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Ọrụ ugbo ziri ezi

Ọrụ ugbo nke ọma (PA) bụ atụmatụ njikwa ọrụ ugbo dabere na ilele, tụọ na ịzaghachi na mgbanwe oge na oghere iji kwalite nkwado mmepụta ugbo.[2] A na-eji ya ma ihe ọkụkụ na anụ ụlọ.[3] Ọrụ ugbo nke ọma na-ejikarị teknụzụ arụ ọrụ arụ ọrụ ugbo, na-emezi nyocha ha, ime mkpebi ma ọ bụ ịrụ ọrụ.[4][5] Ebumnuche nke nyocha ọrụ ugbo nkenke bụ ịkọwapụta usoro nkwado mkpebi maka njikwa ọrụ ugbo dum na ebumnuche nke ịkwalite nlọghachi na ntinye mgbe ị na-echekwa akụrụngwa. [2][3]

Ihe oyiyi ndị na-acha adịgboroja na-egosi ngwa Mmetụta dịpụrụ adịpụ na ọrụ ugbo ziri ezi.[1]
Yara N-Sensor ALS nke a na-etinye n'elu okpokoro traktọ - usoro nke na-edekọ ihe ọkụkụ na-egbuke egbuke, na-agbakọ aro maka imeju ma na-agbanwe ọnụọgụ nke fatịlaịza gbasaa
Nkọwa Nkọwapụta NDVI 4 cm / pixel GSD

Otu n'ime ọtụtụ ụzọ ndị a bụ usoro phytogeomorphological nke jikọtara nkwụsi ike / njirimara nke mkpụrụ osisi ọtụtụ afọ na njiri mara mbara ala. Mmasị nke usoro phytogeomorphological sitere n'eziokwu ahụ bụ na akụkụ geomorphology na-akọwakarị hydrology nke ubi ugbo. [4][5]

Emeela ka omume ọrụ ugbo nke ọma site na ọbịbịa nke GPS na GNSS. Ikike onye ọrụ ugbo na/ma ọ bụ onye nchọcha nwere ịchọta kpọmkwem ọnọdụ ha n'ọhịa na-enye ohere ịmepụta maapụ nke mgbanwe mbara igwe nke ọtụtụ mgbanwe dị ka enwere ike tụọ (dịka ihe ọkụkụ, njirimara ala/topography, ihe ndị na-edozi ahụ, ọkwa mmiri, ọkwa nitrogen, pH, EC, mg, K, na ndị ọzọ).[10] A na-anakọta data yiri nke ahụ site n'usoro ihe mmetụta etinyere na ngwakọ ndị nwere GPS. Usoro ndị a nwere ihe mmetụta nke na-eme ihe n'ezie na-atụ ihe niile site na ọkwa chlorophyll ruo ọkwa mmiri osisi, yana foto dị iche iche.[11] A na-eji data a na njikọ satịlaịtị site na teknụzụ mgbanwe ọnụego mgbanwe (VRT) gụnyere ndị na-akụ mkpụrụ, ndị na-efesa, wdg iji kesaa akụrụngwa kacha mma. Otú ọ dị, ọganihu nkà na ụzụ na-adịbeghị anya enyerela aka iji ihe mmetụta nke oge eme ihe ozugbo na ala, nke nwere ike ibunye data na ikuku na-enweghị mkpa ọnụnọ mmadụ.[6][7][8]

Ụgbọ ala ndị na-akwọ ụgbọ ala na-anaghị akwụ ụgwọ bụ ndị dị ọnụ ala nke ndị ọkwọ ụgbọ elu nwere ike ịrụ ọrụ ugbo nke ọma. Enwere ike ịkwado drones ọrụ ugbo [15] nwere igwefoto multispectral ma ọ bụ RGB iji weghara ọtụtụ onyonyo nke ubi enwere ike ịdụkọta ọnụ site na iji ụzọ fotogrammetric mepụta orthophotos. Onyonyo dị iche iche nwere ọtụtụ ụkpụrụ n'otu pikselụ na mgbakwunye na omenala uhie, ụkpụrụ na-acha anụnụ anụnụ dị ka nso infrared na ụkpụrụ ụdị dị iche iche nke na-acha uhie uhie ejiri na-ahazi na nyochaa ndepụta ahịhịa dị ka maapụ NDVI.[16] Drones ndị a nwere ike ịse foto yana ịnye ntụnyere mpaghara dị ka elu, nke na-enye ohere ngwanrọ ịrụ ọrụ algebra maapụ iji wuo maapụ topography. Enwere ike iji map ndị a na-ahụ maka ihe ọkụkụ na-ejikọta ahụike ihe ọkụkụ na ọdịdị ọdịdị, nke a ga-esi na ya pụta iji kwalite ntinye ihe ọkụkụ dị ka mmiri, fatịlaịza ma ọ bụ kemịkalụ dị ka ahịhịa ahịhịa na ndị na-ahụ maka uto site na ngwa mgbanwe ọnụego.

Akụkọ ihe mere eme

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Ọrụ ugbo ziri ezi bụ akụkụ dị mkpa nke usoro nke atọ nke mgbanwe ọrụ ugbo nke oge a. Mgbanwe ọrụ ugbo mbụ bụ mmụba nke ọrụ ugbo, site na 1900 ruo 1930. Onye ọrụ ugbo ọ bụla na-emepụta nri zuru ezu iji nye ihe dị ka mmadụ 26 nri n'oge a.[9] Afọ 1960 kpaliri Green Revolution na usoro ọhụrụ nke mgbanwe mkpụrụ ndụ ihe nketa, nke mere ka onye ọrụ ugbo ọ bụla na-enye ihe dị ka mmadụ 156.[9] A na-atụ anya na ka ọ na-erule afọ 2050, ọnụ ọgụgụ ndị bi n'ụwa niile ga-eru ihe dị ka ijeri 9.6, mmepụta nri ga-abụrịrị okpukpu abụọ site na ọkwa dị ugbu a iji nye ọnụ ọ bụla nri. Site na ọganihu teknụzụ ọhụrụ na mgbanwe ọrụ ugbo nke ọrụ ugbo ziri ezi, onye ọrụ ugbo ọ bụla ga-enwe ike inye mmadụ 265 nri n'otu mpaghara ahụ.[9]

Nchịkọta

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Ugboro mbụ nke mgbanwe ọrụ ugbo ziri ezi bịara n'ụdị satellite na ihe oyiyi ikuku, amụma ihu igwe, ngwa fatịlaịza na-agbanwe agbanwe, na ihe ngosi ahụike ihe ọkụkụ.[10] Ifufe nke abụọ na-agbakọta data igwe maka ọbụna ịkụ osisi ziri ezi, eserese ala, na data ala.[11]

Ọrụ ugbo ziri ezi na-ezube imeziwanye njikwa ọkwa n'ihe gbasara:

  • wuru ihe ndekọ nke ugbo ha
  • imeziwanye mkpebiime mkpebi
  • ịkwalite nchọpụta ka ukwuu
  • ịkwalite ahịa nke ngwaahịa ugbo
  • melite ndokwa ịgbazite na mmekọrịta ya na ndị nwe ụlọ
  • bulie ogo nke ngwaahịa ugbo (dịka ọkwa protein na ọka wit)

Ịkụ ihe na-enye ntụziaka

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Ịkụ ihe na-enye ntụziaka bụ ụdị usoro ọrụ ugbo nke na-enye ndụmọdụ ịkụ ihe na-akpali data nke nwere ike ikpebi ọnụego ịkụ ihe na'ụzọ dịgasị iche iche iji kwado ọnọdụ dịgasịiche gafee otu ubi, iji bulie ihe ọkụkụ. A kọwawo ya dị ka "Big Data on the farm". Monsanto, DuPont na ndị ọzọ na-amalite teknụzụ a na US.[12][13]

Ụkpụrụ Ndị Dị na ya

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Ọrụ ugbo ziri ezi na-eji ọtụtụ ngwá ọrụ ma ebe a bụ ụfọdụ n'ime ihe ndị bụ isi: traktọ, ngwakọta, sprayers, ndị ọrụ ugbo, ndị na-egwu ala, nke a na-ewere dị ka usoro nduzi onwe onye. Obere ngwaọrụ dị na ngwá ọrụ na-eji GIS (usoro ozi ala) bụ ihe na-eme ka ọrụ ugbo bụrụ ihe ziri ezi. Ị nwere ike iche echiche banyere usoro GIS dị ka "ụbụrụ." Iji nwee ike iji ọrụ ugbo ziri ezi, ọ dị mkpa ka ejiri teknụzụ na usoro data ziri ezi jikọta ngwá ọrụ ahụ. Ngwá ọrụ ndị ọzọ gụnyere teknụzụ ọnụego na-agbanwe agbanwe (VRT), usoro nhazi ụwa na usoro ozi ala, nnwale grid, na ihe mmetụta dịpụrụ adịpụ.[14]

Ebe a na-achọta ala

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Geolocating a ubi na-enyere onye ọrụ ugbo aka ikpuchi ozi anakọtara site na nyocha nke ala na nitrogen fọdụrụnụ, na ozi gbasara ihe ọkụkụ gara aga na resistivity nke ala. A na-eme geolocation n'ụzọ abụọ

  • A na-akọwa ubi ahụ site na iji onye na-anabata GPS n'ime ụgbọala ka onye ọrụ ugbo na-anya traktọ gburugburu ubi ahụ.
  • A na-akọwa ubi ahụ na basemap nke sitere na foto ikuku ma ọ bụ satellite. Ihe oyiyi ndị ahụ ga-enwerịrị ọkwa ziri ezi nke mkpebi na ogo geometric iji hụ na geolocation ziri ezi.

Mgbanwe

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Mgbanwe n'ime na n'etiti mpaghara nwere ike ịpụta site na ọtụtụ ihe. Ndị a gụnyere ọnọdụ ihu igwe (ụgbụgbọ mmiri, ụkọ mmiri ozuzo, wdg), ala (ọdịdị, omimi, ọkwa nitrogen), omume ịkọ ugbo (ọrụ ugbo na-adịghị arụ ọrụ ugbo), ahịhịa na ọrịa.Ihe ngosi na-adịgide adịgide - ọkachasị ihe ngosi ala - na-enye ndị ọrụ ugbo ozi gbasara isi ihe ndị na-adịkarị na gburugburu ebe obibi.Ihe ngosi isi na-enye ha ohere ịchọpụta ọnọdụ ihe ọkụkụ, ya bụ, ịhụ ma ọrịa na-etolite, ma ọ bụrụ na ihe ọkụkụ ahụ na-ata ahụhụ site na nrụgide mmiri, nrụgide nitrogen, ma ọ bụ ebe obibi, ma ice mebiri ya na ihe ndị ọzọ.Ozi a nwere ike ịpụta site na ụlọ ọrụ ihu igwe na ihe mmetụta ndị ọzọ (resistivity eletrik nke ala, nchọpụta anya nkịtị, foto satellite, wdg).Nnyocha nke ala na nyocha ala na-eme ka o kwe omume ịlele mmiri dị n'ime. Resistivity nke ala bụkwa ihe dị mfe ma dị ọnụ ala.[15]

Atụmatụ

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Ihe oyiyi NDVI e ji obere usoro ikuku Stardust II mee n'otu ụgbọ elu (299 mosaic images)

N'iji map ala, ndị ọrụ ugbo nwere ike ịchụso usoro abụọ iji gbanwee ihe ntinye ubi:

  • Ụzọ ịkọ ọdịnihu: dabere na nyocha nke ihe ngosi kwụ otu ebe (ala, resistivity, akụkọ ihe mere eme nke ubi, wdg) n'oge usoro ihe ọkụkụ.
  • Usoro nchịkwa: ozi sitere na ihe ngosi kwụ otu ebe na-emelite mgbe niile n'oge usoro ihe ọkụkụ site na:
    • nnwale: ịtụle biomass, ịtụle chlorophyll nke akwụkwọ, ịtụ mkpụrụ osisi, wdg.
    • Mmetụta dịpụrụ adịpụ: ịtụle parameters dị ka okpomọkụ (ikuku / ala), iru mmiri (ikuku/ala / akwụkwọ), ifufe ma ọ bụ obosara osisi nwere ike ime n'ihi Wireless Sensor Networks na Intanet nke ihe (IoT) [16]
    • proxy-detection: ihe mmetụta dị n'ime ụgbọala na-atụle ọnọdụ akwụkwọ; nke a chọrọ ka onye ọrụ ugbo na-akwọ ụgbọala gburugburu ubi ahụ dum.
    • mmetụta dị n'elu ma ọ bụ satellite: a na-enweta ihe oyiyi multispectral ma na-edozi ya iji nweta map nke ihe ọkụkụ biophysical parameters, gụnyere ihe ngosi nke ọrịa.[17] Ngwá ọrụ ikuku nwere ike ịlele oke mkpuchi osisi na ịmata ọdịiche dị n'etiti ihe ọkụkụ na ahịhịa.[18]

Mkpebi nwere ike ịdabere na ụdị nkwado mkpebi (ụdị ihe ọkụkụ na ụdị aro) dabere na nnukwu data, mana na nyocha ikpeazụ ọ dị n'aka onye ọrụ ugbo ikpebi n'ihe gbasara uru azụmaahịa na mmetụta na gburugburu ebe obibi- ọrụ nke usoro ọgụgụ isi (AI) na-eweghara dabere na mmụta igwe na netwọk akwara.

Ọ dị mkpa ịghọta ihe mere e ji nabata teknụzụ PA ma ọ bụ na a nabataghị ya, "maka na ntinye teknụzụ nke PA ga-eme, onye ọrụ ugbo ga-ahụ teknụzụ ahụ dị ka ihe bara uru ma dị mfe iji mee ihe. O nwere ike ọ gaghị ezu inwe data dị mma n'èzí na uru akụ na ụba nke teknụzụ AP dịka nghọta nke ndị ọrụ ugbo nwere igosipụta echiche akụ na ụba ndị a. "[19]

Mmejuputa omume

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Nkà na ụzụ ozi ọhụrụ na nkwurịta okwu na-eme ka njikwa ihe ọkụkụ dị n'ọhịa rụọ ọrụ nke ọma ma dịkwuo mfe maka ndị ọrụ ugbo.Mmetụta nke mkpebi nchịkwa ihe ọkụkụ na-akpọ maka ngwá ọrụ ugbo nke na-akwado teknụzụ dịgasị iche iche (VRT), dịka ọmụmaatụ, ọnụ ọgụgụ dịgasịiche nke mkpụrụ osisi yana ngwa dịgasị anya (VRA) nke nitrogen na ngwaahịa phytosanitary.[20]

Ọrụ ugbo ziri ezi na-eji teknụzụ na ngwá ọrụ ugbo (dịka traktọ, sprayers, harvesters, wdg):

  • usoro ọnọdụ (dịka ndị na-anabata GPS na-eji akara satellite iji chọpụta kpọmkwem ọnọdụ na ụwa);
  • Usoro ozi ala (GIS), ya bụ, ngwanrọ nke na-aghọta data niile dịnụ;
  • Ngwá ọrụ ugbo na-agbanwe agbanwe (onye na-akụ, onye na-agbasa).

Ojiji a na-eji ya eme ihe gburugburu ụwa

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Pteryx UAV, UAV ndị nkịtị maka foto elu na eserese foto nwere isi igwefoto na-agbagharị agbagharị

Echiche nke ọrụ ugbo ziri ezi pụtara na United States na mbido afọ 1980. N'afọ 1985, ndị na-eme nchọpụta na Mahadum nke Minnesota gbanwere ntinye lime dị iche iche n'ubi ihe ọkụkụ. Ọ bụkwa n'oge a ka omume nke nnwale grid pụtara (na-etinye grid kwụ ọtọ nke otu sample kwa hekta). Ka ọ na-erule ngwụcha afọ 1980, a na-eji usoro a eme ihe iji nweta map mbụ maka fatịlaịza na mgbazi pH. Ojiji nke sensọ mmepụta mepụtara site na teknụzụ ọhụrụ, jikọtara ya na ọbịbịa nke ndị na-anabata GPS, anọwo na-enweta ala kemgbe ahụ. Taa, usoro ndị dị otú ahụ na-ekpuchi ọtụtụ nde hekta.

Na American Midwest (US), a na-ejikọta ya ọ bụghị na ọrụ ugbo na-adịgide adịgide kama na ndị ọrụ ugbo bụ ndị na-anwa ịbawanye uru site na itinye ego naanị n'ebe ndị chọrọ fatịlaịza. Omume a na-enye onye ọrụ ugbo ohere ịgbanwe ọnụego fatịlaịza gafee ubi ahụ dịka mkpa nke GPS guided Grid ma ọ bụ Zone Sampling chọpụtara. Fertilizer nke a ga-agbasa n'ebe ndị na-adịghị mkpa nwere ike itinye ya n'ebe na-eme ya, si otú a na-eme ka ojiji ya dị mma.

N'ụwa niile, ọrụ ugbo ziri ezi mepụtara n'ụzọ dịgasị iche iche. Mba ndị bu ụzọ bụ United States, Canada na Australia. Na Europe, United Kingdom bụ nke mbụ gara n'ụzọ a, France sochiri ya nke ọma, ebe ọ pụtara na 1997-1998. Na Latin America, mba na-eduga bụ Argentina, ebe e webatara ya n'etiti afọ 1990 site na nkwado nke National Agricultural Technology Institute. Brazil guzobere ụlọ ọrụ gọọmentị, Embrapa, iji mee nchọpụta ma melite ọrụ ugbo na-adịgide adịgide. Mmepe nke GPS na usoro mgbasa ozi na-agbanwe agbanwe nyere aka mee ka ọrụ ugbo ziri ezi .[21] Taa, ihe na-erughị 10% nke ndị ọrụ ugbo France nwere usoro mgbanwe. Iji GPS eme ihe n'ọtụtụ ebe, mana nke a akwụsịbeghị ka ha jiri ọrụ ugbo ziri ezi, nke na-enye map ndụmọdụ ọkwa.[22]

Ọ bụ ezie na teknụzụ dijitalụ nwere ike ịgbanwe ọdịdị nke igwe ọrụ ugbo, na-eme ka igwe dịkwuo mma ma dịkwuo mfe, mmepụta na-abụghị nke igwe ka na-achịkwa n'ọtụtụ mba na-enweta ego dị ala na nke dị n'etiti, ọkachasị na mpaghara Sahara Africa. [23][24]Nnyocha banyere ọrụ ugbo ziri ezi maka mmepụta na-abụghị nke igwe na-abawanye na nnabata ya.[25][26][27]  Ihe atụ gụnyere AgroCares aka-held soil scanner, uncrewed air vehicle (UAV) ọrụ (nke a makwaara dị ka drones), na GNSS iji mee map ókèala ubi ma guzobe ala.[28] Otú ọ dị, ọ bụghị ihe doro anya ole ndị na-emepụta ọrụ ugbo na-eji teknụzụ dijitalụ eme ihe n'ezie.[28][29]

Ịkpa anụ ụlọ n'ụzọ ziri ezi na-akwado ndị ọrụ ugbo n'oge site n'ịnọgide na-enyocha ma na-achịkwa mmepụta anụmanụ, mmetụta gburugburu ebe obibi, na ahụike na ọdịmma.[30]Sensọ ndị ejikọtara na ụmụ anụmanụ ma ọ bụ na ngwá ọrụ ụlọ nkwakọba ihe na-arụ ọrụ na njikwa ihu igwe ma na-enyocha ọnọdụ ahụike, mmegharị na mkpa ụmụ anụmanụ.  Dịka ọmụmaatụ, enwere ike iji akara eletrọniki (EID) nke na-enye ohere ka robot na-enye mmiri ara nweta nchekwa data nke udder coordinates maka ehi ụfọdụ.[31] Ahịa usoro mmiri ara ehi na-akpaghị aka n'ụwa niile amụbaala n'ime afọ ndị na-adịbeghị anya, mana ọ ga-abụrịrị na nkuchi na Northern Europe, ma eleghị anya ọ fọrọ nke nta ka ọ ghara ịdị na mba ndị na-enweta ego dị ala na nke etiti.[32][33][34] Ngwaọrụ na-enye nri maka ehi na ọkụkọ dịkwa, mana data na ihe akaebe gbasara usoro nkuchi ha na ndị ọkwọ ụgbọala dịkwa ụkọ. [23][24]

E gosiputara uru akụ na ụba na gburugburu ebe obibi nke ọrụ ugbo ziri ezi na China, mana China na-esote mba ndị dị ka Europe na United States n'ihi na usoro ọrụ ugbo nke China nwere obere ugbo ezinụlọ, nke na-eme ka ọnụego nnabata nke ọrụ ugpo ziri ezi dị ala karịa mba ndị ọzọ. Ya mere, China na-anwa iwebata teknụzụ ọrụ ugbo ziri ezi n'ime mba nke ya ma belata ihe ize ndụ ụfọdụ, na-emeghe ụzọ maka teknụzụ China iji zụlite ọrụ ugbo n'ọdịnihu.[35]

N'ọnwa Disemba afọ 2014, onye isi ala Russia kwuru okwu n'ụlọ omebe iwu Russia ebe ọ kpọrọ oku maka National Technology Initiative (NTI). A na-ekewa ya na obere ihe dịka FoodNet initiative. Ihe omume FoodNet nwere usoro ihe ndị a kpọsara dị mkpa, dị ka ọrụ ugbo ziri ezi. Ubi a nwere mmasị pụrụ iche na Russia dị ka ngwá ọrụ dị mkpa n'ịmepụta ihe ndị dị na bioeconomy na Russia.[36][37]

Mmetụta akụ na ụba na gburugburu ebe obibi

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Ọrụ ugbo ziri ezi, dị ka aha ahụ na-egosi, pụtara itinye ihe ntinye ziri ezi na nke ziri ezi dị ka mmiri, fatịlaịza, ọgwụ ahụhụ wdg. n'oge ziri ezi maka ihe ọkụkụ maka ịbawanye mmepụta ya na ịbawanye ihe ọkụkụ ya. Omume nchịkwa ọrụ ugbo ziri ezi nwere ike belata nke ukwuu ọnụọgụ nke ihe oriri na ihe ọkụkụ ndị ọzọ eji eme ihe mgbe ha na-eme ka ihe ọkụkụ dị elu.[38] N'ụzọ dị otú a, ndị ọrụ ugbo na-enweta nloghachi na itinye ego ha site n'ichekwa mmiri, ọgwụ ahụhụ, na fatịlaịza.

Nke abụọ, uru buru ibu nke itinye aka na-emetụta mmetụta gburugburu ebe obibi. Itinye oke kemịkal n'ebe kwesịrị ekwesị na n'oge kwesịrị ekwesị na-abara ihe ọkụkụ, ala na mmiri dị n'okpuru ala uru, ya mere usoro ihe ọkụkụ dum.[39] N'ihi ya, ọrụ ugbo ziri ezi aghọwo isi nkuku nke Ọrụ ugbo na-adịgide adịgide, ebe ọ bụ na ọ na-akwanyere ihe ọkụkụ, ala na ndị ọrụ ugbo ùgwù. Ọrụ ugbo na-adịgide adịgide na-achọ ijide n'aka na a na-aga n'ihu na-enye nri n'ime oke gburugburu ebe obibi, akụ na ụba na mmekọrịta mmadụ na ibe ya achọrọ iji kwado mmepụta ogologo oge.

Akụkọ 2013 gbalịrị igosi na ọrụ ugbo ziri ezi nwere ike inyere ndị ọrụ ugbo nọ na mba ndị na-emepe emepe dịka India aka.[40]

Ọrụ ugbo ziri ezi na-ebelata nrụgide nke ọrụ ugbo na gburugburu ebe obibi site n'ịbawanye arụmọrụ nke igwe na itinye ya n'ọrụ. Dịka ọmụmaatụ, ojiji nke ngwaọrụ nchịkwa dịpụrụ adịpụ dị ka GPS na-ebelata ojiji mmanụ ụgbọala maka ọrụ ugbo, ebe itinye ihe oriri ma ọ bụ ọgwụ ahụhụ nwere ike belata ojiji nke ntinye ndị a, si otú ahụ na-echekwa ego ma belata nsị na-emerụ ahụ n'ime ụzọ mmiri.[41]

GPS na-ebelata ọnụ ọgụgụ nke mkpakọ n'ala site na ịgbaso usoro nduzi e mere n'oge gara aga. Nke a ga-enyekwa ohere maka obere oge n'ọhịa ma belata mmetụta gburugburu ebe obibi nke ngwá ọrụ na kemịkal.

Ọrụ ugbo ziri ezi na-emepụta ọtụtụ data dị iche iche nke na-emepụta ohere iji gbanwee ma jiri data dị otú ahụ mee ihe maka nkà mmụta ihe ochie na ọrụ ihe nketa, na-eme ka nghọta nke nkà mmụta ihe mgbe ochie na ala ugbo nke oge a.[42]

Nkà na ụzụ na-apụta

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Ọrụ ugbo ziri ezi bụ itinye n'ọrụ teknụzụ ọrụ ugbo dijitalụ. E tinyewo ihe karịrị ijeri $ 4.6 na ụlọ ọrụ teknụzụ ọrụ ugbo - mgbe ụfọdụ a na-akpọ agtech.[9]

Robots

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Traktọ ndị na-eduzi onwe ha adịla oge ugbu a, ka akụrụngwa John Deere na-arụ ọrụ dị ka ụgbọ elu na autopilot. Traktọ na-arụ ọtụtụ ọrụ, onye ọrụ ugbo na-abanye maka ihe mberede.[45] Nkà na ụzụ na-aga n'ihu n'igwe na-enweghị ọkwọ ụgbọala nke GPS haziri iji gbasaa fatịlaịza ma ọ bụ ịkọ ala. A na-ebute nnwere onwe nke teknụzụ site na mkpa nyocha nke na-achọsi ike, na-esikarị ike ịrụzu naanị site n'aka ndị ọrụ ugbo na-arụ ọrụ. N'ọtụtụ ọnọdụ nke ọnụ ọgụgụ mmepụta dị elu, mmezi akwụkwọ ntuziaka enweghị ike ịkwado.[49] Ihe ọhụrụ ndị ọzọ na-agụnye, obere ọkụ anyanwụ, igwe/robot nke na-achọpụta ahịhịa na-egbu ya kpọmkwem site na iji ọgwụ ahịhịa ma ọ bụ lasers..[39][43][44]

Robots ọrụ ugbo, nke a makwaara dị ka AgBots, adịlarị, mana a na-emepụta robots owuwe ihe ubi dị elu iji mata mkpụrụ osisi ndị tozuru etozu, gbanwee ọdịdị na ogo ha, ma jiri nlezianya wepụta ha na alaka.[45]

Drones na ihe osise satellite

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A na-eji teknụzụ Drone na Satellite eme ihe n'ọrụ ugbo ziri ezi. Nke a na-emekarị mgbe drones na-ewere foto dị elu ebe satellites na-ejide foto buru ibu. Enwere ike ijikọta foto ụgbọ elu site na ụgbọ elu dị mfe na data sitere na ndekọ satellite iji buo amụma maka mmepụta n'ọdịnihu dabere na ọkwa dị ugbu a nke biomass. Ihe oyiyi ndị a chịkọtara nwere ike ịmepụta map contour iji soro ebe mmiri na-aga, chọpụta mkpụrụ dịgasị iche iche, ma mepụta map nke ebe ndị na-amị mkpụrụ karịa ma ọ bụ obere.[39]

Intanet nke ihe

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Intanet nke ihe bụ netwọk nke ihe ndị a na-ahụ anya nwere ngwá electronic nke na-eme ka nchịkọta data na nchịkọta. IoT na-abanye n'ọrụ na mmepe nke sensọ na ngwanrọ njikwa ugbo. Dịka ọmụmaatụ, ndị ọrụ ugbo nwere ike iji spectroscopy tụọ nitrogen, phosphorus, na potassium na nsị mmiri, nke a ma ama na-ekwekọghị.[39] Ha nwere ike nyochaa ala iji hụ ebe ehi emeela nsị ma tinye fatịlaịza naanị n'ebe ndị chọrọ ya. Nke a na-ebelata ojiji nke fatịlaịza ruo pasent 30.[45] Sensọ mmiri n'ime ala na-ekpebi oge kachasị mma maka osisi mmiri dịpụrụ adịpụ.[46] Enwere ike ịhazi usoro ịgba mmiri iji gbanwee akụkụ nke ogwe osisi ha na-enye mmiri dabere na mkpa na mmiri ozuzo nke osisi ahụ.[39]

Ọ bụghị naanị na ihe ọhụrụ na-ejedebe na osisi - enwere ike iji ha mee ihe maka ọdịmma nke ụmụ anụmanụ. Enwere ike itinye anụ ụlọ na sensọ dị n'ime iji nyochaa acid nke afọ na nsogbu mgbari nri. Sensọ ndị dị n'èzí na-agbaso usoro mmegharị iji chọpụta ahụike na ahụike ehi, mmetụta mmerụ ahụ, ma mata oge kachasị mma maka ịzụlite.[39] Enwere ike ijikọta data a niile sitere na ihe mmetụta ma nyochaa iji chọpụta usoro na usoro.

Dị ka ihe atụ ọzọ, enwere ike iji teknụzụ nlekota mee ka ịkpa aṅụ dịkwuo irè. Aṅụ nwere uru dị ukwuu n'ihe gbasara akụ na ụba ma na-enye ọrụ dị mkpa maka ọrụ ugbo site n'ịtụba ihe ọkụkụ dịgasị iche iche. Nnyocha nke ìgwè aṅụ site na okpomọkụ wireless, iru mmiri na ihe mmetụta na-enyere aka imeziwanye mmepụta nke aṅụ, na ịgụ ịdọ aka ná ntị n'oge na data nke nwere ike iyi ndụ nke ụlọ ahụ dum egwu.[47]

Ngwa smartphones

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Nhazi nwere ike ịbụ nke usoro ọrụ ugbo ziri ezi jikọtara smartphone

Ngwa smartphones na mbadamba na-aghọwanye ewu ewu na ọrụ ugbo ziri ezi. Smartphones na-abịa na ọtụtụ ngwa bara uru arụnyerelarị, gụnyere igwefoto, igwe okwu, GPS, na accelerometer. E nwekwara ngwa ndị a raara nye ngwa ọrụ ugbo dị iche iche dị ka eserese ubi, ịchụso ụmụ anụmanụ, inweta ihu igwe na ozi ihe ọkụkụ, na ndị ọzọ. Ha dị mfe ibugharị, dị ọnụ ala, ma nwee ike kọmpụta dị elu.[48]

Ịmụ ihe igwe

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A na-ejikarị nkuzi igwe eme ihe na njikọ aka na drones, robot, na ịntanetị nke ngwaọrụ ihe. Ọ na-enye ohere maka ntinye data site na nke ọ bụla n'ime isi mmalite ndị a. Kọmputa ahụ na-edozi ozi a ma zighachi omume kwesịrị ekwesị na ngwaọrụ ndị a. Nke a na-enye ohere maka ndị robot ịnye nri zuru oke ma ọ bụ maka ngwaọrụ IoT iji nye mmiri zuru oke ozugbo n'ala.[49] Mmụta igwe nwekwara ike inye ndị ọrụ ugbo amụma n'oge ọ dị mkpa, dị ka ọdịnaya nke nitrogen dị n'ime ala, iji duzie atụmatụ imeju.[50] Ka ọrụ ugbo na-aghọwanye nke dijitalụ, mmụta igwe ga-akwado ọrụ ugbo dị irè na nke ziri ezi na obere ọrụ aka.

Nzukọ

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  • Nzukọ InfoAg
  • Nzukọ Europe na Precision Agriculture (ECPA) (nke a na-eme ugboro abụọ)
  • Nzukọ mba ụwa na Ọrụ Ugbo (ICPA) (nke a na-eme ugboro abụọ)

Hụkwa

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Ebe e si nweta ya

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 Isiokwu a gụnyere ederede sitere naọdịnaya n'efuọrụ. Ikike n'okpuru CC BY-SA 3.0 (Ọ bụ ezie na ọ bụ ezie nankwupụta ikike / ikikeỌpụpụ ọzọ Ihe odide e si nwetaNa Brief to The State of Food and Agriculture 2022 - Ntinye aka n'ọrụ ugbo maka ịgbanwe usoro nri ugbo__ibo____ibo____ibo__ Ọ bụ ezie na ọ bụ[Ihe e dere n'ala ala peeji]

Ihe edeturu

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  1. ↑ Precision Farming : Image of the Day. earthobservatory.nasa.gov (30 January 2001). Retrieved on 12 October 2009.
  2. ↑ McBratney, A., Whelan, B., Ancev, T., 2005. Future Directions of Precision Agriculture. Precision Agriculture, 6, 7-23.
  3. ↑ Whelan, B.M., McBratney, A.B., 2003. Definition and Interpretation of potential management zones in Australia, In: Proceedings of the 11th Australian Agronomy Conference, Geelong, Victoria, 2–6 Feb. 2003.
  4. ↑ Howard, J.A., Mitchell, C.W., 1985. Phytogeomorphology. Wiley.
  5. ↑ Kaspar (March 2003). "Relationship Between Six Years of Corn Yields and Terrain Attributes". Precision Agriculture 4 (1): 87–101. DOI:10.1023/A:1021867123125. ISSN 1385-2256. 
  6. ↑ M. Sophocleous et al., "A Stand-Alone, In Situ, Soil Quality Sensing System for Precision Agriculture," in IEEE Transactions on AgriFood Electronics, doi: 10.1109/TAFE.2024.3351953.
  7. ↑ M. Sophocleous and J. Georgiou, “Precision agriculture: Challenges in sensors and electronics for real-time soil and plant monitoring,” 2017 IEEE Biomed. Circuits Syst. Conf., pp. 1–4, 2017. https://doi.org/10.1109/BIOCAS.2017.8325180
  8. ↑ Sophocleous (2016). IoT & Thick-Film Technology for Underground Sensors in Agriculture.
  9. ↑ 9.0 9.1 9.2 9.3 Digital agriculture: Helping to feed a growing world (23 February 2017). Archived from the original on 15 October 2018. Retrieved on 3 April 2018. Kpọpụta njehie: Invalid <ref> tag; name "ey.com" defined multiple times with different content
  10. ↑ [Haneklaus, Silvia/Lilienthal, Holger/Schnug, Ewald (2016): 25 years Precision Agriculture in Germany – a retrospective. In: Proceedings of the 13th International Conference on Precision Agriculture : 31 July – 3 August 2016, St. Louis, Missouri, USA. Online unter: https://www.openagrar.de/receive/openagrar_mods_00039296]
  11. ↑ Arama Kukutai (27 April 2016). Can Digital Farming Deliver on its Promise?. www.agnewscenter.com.
  12. ↑ Bunge, Jacob. "Big Data Comes to the Farm, Sowing Mistrust", Wall Street Journal, 25 February 2014. Retrieved on 10 February 2015.
  13. ↑ "Digital disruption on the farm", The Economist, 24 May 2014. Retrieved on 10 February 2015.
  14. ↑ Important tools to succeed in precision farming (en-US). Archived from the original on 31 October 2019. Retrieved on 20 November 2019.
  15. ↑ Precision Farming Tools: Soil Electrical Conductivity. Retrieved on 12 June 2016.
  16. ↑ New Waspmote Sensor Board enables extreme precision agriculture in vineyards and greenhouses- Libelium. www.libelium.com.
  17. ↑ Mahlein (1 September 2015). "Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping". Plant Disease 100 (2): 241–251. DOI:10.1094/PDIS-03-15-0340-FE. ISSN 0191-2917. PMID 30694129. 
  18. ↑ "The future of agriculture: Factory fresh", The Economist, 9 June 2016. Retrieved on 12 June 2016.
  19. ↑ Aubert (2012). "IT as enabler of sustainable farming: An empirical analysis of farmers' adoption decision of precision agriculture technology". Decision Support Systems 54: 510–520. DOI:10.1016/j.dss.2012.07.002. Retrieved on 26 November 2020. 
  20. ↑ Herring (29 January 2001). Precision Farming : Feature Articles. earthobservatory.nasa.gov. Retrieved on 12 October 2009.
  21. ↑ Simon Blackmore: Farming with robots. SPIE Newsroom (2 June 2016). Retrieved on 2 June 2016.
  22. ↑ precision agriculture with satellite imagery. Archived from the original on 7 April 2011.
  23. ↑ 23.0 23.1 (2022) The State of Food and Agriculture 2022 − Leveraging agricultural automation for transforming agrifood systems. Rome: Food and Agriculture Organization of the United Nations (FAO). DOI:10.4060/cb9479en. ISBN 978-92-5-136043-9.  Kpọpụta njehie: Invalid <ref> tag; name ":0" defined multiple times with different content
  24. ↑ 24.0 24.1 (2022) In Brief to The State of Food and Agriculture 2022 − Leveraging automation in agriculture for transforming agrifood systems. Rome: Food and Agriculture Organization of the United Nations (FAO). DOI:10.4060/cc2459en. ISBN 978-92-5-137005-6.  Kpọpụta njehie: Invalid <ref> tag; name ":1" defined multiple times with different content
  25. ↑ Nyaga (2021-08-01). "Precision agriculture research in sub-Saharan Africa countries: a systematic map" (in en). Precision Agriculture 22 (4): 1217–1236. DOI:10.1007/s11119-020-09780-w. ISSN 1573-1618. 
  26. ↑ Onyango (2021-01-22). "Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review" (in en). Sustainability 13 (3): 1158. DOI:10.3390/su13031158. ISSN 2071-1050. 
  27. ↑ Proceedings of 1st African Conference of Precision Agriculture – African Plant Nutrition Institute (APNI) (en-US). Retrieved on 2022-12-23.
  28. ↑ 28.0 28.1 Lowenberg-DeBoer (2019). "Setting the Record Straight on Precision Agriculture Adoption" (in en). Agronomy Journal 111 (4): 1552–1569. DOI:10.2134/agronj2018.12.0779. ISSN 0002-1962. 
  29. ↑ Van Beek, C (2020). Adoption level is the most underestimated factor in fertiliser recommendations. AgroCares. Retrieved on 23 December 2022. 
  30. ↑ Schillings (2021). "Exploring the Potential of Precision Livestock Farming Technologies to Help Address Farm Animal Welfare". Frontiers in Animal Science 2. DOI:10.3389/fanim.2021.639678. ISSN 2673-6225. 
  31. ↑ Knight (2020). "Review: Sensor techniques in ruminants: more than fitness trackers" (in en). Animal 14 (S1): s187–s195. DOI:10.1017/S1751731119003276. PMID 32024562. 
  32. ↑ Global milking robots market size by type, by herd size, by geographic scope and forecast. Verified Market Research (2020). Retrieved on 24 July 2022.
  33. ↑ Rodenburg (2017). "Robotic milking: Technology, farm design, and effects on work flow". Journal of Dairy Science 100 (9): 7729–7738. DOI:10.3168/jds.2016-11715. ISSN 0022-0302. PMID 28711263. 
  34. ↑ Lowenberg-DeBoer, J. (2022). Economics of adoption for digital automated technologies in agriculture. Background paper for The State of Food and Agriculture 2022, FAO Agricultural Development Economics Working Paper 22-10. Rome: Food and Agriculture Organization of the United Nations (FAO). DOI:10.4060/cc2624en. ISBN 978-92-5-137080-3. 
  35. ↑ Kendall (2017). "Precision Agriculture in China: Exploring Awareness, Understanding, Attitudes and Perceptions of Agricultural Experts and End-Users in China". Advances in Animal Biosciences 8 (2): 703–707. DOI:10.1017/S2040470017001066. 
  36. ↑ Osmakova (2018). "Recent biotechnology developments and trends in the Russian Federation". New Biotechnology 40 (Pt A): 76–81. DOI:10.1016/j.nbt.2017.06.001. PMID 28634066. 
  37. ↑ Рынки Нти.
  38. ↑ Pepitone (3 August 2016). Hacking the farm: How farmers use 'digital agriculture' to grow more crops. CNNMoney.
  39. ↑ 39.0 39.1 39.2 39.3 39.4 39.5 "The future of agriculture", The Economist, 9 June 2016. Kpọpụta njehie: Invalid <ref> tag; name "economist.com" defined multiple times with different content
  40. ↑ Rajvanshi. "Is precision agriculture the solution to India's farming crisis".
  41. ↑ Schieffer (2015). "The economic and environmental impacts of precision agriculture and interactions with agro-environmental policy". Precision Agriculture 16: 46–61. DOI:10.1007/s11119-014-9382-5. 
  42. ↑ Opitz (2023). "Remote Sensing Data to Support Integrated Decision Making in Cultural and Natural Heritage Management - Impasses and opportunities for collaboration in agricultural areas". Internet Archaeology (62). DOI:10.11141/ia.62.10. 
  43. ↑ Papadopoulos. "This new farming robot uses lasers to kill 200,000 weeds per hour", interestingengineering.com, 21 October 2022. Retrieved on 17 November 2022.
  44. ↑ Verdant Robotics launches multi-action agricultural robot for 'superhuman farming'. Robotics & Automation News (23 February 2022). Retrieved on 17 November 2022.
  45. ↑ 45.0 45.1 Five technologies changing agriculture (7 October 2016). Kpọpụta njehie: Invalid <ref> tag; name "idealog.co.nz" defined multiple times with different content
  46. ↑ M. Sophocleous and J. K. Atkinson, “A novel thick-film electrical conductivity sensor suitable for liquid and soil conductivity measurements,” Sensors Actuators, B Chem., vol. 213, pp. 417–422, 2015. https://doi.org/10.1016/j.snb.2015.02.110
  47. ↑ Precision beekeeping with wireless temperature monitoring. IoT ONE. Retrieved on 27 April 2018.
  48. ↑ Suporn Pongnumkul, Pimwadee Chaovalit, and Navaporn Surasvadi, “Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research,” Journal of Sensors, vol. 2015.
  49. ↑ Goap (December 2018). "An IoT based smart irrigation management system using Machine learning and open source technologies". Computers and Electronics in Agriculture 155: 41–49. DOI:10.1016/j.compag.2018.09.040. 
  50. ↑ Grell (9 October 2020). "Determining and Predicting Soil Chemistry with a Point-of-Use Sensor Toolkit and Machine Learning Model". bioRxiv. DOI:10.1101/2020.10.08.331371. 
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