Like the bosses of many food companies, Jeremy Bunch is worried about the impact of climate change on his business.

就像許多糧食公司的老板一樣，杰里米·邦奇也擔(dān)心氣候變化影響他的業(yè)務(wù)。

“Weather and the climate are maybe the number one risk to our company,” says the boss of US flour firm Shepherd’s Grain.

“天氣和氣候可能是我們公司面臨的頭號風(fēng)險”，美國面粉公司Shepherd’s Grain的老板說道。

Based in Idaho, the business sources wheat from farmers across the US Pacific northwest.

該公司總部位于愛達(dá)荷州，從美國太平洋西北地區(qū)的農(nóng)民那里收購小麥。

As weather patterns become more unpredictable, Mr Bunch says: “I need to have a plan B, and plan C, in case plan A fails.”

隨著天氣形態(tài)變得更加難以預(yù)測，邦奇先生表示：“我需要制定B計劃和C計劃，以防A計劃失敗?！?/b>

To help strengthen these plans, Mr Bunch’s company is now using an AI-powered software system called ClimateAi.

為了強(qiáng)化這些計劃，邦奇先生的公司正在使用一款名為ClimateAi的人工智能軟件系統(tǒng)。

Using current and past data, such as from satellite imagery and temperature and rainfall readings, and combining that with future projections, ClimateAi aims to give farmers the most accurate possible, locally-tailored weather forecasts, from one hour to six months ahead.

ClimateAi利用當(dāng)前和過去的衛(wèi)星圖像、溫度、降雨量等數(shù)據(jù)，結(jié)合對未來的預(yù)測，旨在為農(nóng)民提供最準(zhǔn)確的、因地制宜的、提前一小時到六個月的天氣預(yù)報。

It then advises on exactly when to plant and harvest particular crops, and predicts their yields.

然后，該軟件會準(zhǔn)確地建議何時耕種和收獲特定作物，預(yù)測其產(chǎn)量。

Shepherd’s Grain only started using ClimateAi last year, but already most of its 40 plus farmers are now being guided by the app.

該公司去年才開始使用ClimateAi，但這里的40多名農(nóng)民中的大多數(shù)都在使用這款應(yīng)用程序。

“They’re beginning to look at ClimateAi to help them plan for crop management decisions in their wheat crops, the primary crop grown in the region,” says Mr Bunch.

“該地區(qū)的主要作物是小麥，他們正在考慮用ClimateAi幫助他們規(guī)劃小麥作物的管理決策”，邦奇先生說道。

“A forward look at the weather helps our growers decide which crops to plant. The platform knows when to plant, and when the crop will start flowering and producing seed.”

“預(yù)測天氣有助于我們的種植戶決定種植哪種作物。該平臺知道何時種植，作物何時開花結(jié)籽。”

One of the biggest problems facing the seed industry is how to launch climate resilient seeds to market faster and cheaper, says Himanshu Gupta, chief executive of San Francisco-based ClimateAi.

ClimateAi公司的總部位于舊金山，總裁希曼舒·古普塔表示，種子產(chǎn)業(yè)面臨的一個最大難題是如何更快、更便宜地將氣候適應(yīng)性種子投向市場。

“By the time some seed companies do this, in say 10 to 15 years, the climate has already changed,” says Mr Gupta. “We are running against time to launch new seed varieties.”

“等到一些種子公司在10-15年后才將種子投向市場，氣候已經(jīng)發(fā)生了變化，”古普塔先生說道。 “我們正在爭分奪秒地將新型種子投向市場”。

He says that ClimateAi helps these firms to see how specific test seeds have performed in a particular region or locality. “This can help seed companies figure out the optimal locations for growing seeds.”

他說ClimateAi有助于種子公司了解特定試驗種子在特定地區(qū)或地點的表現(xiàn)。 “這可以幫助種子公司弄清楚最適宜的播種地點”。
原創(chuàng)翻譯：龍騰網(wǎng) http://www.top-shui.cn 轉(zhuǎn)載請注明出處


Last year, a study published in scientific journal Nature warned of the potentially dire consequences of numerous crop failures happening at the same time around the world, as a result of the impact of climate change.

去年，科學(xué)雜志《自然》發(fā)表的一項研究警告稱，由于氣候變化的影響，世界各地同時發(fā)生大量的農(nóng)作物歉收可能帶來可怕的后果。

“Simultaneous harvest failures across major crop-producing regions are a threat to global food security,” said the report, which was led by climate scientist Kai Kornhuber from Columbia University’s Lamont-Doherty Earth Observatory.

這份由哥倫比亞大學(xué)拉蒙特-多爾蒂地球觀測站的氣候科學(xué)家凱·科恩胡伯牽頭完成的報告稱，“所有的農(nóng)作物主產(chǎn)區(qū)同時發(fā)生歉收會對全球糧食安全構(gòu)成威脅”。

This warning comes as the world population is expected to reach 10 billion people by 2050, up from eight billion currently, according to the United Nations.

在這一警告發(fā)出之際，聯(lián)合國預(yù)計到2050年，世界人口將從目前的80億增加到100億。

With increased pressure on crops, at the same time as the global population continues to grow, could AI be key to developing new varieties that can better cope with extremes of weather?

在農(nóng)作物面臨的壓力與日俱增，全球人口持續(xù)增長的同時，人工智能能否成為培育更好地應(yīng)對極端氣候新品種的關(guān)鍵？

In the city of Arusha in Tanzania, David Guerena, agricultural scientist at the International Center for Tropical Agriculture, is leading a project called Artemis.

在坦桑尼亞的阿魯沙市，國際熱帶農(nóng)業(yè)中心的農(nóng)業(yè)科學(xué)家大衛(wèi)·蓋雷納正在牽頭一個名為“阿耳忒彌斯”的項目。

Funded by the Bill and Melinda Gates Foundation, this is using AI to help breed more resilient crops. Specifically the AI is helping speed up work called phenotyping.

該項目在比爾及梅琳達(dá)·蓋茨基金會的資助下，正在利用人工智能幫助培育抗逆性更強(qiáng)的作物。具體來說，人工智能正在幫助加快表型分析工作。

This is the visual studying of new crop varieties based on observations of their characteristics, such as how many flowers, pods or leaves that a plant has.

表型分析是通過觀察作物新品種的特征而進(jìn)行的視覺研究，例如作物開出多少花朵、豆莢、葉子。

“Traditionally it takes around 10 years to develop a new crop variety,” explains Mr Guerena. “But given the pace of climate change, this timefrx is no longer viable."

“傳統(tǒng)上培育作物新品種需要十年左右”，蓋雷納先生說道?！暗紤]到氣候變化的速度，這個周期已經(jīng)行不通了”。

He adds that the phenotyping work traditionally relied on the human eye. “But humans are just not doing this consistently, with the high levels of precision necessary, to make subtle, yet important, plant sextions,” says Mr Guerena.

他補(bǔ)充說，表型分析工作傳統(tǒng)上依賴于人眼?！暗祟惛咀霾坏匠种院?，也達(dá)不到細(xì)致重要的作物選種所需要的精準(zhǔn)度”，蓋雷納先生說道。

“It can be over 30?C in the field. It’s just tiring, and fatigue affects data quality.”

“農(nóng)田的溫度可能超過30°C，這工作很乏味，疲勞會影響數(shù)據(jù)質(zhì)量”。

Instead, growers involved in the project are taking photos of their crops through an app on a smartphone. The trained AI can then quickly analyses, records, and reports what it sees.

然而，參與該項目的種植者正在通過智能手機(jī)上的APP給農(nóng)作物拍照，經(jīng)過訓(xùn)練的人工智能可以快速地分析、記錄、報告它所看到的內(nèi)容。

“Computers can count every flower or pod, from every plant, every day without getting tired,” says Mr Guerena. “This is really important as the number of flowers in bean plants correlate to the number of pods which directly influence yields.

“計算機(jī)可以每天計數(shù)每株植物上的每一朵花或每個豆莢，而不會感到疲倦”，蓋雷納先生說道?！斑@非常重要，因為豆類植物的花朵數(shù)量關(guān)系到豆莢數(shù)量，后者對產(chǎn)量有直接影響。

“Data can be so complicated, to understand what’s happening, but AI can be used to make sense of that complicated data and pick up patterns, show where we need resources, show recommendations.

“透過數(shù)據(jù)來了解情況可能非常復(fù)雜，但人工智能可以用來理解復(fù)雜的數(shù)據(jù)和掌握規(guī)律，告訴我們需要資源的地方，并提供建議。

“Our plant breeders estimate that with the better data from the AI computer vision they may be able to shorten the breeding cycle to only a few years.”

“我們的植物育種家估計，他們借助人工智能計算機(jī)視覺提供的優(yōu)質(zhì)數(shù)據(jù)，或許能夠?qū)⒂N周期縮短至幾年”。

In North Carolina, Avalo is an agriculture technology or “agri-tech” business also working to create climate-resilient crops. It does this by using AI to help study a crop’s genetics.

Avalo是一家位于北卡羅來納州的農(nóng)業(yè)技術(shù)公司，同樣致力于培育氣候適應(yīng)性作物，辦法是利用人工智能來幫助研究作物的遺傳特征。

“Our process starts with genomic data about crops, for example, the sequences of various varieties,” says Rebecca White, Avalo’s chief operating officer.

“我們從農(nóng)作物的基因組數(shù)據(jù)著手，例如不同品種的基因序列，”Avalo公司的首席運營官麗貝卡·懷特說道。

“For example, with different tomatoes, there’s some small differences in genomes that give them different traits, for example different flavours, pesticide-resilient profiles. Our machine-learning programme is able to take these small differences across a number of varieties and see which genomes are important for what traits.”

“例如，不同品種的西紅柿在基因組上存在細(xì)微差異，使它們的性狀各不相同，例如口味、耐藥性等。我們的機(jī)器學(xué)習(xí)程序能夠識別不同品種之間的細(xì)微差異，了解哪些基因組對哪些性狀很重要”。

Using their tech they have been able to create a broccoli that matures in a greenhouse in 37 days rather than the standard 45 to 60 days, says Ms White.

懷特女士說，他們利用這項技術(shù)得以培育出一種西蘭花，它在溫室大棚中的成熟周期為37天，而普通西蘭花為45-60天。

“Broccoli produced on that timescale can get additional growth cycles, and it saves carbon footprint and improves the environmental impact.”

“這一生長周期的西蘭花可以增加種植批次，并且減少碳足跡和對環(huán)境的影響”。

Avalo, which works with companies in Asia and North America, is also working to make rice resistant to frost, and potatoes more tolerant to drought.

Avalo公司還與亞洲和北美洲的公司合作，致力于培育具有抗霜性的水稻和耐寒性更強(qiáng)的馬鈴薯。

“Our core technologies can identify the genetic basis of complex traits with minimal training and, via sequencing and predictive analysis, quickly and inexpensively assess and model new plant varieties,” says Ms White.

“我們的核心技術(shù)能以最少的訓(xùn)練來識別復(fù)雜性狀的遺傳基礎(chǔ)，通過基因測序和預(yù)測分析對新的作物品種進(jìn)行快速低廉的評估和建?！?，懷特女士說道。

“We are creating new varieties for diverse crops that are developed five-times faster and for a fraction of the cost compared to traditional breeding.”

“我們正在為各種作物培育新品種，速度比傳統(tǒng)育種快五倍，但成本只是后者的一小部分”。

However, while AI can help mitigate the impact of climate-related weather, and enhance crop resilience, there are a number of challenges when it comes to using AI in agriculture, says Kate E Jones, professor of ecology and biodiversity at University College London.

然而，倫敦大學(xué)學(xué)院生態(tài)與生物多樣性教授凱特E·瓊斯表示，雖然人工智能有助于減輕氣候相關(guān)天氣的影響，并增強(qiáng)作物的抗逆性，但在農(nóng)業(yè)領(lǐng)域使用人工智能仍面臨許多挑戰(zhàn)。

“The effectiveness of AI in ensuring food security also depends on addressing challenges such as data quality, technology accessibility… while acknowledging that AI is one tool among many in a comprehensive strategy for sustainable and resilient agriculture.”

“人工智能在確保糧食安全的有效性方面還取決于能否解決數(shù)據(jù)質(zhì)量、技術(shù)普及度等挑戰(zhàn)……但也要承認(rèn)人工智能是可持續(xù)性和抗逆性農(nóng)業(yè)綜合戰(zhàn)略中的眾多工具之一”。