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本文導(dǎo)讀目錄：

1、現(xiàn)代農(nóng)業(yè)新技術(shù)的論文

2、現(xiàn)代農(nóng)業(yè)智能改造傳統(tǒng)農(nóng)業(yè)的14種方式【中英雙語】

3、現(xiàn)代農(nóng)業(yè)智能轉(zhuǎn)型，新農(nóng)人引得回留得住

4、現(xiàn)代農(nóng)業(yè)有哪些新思維、新技術(shù)、新玩法？

現(xiàn)代農(nóng)業(yè)新技術(shù)的論文 ♂

現(xiàn)代農(nóng)業(yè)新技術(shù)的論文

農(nóng)作物秸稈的綜合開發(fā)利用
摘要:農(nóng)作物秸稈是農(nóng)業(yè)生產(chǎn)的主要副產(chǎn)品,也是工農(nóng)業(yè)生產(chǎn)的重要資源。本文介紹了農(nóng)作物秸稈綜合利用概況,論述
了當(dāng)前農(nóng)作物秸稈綜合利用的技術(shù)方法,提出了農(nóng)作物秸稈未來綜合開發(fā)利用的基本途徑。
關(guān)鍵詞:農(nóng)作物秸稈;綜合開發(fā);利用;基本途徑

近幾年來,為實(shí)現(xiàn)農(nóng)作物秸稈的綜合利用,全國各
地大力推廣聯(lián)合收獲、秸稈還田、青貯氨化、秸稈加工顆
粒飼料、秸稈養(yǎng)殖蚯蚓等秸稈加工利用技術(shù),取得了較
好的效果。特別是通過實(shí)施秸稈還田與禁止焚燒,開展
綜合利用,秸稈綜合利用水平有所提高。但是,目前真正
綜合開發(fā)利用技術(shù)不多,大部分農(nóng)作物秸稈(全國約有
5億t)尚未得到合理利用,僅靠單一技術(shù)和小規(guī)模生產(chǎn)
加工方式,不能把秸稈全部充分利用起來,經(jīng)濟(jì)效益和
社會效益都很低,秸稈綜合利用仍有很大的發(fā)展空間[1]。
1農(nóng)作物秸稈加工利用技術(shù)
1.1秸稈飼料化技術(shù)
農(nóng)作物秸稈雖然所含營養(yǎng)成分低,粗纖維含量高
(31%~45%),蛋白質(zhì)含量少(3%~6%),但是,經(jīng)過
適當(dāng)?shù)募庸ぬ幚?補(bǔ)充適量的粗飼料和其他必須營養(yǎng)物
質(zhì),仍能滿足牲畜的各種營養(yǎng)需要。我國具有利用農(nóng)作
物秸稈飼養(yǎng)畜禽的傳統(tǒng),并由此培育出了具有高繁、耐
粗飼的諸多優(yōu)良畜禽品種,同時(shí)建立了一整套的秸稈飼
料化技術(shù)。因此,利用秸稈養(yǎng)殖,仍是發(fā)展畜牧業(yè)的一條
重要途徑[2]。
1.1.1物理處理技術(shù)方法利用人工、機(jī)械、熱、水和壓
力等作用,通過改變秸稈的物理性狀,使秸稈破碎、軟
化、降解,從而便于家畜咀嚼和消化的一種加工方法。實(shí)
踐證明,秸稈未經(jīng)切短,家畜只能采食40%~60%,而
經(jīng)過切短或粉碎后的秸稈,可以幾乎全部被家畜采食。
常用的處理方法主要有切斷與切碎處理、揉搓處理、軟
化處理、熱噴處理、膨化處理、顆粒處理及碾青處理等方
法。
1.1.2化學(xué)處理方法利用一些化學(xué)物質(zhì)來處理秸稈,
在打破秸稈營養(yǎng)物質(zhì)障礙的同時(shí),提高家畜對秸稈的利
用率。實(shí)驗(yàn)結(jié)果表明,秸稈氨化后可提高消化率約10%。
秸稈氨-堿復(fù)合處理后,麥秸的消化率可提高到66.5%,
稻草的消化率提高到71%。同時(shí),動(dòng)物的采食量大幅度
增加。常用的處理方法主要有堿化處理、氨化處理、酸化
處理、氧化劑處理、氨-堿復(fù)合處理和堿-酸復(fù)合處理等
方法。
1.1.3生物處理方法利用有益的微生物(如乳酸菌、
酵母菌)和酶等,在適宜的條件下,分解秸稈中難以被家
畜消化的纖維素和木質(zhì)素的一種方法。據(jù)實(shí)驗(yàn)測定,麥
秸微貯處理后,干物質(zhì)體內(nèi)消化率可提高24.14%,粗
纖維體內(nèi)消化率提高43.77%,有機(jī)物體內(nèi)消化率提高
29.4%。常用的處理方法主要有自然發(fā)酵法、微生物發(fā)
酵法、酶解技術(shù)等。
1.2秸稈養(yǎng)殖蚯蚓技術(shù)
將秸稈經(jīng)過粉碎堆制處理后,作為蚯蚓餌料飼養(yǎng)蚯
蚓。蚯蚓含有多種氨基酸和豐富的粗蛋白,不僅可用來
補(bǔ)充畜禽蛋白質(zhì)飼料的不足,還可入藥。實(shí)踐證明,25~
30 kg秸稈餌料可以生產(chǎn)1 kg鮮蚯蚓,并可獲得70%
蚯蚓糞。蚯蚓糞又是很好的有機(jī)肥料,含有很高的有機(jī)
質(zhì)、腐植酸、氮、磷、鉀,并含多種微量元素和氮基酸,是
植物生長最需要的養(yǎng)料[3～4]。
1.3秸稈作為基料生產(chǎn)食用菌技術(shù)
利用農(nóng)作物秸稈作為基料栽培食用菌,不僅來源豐
富,價(jià)格低廉,而且,可以緩解諸如棉籽殼等其他基料日
漸緊缺且價(jià)高而影響食用菌生產(chǎn)的問題,大大增加了食
用菌生產(chǎn)原料的來源。同時(shí),生產(chǎn)菌菇后的菌糠是一種
富含營養(yǎng)的菌體蛋白飼料,既能作為飼料過腹還田,也
可作為優(yōu)質(zhì)的有機(jī)肥直接還田。
1.4秸稈還田技術(shù)
農(nóng)作物秸稈中含有大量的有機(jī)質(zhì)、氮、磷、鉀、鎂、硫
和微量元素,將其通過機(jī)械或生物性處理后直接還田,
能夠有效改良土壤,提高地力,降低生產(chǎn)成本,提高農(nóng)產(chǎn)
品的產(chǎn)量和質(zhì)量。這項(xiàng)技術(shù)主要包括秸稈粉碎還田、根
茬粉碎還田、整稈翻埋還田、整稈壓扁還田和堆漚還田
等形式。
1.5其他

1.5.1秸稈能源化利用技術(shù)農(nóng)作物秸稈纖維中的碳
約占40%以上(如小麥、玉米等),是很好的能源物質(zhì)。
該項(xiàng)技術(shù)主要有秸稈的生物質(zhì)氣化技術(shù)、秸稈焚燒發(fā)電
技術(shù)和燃料乙醇生產(chǎn)技術(shù)等。另外,還利用秸稈原料經(jīng)
烘干或曬干、粉碎,隔絕空氣下加熱得到固體木炭,加工
成多種型炭。
1.5.2秸稈工業(yè)化利用技術(shù)農(nóng)作物秸稈是一種工業(yè)
制品的原料,除了作造紙?jiān)贤?還可以秸稈中的纖維
作為原料加工纖維密度板、植物地膜等產(chǎn)品;以秸稈為
原料制造餐具、包裝材料;利用秸稈中的纖維和木質(zhì)作
為填充材料,以水泥、樹脂為基料壓制成各種類型的纖
維板、輕體隔熱墻板等產(chǎn)品[4～5]。

文秘雜燴網(wǎng)

標(biāo)簽： 農(nóng)業(yè)機(jī)械論文

現(xiàn)代農(nóng)業(yè)智能改造傳統(tǒng)農(nóng)業(yè)的14種方式【中英雙語】 ♂

現(xiàn)代農(nóng)業(yè)智能改造傳統(tǒng)農(nóng)業(yè)的14種方式【中英雙語】

隨著我們進(jìn)入機(jī)器學(xué)習(xí)的新技術(shù)時(shí)代，人工智能和農(nóng)業(yè)正變得如膠似漆。它帶來了令人興奮的無限可能性：從種子發(fā)芽，到保持作物的完整性，再到實(shí)際的收獲過程?？茖W(xué)家估計(jì)到2050年，全球人口將增加到97億人以上，那時(shí)很多饑餓的人口需要養(yǎng)活。相比于人口的大量增長，耕地面積只會增加4%。因此，解決辦法不是擴(kuò)大農(nóng)田來種植莊稼和飼養(yǎng)牲畜，而是更有效地利用現(xiàn)有的土地。回顧過去，我們看到大約70年前“綠色革命”的開始，它帶來了灌溉系統(tǒng)的改善，農(nóng)田機(jī)械化的方法，以及新型的人造肥料。這些因素的疊加起來提高了糧食產(chǎn)量，全球約有10億人因此從饑餓中獲救。這種快速發(fā)展帶來了許多好處，如更高的產(chǎn)量，但也有許多負(fù)面因素：種植業(yè)大量使用殺蟲劑、化肥等激素，破壞了生物多樣性，一些不可或缺的生物滅絕。同時(shí)，那些耕作方法加在一起，向地球上的小溪和河流注入了大量的毒素，也耗盡了土壤的自然肥力。

As we enter the new technology era of machine learning, artificial intelligence and agriculture are becoming closely intertwined. It brings exciting infinite possibilities: from seed germination, to maintaining the integrity of the crop, to the actual harvesting process. Scientists estimate that the global population will grow to more than 9.7 billion people by 2050, when many hungry people will need to be fed. Compared to the massive population growth, the arable land area will only increase by 4 percent. Therefore, the solution is not to expand farmland to grow crops and raise livestock, but to moreeffectively use the existing land. Looking back, we see the start of the "Green Revolution" about 70 years ago, which brought improvements to irrigation systems, methods of mechanized farmland, and new types of man-made fertilizers. The combination of these factors has increased food production, and about a billion people worldwide have been saved from hunger. This rapid development has brought many benefits, such as higher yields, but there are also many negative factors: the heavy use of pesticides,fertilizers and other hormones, destroying biodiversity, and some indispensable biological extinction. At the same time, those farming methods put together inject large amounts of toxins into the earth's streams and rivers, as well as draining the soil's natural fertility.

可持續(xù)農(nóng)業(yè)和糧食問題專家Danielle Nierenberg說：“這些方法從來沒打算長期使用?！比绻覀円^續(xù)保持糧食生產(chǎn)的穩(wěn)定和充足，就必須進(jìn)行變革。目前，全球20%的人口受雇于農(nóng)業(yè)綜合企業(yè)，這是一個(gè)價(jià)值3萬億美元的產(chǎn)業(yè)。但是我們?nèi)绾芜M(jìn)行這個(gè)變換呢？答案可以在人工智能和農(nóng)業(yè)的融合發(fā)展中找到。新型的機(jī)器學(xué)習(xí)技術(shù)在農(nóng)業(yè)各個(gè)解決方案中是如何推動(dòng)生產(chǎn)的？人工智的大量應(yīng)用，改善了發(fā)展中國家和已經(jīng)領(lǐng)先的西方國家的農(nóng)業(yè)狀況：

food production, we must change. Currently, 20% of the world's population is employed in an agribusiness, a $3 trillion industry. But how do we make this transformation? The answer can be found in the integrated development of artificial intelligence and agriculture. How do new machine-learning technologies drive production across agricultural solutions? The extensive application of artificial intelligence has improved the agricultural situation in developing countries and already leading Western countries:

1、人工智能選種

如果我們想要有最好的作物，那么這一切都取決于我們種植的種子的基因。Monsanto公司現(xiàn)在正在使用人工智能掃描具有最理想特性的種子的DNA序列。農(nóng)民將不再需要投入時(shí)間和精力來進(jìn)行種子的交叉變異實(shí)驗(yàn)，因?yàn)楝F(xiàn)在有計(jì)算機(jī)程序可以為他們進(jìn)行這種分析。種子本身有發(fā)芽率，或“種子休眠”，這意味著它們只有在特定條件下才會發(fā)芽和開始生長。研究人員可以利用人工智能找出種子發(fā)芽的最佳條件，如溫度和濕度水平，使作物能夠比預(yù)期的更早開始生長。這減少了等待時(shí)間，并可以使作物全年種植。機(jī)器學(xué)習(xí)支持的圖像分析的新應(yīng)用，加上移動(dòng)成像的自動(dòng)化控制，可以測試種子的表型，以確定使用哪種種子最好。這方面的實(shí)例可以在種子發(fā)芽技術(shù)中找到，該技術(shù)已經(jīng)用于測試番茄和玉米等作物。

1、Artificial intelligence for species selection

If we want to have the best crops, then it all depends on the genes of the seeds we grow. Monsanto Company is now using AI to scan the DNA sequences of seeds with the most desirable features. Farmers will no longer need to devote time and effort to cross-variation experiments on seeds, as there are now computer programs available to perform this analysis for them. The seeds themselves have a germination rate, or "seed dormancy," which means that they only germinate and start to grow under certain conditions. Researchers can use AI to find out the best conditions for seed germination, such as

2、通過人工智能反饋進(jìn)行土壤管理

在世界各地種植農(nóng)作物時(shí)，土壤營養(yǎng)也會發(fā)揮作用。通過特殊的算法，深度學(xué)習(xí)被帶到這里的最前沿，這些算法可以幫助監(jiān)測種植前和生長過程中土壤的健康狀況。

土壤退化和侵蝕也是影響農(nóng)作物生長的重要因素，但這兩個(gè)問題都可以用人工智能解決，就像PEAT公司在德國做過的實(shí)驗(yàn)?zāi)菢?。他們開發(fā)了一種能分析土壤缺陷的Plantix。加上無人機(jī)的視覺感知能力，它們可以探測到作物的生長區(qū)域，這些作物可能生長在有缺陷的土壤中，或會遭受區(qū)域里疾病和害蟲的侵襲。

它通過對葉子成像，然后通過一個(gè)軟件運(yùn)行，這個(gè)軟件可以區(qū)分正常和不健康的生長模式。更重要的是，軟件會向農(nóng)民提出解決問題的方法。

CropDiagnosis是另一個(gè)類似的應(yīng)用程序，它可以用無人機(jī)掃描整個(gè)領(lǐng)域，并且評估土壤中灌溉和氮含量水平。

在美國，Trace Genomics也在追隨他們的腳步，采用基于人工智能的技術(shù)來研究土壤弱點(diǎn)和作物缺陷。

2、Soil management through artificial intelligence feedback

Soil nutrition also plays a role when growing crops around the world. Deep learning is being brought here to the forefront of special algorithms that can help monitor the health of the soil before planting and during growth.

Soil degradation and erosion are also important factors affecting crop growth, but both problems can be solved with artificial intelligence, as PEAT did in Germany. They developed a Plantix that analyzes soil defects. Combined with the visual perception of drones, they can detect the growing areas of crops that may grow in defective soil or suffer fromdisease and pests in the areas.

It is run by imaging the leaves and then through a software that distinguishes between normal and unhealthy growth patterns. More importantly, the software presents farmers with solutions to the problem.

CropDiagnosis is another similar application that can scan entire fields with drones and assess irrigation and nitrogen levels in soil. In the US, Trace Genomics is also following in their footsteps, using AI-based technologies to study soil weaknesses and crop defects.

3、人工智能管理灌溉和用水

植物要想正常生長，就需要持續(xù)不斷的供給需要的水。在世界上雨水和淡水稀少或不可靠的地區(qū)，種植作物尤其困難。就像你的花園灑水器可以設(shè)置定時(shí)器一樣，現(xiàn)代的人工智能灌溉方法比這更進(jìn)一步。

他們可以通過農(nóng)業(yè)環(huán)境中的機(jī)器學(xué)習(xí)技術(shù)實(shí)時(shí)跟蹤土壤中的水分含量，從而準(zhǔn)確地知道何時(shí)向作物提供水，以及如何合理節(jié)約水的消耗。這意味著農(nóng)民有更多時(shí)間來做其他的重要工作，而不必費(fèi)心親自灌溉作物。

據(jù)估計(jì)，地球上約70%的淡水供應(yīng)用于農(nóng)業(yè)生產(chǎn)，因此更有效地管理淡水供應(yīng)將對如何利用這一寶貴資源產(chǎn)生連鎖反應(yīng)。

3. Artificial intelligence manages irrigation and water use

For plants to grow normally, they need a constant supply of water. Growing crops is particularly difficult in areas of the world where rainwater and fresh water are scarce or unreliable. Just as your garden sprinkler can set a timer, modern AI irrigation approaches go further than that.

They can track the water content in the soil in real time through machine learning technology in agricultural environments, thus knowing exactly when to provide water to the crops and how to rationally save water consumption. This means that farmers have more time to do other important work without having to bother to irrigate the crops themselves.

It is estimated that about 70% of the planet's freshwater supply is used for agricultural production, so more efficient management of the freshwater supply will have a knock-on effect on how this valuable resource is utilized.

4、基于圖像的養(yǎng)分和肥料使用解決方案

土壤本身并不總是為作物提供最好的營養(yǎng)，農(nóng)民必須定期輪作。在過去，肥料是植物的主要肥料，但農(nóng)業(yè)現(xiàn)代化帶來了大量新的和創(chuàng)新的施肥方案。

農(nóng)民花大量時(shí)間在地里以氮肥的形式為作物提供必要的營養(yǎng)，然而人工智能現(xiàn)在已經(jīng)成為這個(gè)領(lǐng)域的主要參與者。

現(xiàn)代人工智能解決方案不僅可以檢測出需要多少肥料才能減少浪費(fèi)，而且還有可用的硬件來輔助運(yùn)輸過程。其中一個(gè)解決方案就是Rowbot。

這是一臺基于圖像的機(jī)器，它在作物生長期間收集植物數(shù)據(jù)，只向最需要化肥的作物提供肥料，從而提高原本收成較低的作物的產(chǎn)量。

由Bosch開發(fā)的Plantect是另一個(gè)智能的人工智能套件，它可以幫助農(nóng)場從確定正確的陽光和濕度水平到無縫監(jiān)控一切，并與物聯(lián)網(wǎng)協(xié)同工作。

4. Image-based nutrient and fertilizer use solutions

The soil itself does not always provide the best nutrition for the crops, and farmers must regularly rotate them. In the past, fertilizers were the main fertilizers for plants, but agricultural modernization has brought a host of new and innovative fertilization schemes. Farmers spend a lot of time in the fields providing the necessary nutrients for their crops in the form of nitrogen fertilizer, yet AI has now become a major player in the field. Modern AI solutions can not only detect how much fertilizer is needed to reduce waste, but also have the hardware available to assist the shipping process. One of the solutions is theRowbot. It is an image-based machine that collects plant data during crop growth and provides fertilizer only to the crops that need fertilizer most, thereby increasing the yields of crops that originally have lower harvests. Developed by Bosch, Plantect is another intelligent AI suite that can help farms move from determining the right sunlight and humidity levels to seamlessly monitoring everything, and working in concert with the Internet of Things.

5、人工智能可以預(yù)測天氣狀況

從潮濕的英格蘭到太陽炙烤下的加利福尼亞，再到干旱肆虐的索馬里，天氣狀況極大地影響了農(nóng)作物的生長。

一季不下雨意味著成千上萬的人在幾個(gè)月內(nèi)都會挨餓。然而，人工智能現(xiàn)在可以與機(jī)器學(xué)習(xí)相關(guān)的特殊算法結(jié)合使用——再加上衛(wèi)星信息——以確保無論天氣如何，農(nóng)作物都不會歉收。

美國一家名為aWhere的公司正在利用這種人工智能技術(shù)來預(yù)測天氣模式，使農(nóng)民能夠提前采取正確的措施。

它能測量一切：從太陽輻射到降水、溫度推測和風(fēng)速，以提供有關(guān)潛在作物生長和產(chǎn)量的準(zhǔn)確數(shù)據(jù)。

例如，如果你知道兩天后會有大量降雨，就不需要用昂貴的灌溉用水。或者，如果你知道接下來的幾天會帶來高溫，那么你可以確保作物在早晨早些時(shí)候澆水，為溫度上升做好準(zhǔn)備，減少土壤蒸發(fā)。

這兩者都可以被編程到AI機(jī)器解決方案中，當(dāng)軟件和硬件結(jié)合在一起時(shí)，農(nóng)業(yè)技術(shù)可以提前為農(nóng)戶采取行動(dòng)。

5. Artificial intelligence can predict weather conditions

From wet England to sun-setting California to arid Somalia, weather conditions have greatly affected crops. A season of no rain means that thousands of people will starve within a few months. However, AI can now use —— in combination with special algorithms related to machine learning plus satellite information —— to ensure that crops don't fail regardless of the weather. A US company called aWhere is using this artificial intelligence technology to predict weather patterns and allow farmers to take the right steps ahead of time. It measures everything: fromsolar radiation to precipitation, temperature speculation, and wind speed to provide accurate data on potential crop growth and yield. For example, if you know that there will be a lot of rain after two days, no expensive irrigation water is needed. Or, if you know that the next few days will bring high heat, then you can make sure that the crops are watered early in the morning in preparation for a temperature rise and reduce soil evaporation. Both can be programmed into AI machine solutions, and when software and hardware are combined, agricultural technology cantake action for farmers ahead.

6、創(chuàng)新的機(jī)器視覺來識別作物問題

一旦作物生長，就有必要保護(hù)它們的生長不受疾病和蟲害的侵蝕。在這方面，人工智能也可以提供幫助。

你不僅可以在人工智能控制機(jī)器和條件的溫室里種植作物，而且戶外作物也可以從技術(shù)投入中受益。

跨國農(nóng)業(yè)企業(yè)John Deere現(xiàn)在收購了Blue River Technology，作為其人工智能武器庫的一部分。他們共同開發(fā)了一種“看和噴”的方法，利用人工智能機(jī)器學(xué)習(xí)和計(jì)算機(jī)視覺相結(jié)合，找出影響作物生長的雜草，然后將它們清除。

該公司發(fā)言人John May表示：“機(jī)器學(xué)習(xí)是Deere未來的一項(xiàng)重要能力，并且它認(rèn)識到技術(shù)對我們客戶的重要性?！?/span>

“看和噴”方法意味著，他們現(xiàn)在可以針對特定的雜草，提高作物產(chǎn)量，而不是以高昂的成本噴灑整株作物，而且還會伴隨著對的健康影響。

6. Innovative machine vision to identify crop problems

Once crops are grown, it is necessary to protect their growth from disease and insect pests. In this regard, AI can also help. Not only can you grow crops in a greenhouse where AI controls machines and conditions, but outdoor crops can also benefit from technology inputs. Multinational agribusiness John Deere has now acquired Blue River Technology as part of its AI arsenal. Together, they developed a "see and spray" method, using a combination of artificial intelligence machine learning and computer vision to identify weeds that affect crops andthen remove them. Company spokesman John May said: " Machine learning is an important capability of Deere in the future, and it recognizes the importance of technology to our customers.” The see and spray approach means that they can now target specific weeds and increase crop yields, rather than spraying whole crops at a high cost, along with their health effects.

7、用人工智能技術(shù)監(jiān)測雜草和害蟲問題

人工智能傳感器也正在開發(fā)中，利用圖像傳感技術(shù)來檢測植物葉片的病害特征。這與通過人工智能機(jī)器進(jìn)行的彩色成像有關(guān)。人工智能機(jī)器能夠區(qū)分健康和患病的葉子，然后通過與機(jī)器人集成來去除它們。

微軟開發(fā)人員也在使用同樣的技術(shù)，他們合作開發(fā)了一個(gè)害蟲預(yù)測界面，可以識別破壞農(nóng)作物的昆蟲。在很短的時(shí)間內(nèi)，這將包括診斷和消滅害蟲的實(shí)際遠(yuǎn)程機(jī)器視覺。

這項(xiàng)技術(shù)最多可以減少80%的化學(xué)物質(zhì)的使用，而花在除草劑上的錢會減少90%。

雜草控制對農(nóng)民來說非常重要，因?yàn)槟壳凹s有250個(gè)品種對現(xiàn)代除草劑具有抗藥性，僅大豆和玉米作物上的雜草生長每年就造成400多億美元的損失。

7. Using artificial intelligence technology to monitor weeds and pests

AI sensors are also being developed to use image-sensing techniques to detect disease characteristics in plant leaves. This is related to color imaging via an AI machine. AI machines are able to distinguish healthy from diseased leaves and then remove them by integrating with the robot. Microsoft developers, who have collaborated to develop a pest prediction interface that identifies insects that damage crops. In a short time this will include diagnosis and elimination of pests by actual remote machine vision. The technology could reduce the use of chemicals by up to80%, and reduce the money spent on herbicides by 90%. Weed control is very important for farmers because about 250 varieties are currently resistant to modern herbicides, and weeds growing on soybean and corn crops alone cost more than $40 billion a year.

8、預(yù)測正確的收獲時(shí)間

幾個(gè)世紀(jì)以來，農(nóng)民們一直在考慮天氣狀況和作物的總體狀況等因素，決定最佳收割時(shí)間

由于成像技術(shù)反饋給遠(yuǎn)程學(xué)習(xí)軟件，人工智能現(xiàn)在帶來了一個(gè)決定作物是否可以采摘的新元素。

該技術(shù)可以用白色和UVA型燈分析水果的成熟度，這意味著農(nóng)民可以選擇只采摘最成熟的水果或蔬菜，而把其他未成熟的水果留一段時(shí)間。

這可以在溫室里小規(guī)模地進(jìn)行，也可以在更大的規(guī)模上進(jìn)行，使用直升機(jī)和無人機(jī)可以構(gòu)建一個(gè)整體的田間管理地圖。

8. Predict the right harvest time

For centuries, farmers have considered the weather conditions and the overall state of their crops to determine the best harvest time With imaging feeds back to remote learning software, AI now brings a new element to determine whether crops can be picked. The technique can analyze the maturity of fruit with white and UVA lamps, meaning that farmers can choose to pick only the most mature fruits or vegetables while leaving the other immature fruits for a period of time. This can be done on a small scale in a greenhouse or on a larger scale, using helicopters anddrones to build a holistic map of field management.

9、機(jī)械收割方法

現(xiàn)在讓我們看看食物是如何挑選的。越來越多的農(nóng)場工人不愿意日復(fù)一日地做重復(fù)性的、季節(jié)性的采摘水果和蔬菜的工作，預(yù)計(jì)在2014年至2024年間，這一比例將降至6%。

我們面臨著這樣的事實(shí)上：由于工人短缺，熟透的水果往往無法采摘，這意味著利潤的損失。

根據(jù)農(nóng)業(yè)綜合企業(yè)的性質(zhì)，一個(gè)農(nóng)場大約40%的利潤用于體力勞動(dòng)和工資。

人工智能可以大幅減少這一數(shù)字，因?yàn)橐坏┵徺I了機(jī)器，它們就會隨著時(shí)間的推移為自己買單。

有兩個(gè)機(jī)器收割的例子來自Harvest CROO Robotics，它創(chuàng)造了采摘成熟草莓的硬件，以及擁有可以收割蘋果園的機(jī)器的豐富技術(shù)。這種類型的人工智能將感知和動(dòng)作結(jié)合在一起，因此自主機(jī)器可以看到需要收獲什么，然后繼續(xù)執(zhí)行收獲的動(dòng)作。

9. Mechanical harvesting methods

Now let's see how the food is chosen. The growing reluctance of farm workers to do repetitive, seasonal work of fruit and vegetables is expected to fall to 6% between 2014 and 2024. We face the fact that because of a shortage of workers, ripe fruit is often not picked, which means a loss of profits. Depending on the nature of the agribusiness, about 40% of the profits of a farm go to manual labor and wages. AI can dramatically reduce that number, because once they buy machines, they pay for themselves over time. There are two examples of machine harvesting from Harvest CROO Robotics, which createsthe hardware for picking ripe strawberries, and the rich technology of having machines that can harvest apple orchards. This type of AI combines perception and action, so that the autonomous machine can see what needs to be harvested, and then continue to perform the harvested action.

10、農(nóng)場機(jī)器接受人工智能升級

現(xiàn)代農(nóng)業(yè)往往使用各種各樣的機(jī)器來保持生產(chǎn)效率。

從拖拉機(jī)和收割機(jī)到四軸腳踏車和運(yùn)貨卡車，機(jī)器是農(nóng)業(yè)的重要組成部分，但是機(jī)器故障和持續(xù)的維護(hù)是一個(gè)嚴(yán)重但經(jīng)常被忽視的影響利潤的問題。像汽車這樣的普通道路交通工具，現(xiàn)在正在用一組非同尋常的電子產(chǎn)品進(jìn)行制造，從輪胎壓力到油位，這些電子產(chǎn)品可以提供各種反饋。

未來的農(nóng)業(yè)機(jī)械也將采用同樣先進(jìn)的監(jiān)測系統(tǒng)。與其等著拖拉機(jī)在田里拋錨，還不如提前警告農(nóng)民任何故障。與物聯(lián)網(wǎng)相結(jié)合，這些物品甚至可以在問題出現(xiàn)之前就預(yù)先提醒和維修。

10. Farm machines accept artificial intelligence upgrade

Modern agriculture often uses a wide variety of machines to maintain production efficiency. From tractors and harvesters to quad bicycles and cargo trucks, machines are an important part of agriculture, but machine failure and continuous maintenance is a serious but often overlooked problem affecting profits. Ordinary road vehicles like cars are now being manufactured with an unusual set of electronics that can provide a variety of feedback, from tire pressure to oil levels. Future agricultural machinery will also use the same advanced monitoring system. Instead of waiting for the tractor to break down in the field, just warn the farmers of any problems. Combined with the Internet of Things, these items can be alerted and repaired even before problems arise.

11、人工智能無人機(jī)的崛起

展望未來，無人機(jī)已經(jīng)在許多方面得到了應(yīng)用，要使現(xiàn)有的無人機(jī)適應(yīng)農(nóng)業(yè)生產(chǎn)，所需要的只是硬件和軟件的集成，這為這些飛行器提供了額外的用途。

像VineView所使用的智能攝像頭，可以在很遠(yuǎn)的地方為農(nóng)民提供反饋和信息——從作物生長受阻和缺水到土壤條件和病蟲害監(jiān)測。未來的農(nóng)民不再需要步行數(shù)英里穿過他們的莊稼和農(nóng)田來評估它的狀況——而是用無人機(jī)在幾分鐘內(nèi)飛去所關(guān)注的地區(qū)。

到2027年，農(nóng)業(yè)無人機(jī)的市場份額預(yù)計(jì)將接近5億。無人駕駛拖拉機(jī)也將成為現(xiàn)實(shí)，在沒有真人指導(dǎo)的情況下，通過編程使其以一定的速度行駛，同時(shí)以有效的方式執(zhí)行特定任務(wù)。

11. The rise of AI drones

Looking ahead, UAVs have been used in many ways, and all is needed to adapt existing UAVs to agricultural production is the integration of hardware and software, which provides additional uses for these vehicles. Smart cameras like those used by VineView can provide farmers with feedback and information —— from crop growth block and water shortage to soil conditions and pest monitoring. Future farmers will no longer need to walk miles through their crops and farmland to assess its condition —— but will use drones to fly to the areas of interest in minutes. By 2027, the market share of agricultural drones is expected to approach $500 million. Driverless tractors will also become a reality, being programmed to drive at a certain speed while performing specific tasks in an effective way。

12、來自數(shù)據(jù)庫的云共享信息可以幫助農(nóng)民

由于“Alexa”類型的系統(tǒng)為農(nóng)民的所有問題提供了解決方案，人工智能可以成為農(nóng)民最好的朋友。

建立農(nóng)業(yè)的知識數(shù)據(jù)庫，并能向其詢問從動(dòng)物疾病到土壤質(zhì)量的一切問題。這樣的基礎(chǔ)可以學(xué)習(xí)正確的解決方案和回答問題，然后可以有效地與業(yè)務(wù)中的其他人共享。

當(dāng)農(nóng)業(yè)在很大程度上實(shí)現(xiàn)自動(dòng)化時(shí)，數(shù)據(jù)共享無疑將具有重要性。訓(xùn)練系統(tǒng)需要數(shù)據(jù)，特別是人工智能算法的數(shù)據(jù)非常有價(jià)值。

近年來，農(nóng)業(yè)數(shù)據(jù)聯(lián)盟(Agricultural Data Coalition)已成立，旨在幫助農(nóng)民掌握信息和數(shù)據(jù)處理技術(shù)，以便從研究人員到農(nóng)場主、農(nóng)作物買家和保險(xiǎn)公司等所有人都能共同努力，提高產(chǎn)量，從而提高所有人的利潤。

得益于人工智能技術(shù)，總體產(chǎn)量得以提高，將人工智能應(yīng)用于農(nóng)業(yè)的最終目標(biāo)是提高每平方英尺的作物產(chǎn)量。

產(chǎn)量的提高主要是通過模仿人類認(rèn)知的算法實(shí)現(xiàn)的，在分析大數(shù)據(jù)時(shí)，將農(nóng)業(yè)中的機(jī)器學(xué)習(xí)技術(shù)帶到最前沿，并利用它做出有效的決策。這些數(shù)學(xué)人工智能公式可以通過決定作物從播種到收獲的最佳操作過程來幫助提高作物產(chǎn)量。

人工智能解決方案在農(nóng)業(yè)領(lǐng)域的技術(shù)有很多，而且具有幾乎無限的潛力。農(nóng)業(yè)傳感器可以看到外形，識別語音命令和操作視覺感知能力來收集所需的數(shù)據(jù)。

信息管理系統(tǒng)控制收集的數(shù)據(jù)，并允許人工智能軟件基于深度學(xué)習(xí)技術(shù)和機(jī)器學(xué)習(xí)通過預(yù)測分析做出決策。這些數(shù)據(jù)可以用于專門為農(nóng)業(yè)綜合企業(yè)制造的硬件，比如自動(dòng)無人機(jī)和自動(dòng)駕駛汽車。

充分利用收集到的數(shù)據(jù)，能為農(nóng)民提供最好的服務(wù)。農(nóng)業(yè)領(lǐng)域的人工智能解決方案要想在這一領(lǐng)域起飛，就需要在農(nóng)業(yè)實(shí)踐中集成人工智能的多方優(yōu)勢。

12. Cloud-sharing information from databases can help farmers

Because the "Alexa" -type systems provide solutions to all the farmers 'problems, AI can be the farmer's best friend. Establish a knowledge database of agriculture and ask them about everything from animal disease to soil quality. Such a foundation can learn the correct solutions and answer questions, which can then be effectively shared with others in the business. When agriculture is largely automated, data sharing will undoubtedly be important. Training systems require data, especially data for AI algorithms, which is very valuable. In recent years, the Agricultural Data Alliance (Agricultural Data Coalition)has been established to help farmers master information and data processing technology so that everyone from researchers to farmers, crop buyers and insurance companies can work together to increase production and thus increase profits for all. Thanks to AI technology, overall production has increased, and the ultimate goal of applying AI to agriculture is to increase crop production per square foot.

potential. Agricultural sensors can see the shape, recognize voice commands and manipulate the visual perception ability to collect the required data. The information management system controls the collected data and allows AI software to make decisions through predictive analysis based on deep learning techniques and machine learning. The data can be used for hardware made specifically for agribusinesses, such as autonomous drones and self-driving vehicles. Make full use of the collected data to provide the best service for farmers. For AI solutions in agriculture to take off in thisarea, it requires integrating multiple advantages of AI in agricultural practice.

13、“農(nóng)業(yè) 4.0 ”指即將來臨的智能農(nóng)業(yè)

我國農(nóng)業(yè)科學(xué)家瞄準(zhǔn)“農(nóng)業(yè)4.0”，起步晚，但進(jìn)神速，是一種“彎道超車”模式?；ヂ?lián)網(wǎng)時(shí)代農(nóng)業(yè)通過網(wǎng)絡(luò)、信息等進(jìn)行資源軟整合， 在大數(shù)據(jù)、云計(jì)算、互聯(lián)網(wǎng)、傳感器的基礎(chǔ)之上形成智能農(nóng)業(yè)。 “農(nóng)業(yè) 4.0 ”是利用農(nóng)業(yè)標(biāo)準(zhǔn)化體系的系統(tǒng)方法對農(nóng)業(yè)生產(chǎn)進(jìn)行統(tǒng)一管理，所有過程均是可控、高效的。 農(nóng)業(yè)服務(wù)者與農(nóng)業(yè)生產(chǎn)者之間的信息通道通過農(nóng)業(yè)標(biāo)準(zhǔn)化平臺實(shí)現(xiàn)對等連接， 使整個(gè)過程中的互動(dòng)性更強(qiáng)。

13. Agriculture 4.0, which refers to the upcoming smart agriculture

Chinese agricultural scientists aim at "agriculture 4.0", started late, but into the speed, is a "curve overtaking" mode. In the Internet era, agriculture soft integrates resources through network and information, forming intelligent agriculture on the basis of big data, cloud computing, Internet and sensors."Agriculture 4.0" is the system method of agricultural standardization system to conduct unified management of agricultural production, and all the processes are controllable and efficient. The information channel between agricultural service providers and agricultural producers is peer-to-peer connectedthrough the agricultural standardization platform, making the interaction in the whole process stronger.

14、發(fā)展智慧農(nóng)業(yè)的社會需求

伴隨著我國工業(yè)化和城市化發(fā)展， 農(nóng)業(yè)人口出現(xiàn)下降是一個(gè)必然的趨勢。對于其他產(chǎn)業(yè)而言，從事農(nóng)業(yè)勞動(dòng)的收益相對較少，年輕人普遍不愿意繼承，導(dǎo)致農(nóng)業(yè)生產(chǎn)呈現(xiàn)出“ 后繼無人”的窘境。
如果不改變農(nóng)業(yè)生產(chǎn)的傳統(tǒng)形象，那么很難吸引年輕勞動(dòng)力向農(nóng)業(yè)部門轉(zhuǎn)移。
提高農(nóng)業(yè)競爭力，就需要順應(yīng)現(xiàn)代科技發(fā)展潮流，把大數(shù)據(jù)、機(jī)器人和人工智能等先進(jìn)技術(shù)引入農(nóng)業(yè)生產(chǎn)過程，改造傳統(tǒng)的農(nóng)業(yè)發(fā)展形態(tài)，實(shí)現(xiàn)從經(jīng)驗(yàn)種田到智慧種田的轉(zhuǎn)變。推動(dòng)發(fā)展智慧農(nóng)業(yè)，推動(dòng)農(nóng)業(yè)向信息化、智能化方向發(fā)展。
農(nóng)業(yè)物聯(lián)網(wǎng)的推廣不僅可以大幅減輕農(nóng)業(yè)勞作的壓力（農(nóng)戶應(yīng)用信息技術(shù)來解決農(nóng)業(yè)生產(chǎn)中的播種、控制、質(zhì)量安全以及成本削減等問題），提升農(nóng)業(yè)對青年人和女性勞動(dòng)者的吸引力，解決農(nóng)業(yè)生產(chǎn)勞動(dòng)力短缺的問題，而且大大提升了農(nóng)業(yè)的生產(chǎn)能力和效率，有助于促進(jìn)各地生產(chǎn)出高附加值和高品質(zhì)的農(nóng)產(chǎn)品，獲得了很好的經(jīng)濟(jì)效益和生態(tài)效益，增強(qiáng)農(nóng)業(yè)的魅力和國際競爭力。

14. The social need of developing smart agriculture

With the development of China's industrialization and urbanization, the decline of agricultural population is an inevitable trend. For other industries, the benefits of agricultural labor are relatively small, and young people are generally unwilling to inherit it, leading to the dilemma of "no successor" in agricultural production. Without changing the traditional image of agricultural production, it will be difficult to attract younger workers to the agricultural sector. To improve agricultural competitiveness, it is necessary to follow the trend of modern science andtechnology development, introduce advanced technologies such as big data, robots and artificial intelligence into the agricultural production process, transform the traditional form of agricultural development, and realize the transformation from experienced farming to intelligent farming. We will promote the development of smart agriculture and promote the development of agriculture toward information application and intelligence.

agricultural work (farmers apply information technology to solve the planting, control, quality safety and cost reduction), improve the agricultural attractive for young people and female workers, solve the problem of agricultural labor shortage, and greatly improve the agricultural production capacity and efficiency, help to promote around produce high value-added and high quality agricultural products, obtained a good economic and ecological benefits, enhance the charm of agriculture and international competitiveness.

現(xiàn)代農(nóng)業(yè)智能轉(zhuǎn)型，新農(nóng)人引得回留得住 ♂

現(xiàn)代農(nóng)業(yè)智能轉(zhuǎn)型，新農(nóng)人引得回留得住

?　? ?我國農(nóng)業(yè)勞力占比由1991年的60%下降到2018年的26%，已經(jīng)低于世界平均值；疊加城市化進(jìn)程對周邊區(qū)域勞動(dòng)力的虹吸效應(yīng)，進(jìn)一步加劇了農(nóng)業(yè)用工成本高，甚至無人可用的局面。據(jù)國家發(fā)展和改革委員會的成本調(diào)查資料顯示，目前幾乎所有農(nóng)產(chǎn)品生產(chǎn)的人工成本占比超過 50%。如何吸引更多人回鄉(xiāng)，以及農(nóng)業(yè)生產(chǎn)方式如何現(xiàn)代化轉(zhuǎn)型成為我國農(nóng)業(yè)面臨的主要問題。

　　從人口紅利轉(zhuǎn)向技術(shù)紅利、人才紅利，已成為中國農(nóng)業(yè)可持續(xù)發(fā)展的要義。為此，國家從頂層架構(gòu)到具體執(zhí)行不斷推進(jìn)“智慧農(nóng)業(yè)”發(fā)展，吸引越來越多企業(yè)投入其中，進(jìn)行技術(shù)創(chuàng)新、產(chǎn)品研發(fā)、生產(chǎn)智造，不斷描繪清晰智慧農(nóng)業(yè)的發(fā)展脈絡(luò)。深耕農(nóng)業(yè)8年的極飛科技，近期對外亮相了一系列新款農(nóng)業(yè)科技產(chǎn)品，并介紹了全新的服務(wù)體系，為外界探究智慧農(nóng)業(yè)的發(fā)展進(jìn)程提供一個(gè)可追蹤的企業(yè)樣本。

　　現(xiàn)代化農(nóng)業(yè)轉(zhuǎn)型：解決農(nóng)業(yè)苦、成本高的問題

　　“在智能農(nóng)機(jī)的幫助下，不需要親身下田做各種繁重作業(yè)，相比城市的工作更自由?！?0后新農(nóng)人梁亨達(dá)是廣州增城的種糧大戶，千畝農(nóng)田一人管?！耙郧坝萌斯と龇剩话佼€田需要2-3個(gè)人工作 2 天才能完成，人工成本需要 1000 多塊，農(nóng)業(yè)無人機(jī)幾起幾落就將原本需要忙碌一天的任務(wù)輕松搞定，提高了效率，也減少了成本?！被貞浧饛膰筠o職進(jìn)入農(nóng)業(yè)的過往，梁亨達(dá)分享了具體而鮮活的細(xì)節(jié)，三年前，他是在見到極飛農(nóng)業(yè)無人機(jī)對遭受稻飛虱蟲害的農(nóng)田進(jìn)行打藥的“高科技種地”場景后，入坑農(nóng)業(yè)并扎根其中。

　　在田間地頭，已經(jīng)出現(xiàn)越來越多年輕人忙碌的身影，走出農(nóng)村又回歸農(nóng)業(yè)的“當(dāng)代花木蘭”吳董淑；憑借多年經(jīng)驗(yàn)和技術(shù)優(yōu)勢，組織 200 多架農(nóng)業(yè)無人機(jī)參與當(dāng)?shù)匦←溄y(tǒng)防統(tǒng)治的閆文炯；將自家農(nóng)資店的生意嵌入到農(nóng)業(yè)無人機(jī)飛防服務(wù)產(chǎn)業(yè)鏈的楊秀世......細(xì)看推動(dòng)他們回到農(nóng)業(yè)并踏出新路子的同類項(xiàng)，都離不開先進(jìn)的智能農(nóng)機(jī)設(shè)備——農(nóng)業(yè)無人機(jī)。

　　農(nóng)業(yè)無人機(jī)在新農(nóng)人中備受關(guān)注，也推動(dòng)相關(guān)企業(yè)不斷迭代升級更好用的產(chǎn)品和技術(shù)。極飛科技今年發(fā)布會帶來了諸多小驚喜，如采用全新的技術(shù)理念把飛行平臺和作業(yè)系統(tǒng)完全分離，讓新農(nóng)人可以快速的在植保、播撒、測繪間靈活的切換，提高維修和運(yùn)輸效率。新推出的極飛 2022款P100農(nóng)業(yè)無人機(jī)在藥箱容量、作業(yè)效率上都進(jìn)行了提升，特別是在電力系統(tǒng)上，農(nóng)戶不再需要反復(fù)充電耽誤農(nóng)時(shí)。種種細(xì)節(jié)的改進(jìn)，都是為了解決梁亨達(dá)等千畝種糧大戶在農(nóng)忙時(shí)節(jié)所遇到的痛點(diǎn)。

　　智慧農(nóng)業(yè)實(shí)踐范本：農(nóng)業(yè)現(xiàn)代化的一小步

　　隨著越來越多的人和企業(yè)進(jìn)入農(nóng)業(yè)，農(nóng)業(yè)潛藏著的巨大市場需求和空間也不斷被看到。據(jù)前瞻產(chǎn)業(yè)研究院報(bào)告數(shù)據(jù)，2019年我國智慧農(nóng)業(yè)的市場規(guī)模約為622億元，預(yù)計(jì)到2025年中國農(nóng)業(yè)數(shù)字經(jīng)濟(jì)規(guī)模將達(dá)到1.26萬億元。

　　農(nóng)業(yè)天然的慢周期屬性，需要身處其中的從業(yè)者、企業(yè)拿出足夠的耐心和決心，才能做出些許成績。極飛科技通過多年的技術(shù)和產(chǎn)品積累，完成了6大產(chǎn)品線的布局；同時(shí)也在探索無人農(nóng)業(yè)的可能性，向智慧農(nóng)業(yè)踏出自己的一小步。今年年初，極飛科技“超級棉田”項(xiàng)目首次實(shí)踐全程無人化智能管理，借助氣象站、攝像頭、土壤傳感器等數(shù)字基礎(chǔ)設(shè)施，以及人工智能高科技手段實(shí)現(xiàn)管理3000畝高標(biāo)準(zhǔn)棉田，實(shí)現(xiàn)畝產(chǎn)254公斤?！俺壝尢铩表?xiàng)目的探索實(shí)踐，得到了尉犁縣政府的認(rèn)可，并與極飛科技簽署戰(zhàn)略協(xié)議，共建棉花現(xiàn)代產(chǎn)業(yè)園，大力推廣超級棉田無人化管理模式。

　　好的技術(shù)和產(chǎn)品，讓“農(nóng)業(yè)苦、成本高”不再成為阻礙年輕人回歸農(nóng)業(yè)的第一難；而無人化農(nóng)業(yè)的探索，則是在推動(dòng)農(nóng)業(yè)從傳統(tǒng)種植方式向現(xiàn)代化轉(zhuǎn)型的嘗試。

　　科技改變農(nóng)業(yè)，帶來不同于以往的農(nóng)業(yè)生產(chǎn)方式；當(dāng)然，也改變著農(nóng)業(yè)里的人?！昂诳萍肌薄ⅰ爸悄芑?、“新潮”這類代表著時(shí)尚、現(xiàn)代化的形容詞在以前并不會與農(nóng)業(yè)關(guān)聯(lián)起來，但如今卻成為現(xiàn)實(shí)。今天，返鄉(xiāng)創(chuàng)業(yè)的“新農(nóng)人”開始利用現(xiàn)代科技進(jìn)行農(nóng)業(yè)生產(chǎn)，不用親自下地，甚至在家打著撲克就能實(shí)現(xiàn)農(nóng)作物的管理。新的技術(shù)吸引新農(nóng)人回來，而新的農(nóng)業(yè)生產(chǎn)方式，將讓他們留在農(nóng)業(yè)，探索個(gè)人事業(yè)的新未來；他們，才是智慧農(nóng)業(yè)發(fā)展的主力軍。

現(xiàn)代農(nóng)業(yè)有哪些新思維、新技術(shù)、新玩法？ ♂

現(xiàn)代農(nóng)業(yè)有哪些新思維、新技術(shù)、新玩法？

農(nóng)業(yè)現(xiàn)代化進(jìn)程中，有哪些創(chuàng)新？

1、智慧農(nóng)業(yè)

智慧農(nóng)業(yè)，實(shí)際上是利用移動(dòng)互聯(lián)網(wǎng)，物聯(lián)網(wǎng)，大數(shù)據(jù)，云計(jì)算等技術(shù)和工具，把各個(gè)節(jié)點(diǎn)的數(shù)據(jù)匯集，整合，分析，并有效運(yùn)用。一句話，數(shù)據(jù)產(chǎn)生智慧，智慧驅(qū)動(dòng)農(nóng)業(yè)的生產(chǎn)，經(jīng)營，服務(wù)。

阿里研究院提出了端+網(wǎng)+云的范式，端，利用智能手機(jī)，無線芯片，傳感器等，把所有的物，人，信息連接起來;網(wǎng)，即移動(dòng)互聯(lián)網(wǎng)，和物聯(lián)網(wǎng)，作為中間層，把端的數(shù)據(jù)傳輸?shù)皆贫?；云，就是云?jì)算，分布式存儲和按需訪問。

2、資源節(jié)約型、環(huán)境友好型農(nóng)業(yè)

有機(jī)農(nóng)業(yè)、生態(tài)農(nóng)業(yè)、循環(huán)農(nóng)業(yè)等都可以歸到這個(gè)范疇里。農(nóng)業(yè)不能再是粗放式發(fā)展，對資源過度使用，對生態(tài)環(huán)境造成不可逆的傷害。兩型農(nóng)業(yè)強(qiáng)調(diào)技術(shù)賦能，用技術(shù)提高土地產(chǎn)出率、資源利用率、勞動(dòng)生產(chǎn)率。

3、分享農(nóng)業(yè)

這幾年分享經(jīng)濟(jì)大行其道，且誕生了一批酷公司，如滴滴，愛彼迎，摩拜等。雖不乏掛羊頭賣狗肉，但分享的概念漸入人心則是毋庸置疑。具體到農(nóng)業(yè)，真正踐行分享模式并不容易。

4、農(nóng)業(yè)產(chǎn)業(yè)化聯(lián)合體

最近，國家提出了農(nóng)業(yè)產(chǎn)業(yè)化聯(lián)合體的發(fā)展模式，希望新型農(nóng)業(yè)經(jīng)營主體能風(fēng)險(xiǎn)共擔(dān)，利益均沾，互信互惠，聯(lián)合發(fā)展。彼此結(jié)成聯(lián)合體，一榮俱榮一損俱損，而非零和競爭。也就是說，農(nóng)業(yè)發(fā)展要有包容性，普惠性，讓農(nóng)戶，中小型農(nóng)業(yè)經(jīng)營者能分享產(chǎn)業(yè)鏈增值收益。

5、農(nóng)匠精神

農(nóng)業(yè)加匠人精神，即農(nóng)匠精神。農(nóng)匠精神，要求農(nóng)業(yè)人能愛農(nóng)業(yè)，懂技術(shù)，善經(jīng)營，不忘初心方得始終。農(nóng)匠精神，召喚一批新農(nóng)人，篤定前行，不投機(jī)，精心打磨產(chǎn)品和服務(wù)，而不是用概念和樣板工程去忽悠消費(fèi)者，投資人，政府。

農(nóng)業(yè)是個(gè)傳統(tǒng)行業(yè)，但可以注入新思維，運(yùn)用新技術(shù)。

不過，技術(shù)為術(shù)，玩法為法，正道才是王道。道者，法自然，應(yīng)天時(shí)，借地力，合人性也。模式無常，天行有常，不為忽悠者存，不為實(shí)干家亡。

共勉。

標(biāo)簽： 農(nóng)業(yè)機(jī)械新技術(shù)大全