泡大小。 电子鼻位于玻璃顶部，用于测量释放的气体。 计算机视觉和机器学习算法处理相机和传感器信息，并将啤酒放置在250多个先前已分析过的库中。

Aroma profiles conducted with the sensors were 97% accurate. Such technology could be attractive to craft brewers interested in maintaining consistency and quality control. “You can test every batch and get instant results,” says Gonzalez Viejo.

用传感器进行的香气分析准确率为97％。 此类技术对于有兴趣保持一致性和质量控制的精酿啤酒制造商可能很有吸引力。 “您可以测试每个批次并获得即时结果，”冈萨雷斯·维耶霍说。

The team has even added consumer reaction to mix. Researchers used video cameras, infrared thermal imagery, and brain wave headsets to measure heart rate, body temperature, brainwaves, and facial expressions of staff and student participants as they drank different beers and wines or consumed food products. Their assessments of foam, color, aroma, mouthfeel, taste, flavor, and overall likeness of beers are being paired with the visual and e-nose data collected during a pour to increase accuracy.

该团队甚至增加了消费者的React。 研究人员使用摄像机，红外热像仪和脑电波头戴式耳机来测量员工和学生饮用不同啤酒和葡萄酒或食用食品时的心率，体温，脑电波和面部表情。 他们对啤酒的泡沫，颜色，香气，口感，味道，风味和啤酒总体相似度的评估与浇注期间收集的视觉和电子鼻数据相结合，以提高准确性。

Viticulture, winemaking, and brewing are part art form, part science. As technology advances and scientific understanding of the processes occurring in the soil, the root system, the plant, the canopies, and the atmosphere deepens, science may find an advantage. As wine and beer become more popular and demand grows, especially in a world with changing climate, emerging technologies could give growers and producers something to toast.

葡萄栽培，酿酒和酿造是艺术形式，也是科学。 随着技术的进步和对土壤，根系，植物，树冠和大气中发生的过程的科学理解的加深，科学可能会找到优势。 随着葡萄酒和啤酒变得越来越受欢迎和需求增长，特别是在气候变化的世界中，新兴技术可以为种植者和生产者敬酒。