½ÃÀ庸°í¼­
»óǰÄÚµå
1806300

Á¤¹Ð³ó¾÷ ½ÃÀå : ÄÄÆ÷³ÍÆ®º°, ±â¼úº°, ³óÀå ±Ô¸ðº°, ÀÛ¹° À¯Çüº°, ¿ëµµº°, ÃÖÁ¾ ¿ëµµº° - ¼¼°è ¿¹Ãø(2025-2030³â)

Precision Farming Market by Component, Technology, Farm Size, Crop Type, Application, End-use - Global Forecast 2025-2030

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: 360iResearch | ÆäÀÌÁö Á¤º¸: ¿µ¹® 196 Pages | ¹è¼Û¾È³» : 1-2ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    




¡á º¸°í¼­¿¡ µû¶ó ÃֽŠÁ¤º¸·Î ¾÷µ¥ÀÌÆ®ÇÏ¿© º¸³»µå¸³´Ï´Ù. ¹è¼ÛÀÏÁ¤Àº ¹®ÀÇÇØ Áֽñ⠹ٶø´Ï´Ù.

Á¤¹Ð³ó¾÷ ½ÃÀåÀº 2024³â¿¡´Â 104¾ï 1,000¸¸ ´Þ·¯·Î Æò°¡µÇ¾ú½À´Ï´Ù. 2025³â¿¡´Â 114¾ï 9,000¸¸ ´Þ·¯¿¡ À̸£°í, CAGR 10.67%·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 191¾ï 3,000¸¸ ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

ÁÖ¿ä ½ÃÀå Åë°è
±âÁØ ¿¬µµ : 2024³â 104¾ï 1,000¸¸ ´Þ·¯
ÃßÁ¤ ¿¬µµ : 2025³â 114¾ï 9,000¸¸ ´Þ·¯
¿¹Ãø ¿¬µµ : 2030³â 191¾ï 3,000¸¸ ´Þ·¯
CAGR(%) 10.67%

ÀÛ¹° °ü¸®¿¡ Çõ¸íÀ» ÀÏÀ¸Å°°í ÀÚ¿ø Ȱ¿ëÀ» ÃÖÀûÈ­ÇÏ´Â Á¤¹Ð ³ó¾÷ Àü·«À» ÅëÇØ µðÁöÅÐ ³ó¾÷ÀÇ ÀáÀç·ÂÀ» ¹ßÈÖÇÕ´Ï´Ù.

Á¤¹Ð³ó¾÷Àº ³óÀÛ¹° »ý»êÀÇ È¿À²¼º°ú Áö¼Ó°¡´É¼ºÀ» ³ôÀ̱â À§ÇØ µ¥ÀÌÅÍ ±â¹Ý ±â¼úÀ» Ȱ¿ëÇÏ´Â ³ó¾÷ °üÇàÀÇ °Ýº¯À» ÀǹÌÇÕ´Ï´Ù. »ç¹°ÀÎÅÍ³Ý ¼¾¼­, À§¼º ¹× µå·Ð ¿µ»ó, ÀΰøÁö´É ¾Ë°í¸®Áò, °í±Þ ºÐ¼® Ç÷§ÆûÀ» ÅëÇÕÇÏ¿© »ý»êÀÚ´Â Àü·Ê ¾ø´Â Á¤¹Ðµµ·Î ³óÀåÀ» ¸ð´ÏÅ͸µÇÏ°í °ü¸®ÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Çϵå¿þ¾î, ¼ÒÇÁÆ®¿þ¾î, ¼­ºñ½ºÀÇ À¶ÇÕÀº ±âÁ¸ÀÇ ³ó¾÷ ¿öÅ©Ç÷ο츦 »óÈ£ ¿¬°áµÈ »ýŰè·Î ¹Ù²Ù¾î ½Ç½Ã°£ ÀÇ»ç°áÁ¤°ú Á¤±³ÇÑ ÀÚ¿ø ¹èºÐÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù.

Á¤¹Ð³ó¾÷ »ýŰèÀÇ ¹Ì·¡, ÷´Ü±â¼ú°ú Áö¼Ó °¡´ÉÇÑ ½ÇõÀÇ À¶ÇÕ, ±×¸®°í ÁøÈ­ÇÏ´Â ½ÃÀå ¿ªÇÐ ¸ÅÇÎÀ» ÅëÇÑ Á¤¹Ð³ó¾÷ »ýŰèÀÇ ¹Ì·¡¸¦ ¸¸µé¾î°©´Ï´Ù.

Á¤¹Ð³ó¾÷Àº ±â¼úÀÇ ºñ¾àÀûÀÎ ¹ßÀü, Áö¼Ó°¡´É¼º¿¡ ´ëÇÑ ¿ä±¸ Áõ°¡, ½ÃÀå ¿ªÇÐÀÇ ÁøÈ­·Î ÀÎÇØ º¯È­ÀÇ ¹°°á¿¡ ³ëÃâµÇ¾î ÀÖ½À´Ï´Ù. ÀΰøÁö´É°ú ¸Ó½Å·¯´×ÀÇ Çõ½ÅÀº ÀÛ¹°ÀÇ ½ºÆ®·¹½º¸¦ ¿¹ÃøÇϰí ÀÌ»ó ¡Èĸ¦ ½Ç½Ã°£À¸·Î °¨ÁöÇÏ´Â ¿¹Ãø ºÐ¼® ¿£ÁøÀ» °¡´ÉÇÏ°Ô Çß½À´Ï´Ù. ÀÚÀ²ÁÖÇàÂ÷¿Í ·Îº¿ Ç÷§ÆûÀº ¿Ü°ú ¼ö¼ú°ú °°Àº Á¤È®µµ·Î ÀÏ»óÀûÀÎ ÀÛ¾÷À» ¼öÇàÇϸç, °íÇØ»óµµ ¿ø°Ý °¨Áö ½Ã½ºÅÛÀº ´ÙÁß ½ºÆåÆ®·³ µ¥ÀÌÅÍ¿Í ¿­ µ¥ÀÌÅ͸¦ ¼öÁýÇÏ¿© Á¤È®ÇÑ ³óÇÐÀû °³ÀÔÀ» ¾Ë·ÁÁÝ´Ï´Ù. µ¿½Ã¿¡ ºí·ÏüÀÎ ±â¹Ý ÃßÀû¼º ¼Ö·ç¼ÇÀº °ø±Þ¸ÁÀÇ Åõ¸í¼ºÀ» °­È­Çϰí, ³óÀå¿¡¼­ ½ÄʱîÁö ÀÌÇØ°ü°èÀÚ°£ÀÇ ½Å·Ú¸¦ ±¸ÃàÇÕ´Ï´Ù.

2025³â ¹Ì±¹ ³ó»ê¹° °ü¼¼°¡ °ø±Þ¸Á¿¡ ¹ÌÄ¡´Â ´©Àû ¿µÇâ Æò°¡, Á¤¹Ð³ó¾÷ »ç¾÷ÀÇ ±â¼ú äÅðú ºñ¿ë ±¸Á¶

2025³â ¹Ì±¹ÀÌ ¹ßµ¿ÇÑ ÀÏ·ÃÀÇ ³ó¾÷ °ü¼¼´Â Á¤¹Ð³ó¾÷ ºÎ¹®¿¡ ±¤¹üÀ§ÇÑ ¿µÇâÀ» ¹ÌÄ¡°í, °ø±Þ¸Á ±¸¼ºÀ» º¯È­½Ã۰í, ä¿ë ÆÐÅÏ¿¡ ¿µÇâÀ» ¹ÌÄ¡°í ÀÖ½À´Ï´Ù. À̹ø Á¶Ä¡´Â °íÁ¤¹Ð ¾È³» ½Ã½ºÅÛ, ¼¾¼­ ¾î·¹ÀÌ, µå·Ð Ç÷§Æû, °ü·Ã Æß¿þ¾î µî ¼öÀÔ ºÎǰ¿¡ ´ëÇÑ Ãß°¡ °ü¼¼¸¦ ºÎ°úÇÏ¿© Á¶´Þ ºñ¿ëÀ» ³ôÀÌ°í ¸®µå ŸÀÓÀ» ¿¬ÀåÇÏ´Â Ãß°¡ °ü¼¼¸¦ µµÀÔÇß½À´Ï´Ù. ±× °á°ú, Àåºñ Á¦Á¶¾÷ü¿Í ±â¼ú ÅëÇÕ ¾÷üµéÀº »ý»êÀÚ¿¡ ´ëÇÑ ¼­ºñ½º ¼öÁØ ¾à¼ÓÀ» À¯ÁöÇϸ鼭 »õ·Î¿î °¡°Ý ¾Ð·Â¿¡ ´ëÀÀÇϱâ À§ÇØ Á¶´Þ Àü·«À» Àç°ËÅäÇϰí ÀÖ½À´Ï´Ù.

Á¤¹Ð³ó¾÷ Àü·«ÀÇ ±¸¼º¿ä¼Òº°, ±â¼úº°, ³óÀå ±Ô¸ðº°, ÀÛ¹° À¯Çüº°, ¿ëµµº°, ÃÖÁ¾ ¿ëµµº° ºÎ¹®º° ÇÙ½É ÀλçÀÌÆ® °ø°³

´ÙÂ÷¿øÀûÀÎ ºÎ¹® ºÐ¼®À» ÅëÇØ Â÷º°È­µÈ µµÀÔ Æ®·»µå¿Í ÅõÀÚ ¿ì¼±¼øÀ§¸¦ ÆÄ¾ÇÇÒ ¼ö ÀÖ½À´Ï´Ù. ±¸¼º ¿ä¼Ò ¼öÁØ¿¡¼­ Á¤¹Ð ¼¾¼­, ÀÚÀ²ÁÖÇàÂ÷, ¾È³» ¸ðµâ°ú °°Àº Çϵå¿þ¾î´Â ÇöÀå ÀÛ¾÷ÀÇ ÁßÃ߸¦ Çü¼ºÇϰí, µ¥ÀÌÅÍ °ü¸® Ç÷§Æû°ú ºÐ¼® ¿£ÁøÀ» Æ÷ÇÔÇÑ ¼ÒÇÁÆ®¿þ¾î ¼Ö·ç¼ÇÀº ½Ç¿ëÀûÀÎ ÅëÂû·ÂÀ» Á¦°øÇÕ´Ï´Ù. º¸¿ÏÀûÀÎ ¼­ºñ½º Æ÷Æ®Æú¸®¿À´Â ±¸Ãà Áö¿ø, ¸ÂÃãÇü ±³À° ÇÁ·Î±×·¥, Áö¼ÓÀûÀÎ À¯Áöº¸¼ö¸¦ ÅëÇØ Áß¿äÇÑ Áö¿øÀ» Á¦°øÇÏ¿© ¿øÈ°ÇÑ ÅëÇÕ°ú ÃÖÀûÀÇ ¼º´ÉÀ» º¸ÀåÇÕ´Ï´Ù.

¹ÌÁÖ, À¯·´, Áßµ¿/¾ÆÇÁ¸®Ä«, ¾Æ½Ã¾ÆÅÂÆò¾ç ½ÃÀå¿¡¼­ÀÇ Á¤¹Ð³ó¾÷ µµÀÔ µ¿Çâ ¹× °úÁ¦¸¦ Çü¼ºÇÏ´Â Áö¿ª ¿ªÇÐ ºÐ¼®

¼¼°èÀûÀ¸·Î º¼ ¶§, ºÏ¹Ì¿Í ³²¹Ì´Â Á¤¹Ð³ó¾÷ »ýŰ谡 °¡Àå ¼º¼÷ÇÑ Áö¿ª Áß ÇϳªÀÔ´Ï´Ù. ºÏ¹Ì¿¡¼­´Â °­·ÂÇÑ ±¤¼¶À¯ ¹× À§¼º ¿¬°á°ú Áö¿øÀûÀÎ Á¤Ã¥ ÇÁ·¹ÀÓ¿öÅ©°¡ °áÇÕµÇ¾î °íµµÀÇ Áöħ°ú °¡º¯ ¼Óµµ ±â¼úÀ» ±¤¹üÀ§ÇÏ°Ô µµÀÔÇÒ ¼ö ÀÖ°Ô µÇ¾ú½À´Ï´Ù. ´ë±Ô¸ð »ý»êÀÚ´Â ÅëÇÕ Ç÷§ÆûÀ» Ȱ¿ëÇÏ¿© º¹ÀâÇÑ ÀÛ¹° Àç¹è ÀÛ¾÷À» ÁöÈÖÇϰí, ³ó¾÷ ¼­ºñ½º Á¦°ø¾÷ü´Â Áö½Ä ÀÌÀü°ú Áö¿ª ¸ÂÃãÈ­¸¦ ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ³²¹Ì, ƯÈ÷ ºê¶óÁúÀÇ ±¤È°ÇÑ ¿¬ÀÛÁö´ë¿¡¼­ »ý»êÀÚµéÀÌ ¼öÈ®·® Çâ»ó°ú ȯ°æ º¸È£ÀÇ ±ÕÇüÀ» Ãß±¸Çϸ鼭 »õ·Î¿î ÆÄÀÏ·µ ÀÌ´Ï¼ÅÆ¼ºê¿Í Çùµ¿Á¶ÇÕ ¸ðµ¨ÀÌ ±â¼ú µµÀÔÀÇ Ã˸ÅÁ¦ ¿ªÇÒÀ» Çϰí ÀÖ½À´Ï´Ù.

Á¤¹Ð³ó¾÷ ¼Ö·ç¼ÇÀÇ °æÀï ¿ìÀ§¸¦ ÃËÁøÇÏ´Â Àü·«Àû ÆÄÆ®³Ê½Ê ¹× ±â¼ú ÁßÁ¡ ºÐ¾ß, ¾÷°è ¼±µµÀû ±â¾÷ÀÇ Çõ½Å ޱ¸ Á¤¹Ð³ó¾÷ ¼Ö·ç¼ÇÀÇ °æÀï ¿ìÀ§¸¦ ÃËÁøÇÏ´Â Àü·«Àû ÆÄÆ®³Ê½Ê ¹× ±â¼ú ÁßÁ¡ ºÐ¾ß

Á¤¹Ð³ó¾÷°æÀï ±¸µµ¿¡¼­ ¾÷°è¸¦ ¼±µµÇÏ´Â Âü¿© ±â¾÷µéÀº Â÷¼¼´ë ¼¾¼­ ±â¼ú, ÀΰøÁö´É ¾Ë°í¸®Áò, ÀÚÀ² ·Îº¿ °øÇп¡ ´ëÇÑ ÁýÁßÀûÀÎ ÅõÀÚ¸¦ ÅëÇØ Á¦Ç°À» ÁøÈ­½Ã۰í ÀÖ½À´Ï´Ù. ¿£Áö´Ï¾î¿Í Á¦Ç° ÆÀÀº ´ÙÁß ½ºÆåÆ®·³ À̹ÌÁö ¼¾¼­¸¦ °³¼±Çϰí AI ±â¹Ý ÀÌ»ó °¨Áö ±â´ÉÀ» °­È­ÇÏ¿© Àΰ£ÀÇ °³ÀÔÀ» ÃÖ¼ÒÈ­Çϸ鼭 º¹ÀâÇÑ ¹ç ÀÛ¾÷À» ¼öÇàÇÒ ¼ö ÀÖ´Â ÀÚ±â À¯µµÇü ±â°è¸¦ °³¹ßÇϱâ À§ÇØ Çù·ÂÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±â¼ú Áß½ÉÀÇ ³ë·ÂÀº ¾÷¹« È¿À²¼º°ú ȯ°æÀû Áö¼Ó°¡´É¼ºÀ» ¸ðµÎ ÃæÁ·ÇÏ´Â ¼Ö·ç¼ÇÀ» Á¦°øÇϰڴٴ ¾à¼ÓÀ» °­Á¶ÇÏ´Â °ÍÀÔ´Ï´Ù.

Á¤¹Ð³ó¾÷ µµÀÔ °¡¼ÓÈ­ ¹× ¿î¿µ ÃÖÀûÈ­¸¦ À§ÇÑ ¾÷°è ¸®´õ¸¦ À§ÇÑ Àü·«Àû Áß¿ä »çÇ× ¹× ½ÇÇà °¡´ÉÇÑ Á¦¾È

Á¤¹Ð³ó¾÷¿¡¼­ ¼±µµÀû ÁöÀ§¸¦ È®º¸Çϱâ À§ÇØ ¾÷°è ÀÌÇØ°ü°èÀÚµéÀº ´Ù¾çÇÑ °æ¿µ »óȲ¿¡ ÀûÀÀÇÒ ¼ö ÀÖ´Â ¸ðµâ½Ä, È®Àå °¡´ÉÇÑ ±â¼ú Ç÷§ÆûÀÇ Ã¤ÅÃÀ» ¿ì¼±ÀûÀ¸·Î °í·ÁÇØ¾ß ÇÕ´Ï´Ù. ½Å±â¼ú Á¦°ø¾÷ü¿Í Çù·ÂÇÏ°í ¿ÀÇ ¾ÆÅ°ÅØÃ³ API¸¦ ÅëÇÕÇÔÀ¸·Î½á Á¶Á÷Àº ³ó¾÷ ¿ä±¸»çÇ׿¡ µû¶ó ÁøÈ­ÇÏ´Â µ¿±Þ ÃÖ°­ÀÇ ¼Ö·ç¼ÇÀ» ±¸ÃàÇÒ ¼ö ÀÖ½À´Ï´Ù. ¿¬±¸±â°ü ¹× Àü¹® ½ºÅ¸Æ®¾÷°úÀÇ Àü·«Àû Á¦ÈÞ ¹× °øµ¿ Çõ½Å ÆÄÆ®³Ê½ÊÀ» ÅëÇØ ¿§Áö ÄÄÇ»ÆÃ ¼¾¼­ ³×Æ®¿öÅ©¿¡¼­ ¸Ó½Å·¯´× ±â¹Ý ÀÇ»ç°áÁ¤ Áö¿ø ½Ã½ºÅÛ±îÁö °í±Þ ±â´ÉÀÇ ÆÄÀÌÇÁ¶óÀÎÀ» À°¼ºÇÕ´Ï´Ù.

Á¤¹Ð³ó¾÷¿¡ ´ëÇÑ Á¾ÇÕÀûÀÎ ÅëÂû·ÂÀ» Á¦°øÇϱâ À§ÇØ 1Â÷ °ü°èÀÚÀÇ Àǰ߰ú 2Â÷ µ¥ÀÌÅ͸¦ °áÇÕÇÑ È¥ÇÕ ¹æ¹ý ¿¬±¸ Á¢±Ù ¹æ½Ä¿¡ ´ëÇØ ÀÚ¼¼È÷ ¾Ë¾Æº¾´Ï´Ù.

Á¤¹Ð³ó¾÷¿¡ ´ëÇÑ ½ÉÃþ ºÐ¼®¿¡´Â ¾ö°ÝÇÑ È¥ÇÕ ¹æ¹ý·ÐÀû Á¢±Ù¹æ½ÄÀÌ »ç¿ëµÇ¾úÀ¸¸ç, ÀÌÇØ°ü°èÀÚ¿¡ ´ëÇÑ 1Â÷ Á¶»ç¿Í Á¾ÇÕÀûÀÎ 2Â÷ µ¥ÀÌÅÍ °ËÅ並 °áÇÕÇÏ¿© È®½ÇÇÑ ½ÃÀå ÀλçÀÌÆ®¸¦ Á¦°øÇß½À´Ï´Ù. 1Â÷ Á¶»ç Ȱµ¿¿¡¼­´Â ÁÖ¿ä ³óÀå °æ¿µÀÚ, ³ó±â°è ¿£Áö´Ï¾î, ¼ÒÇÁÆ®¿þ¾î ¼³°èÀÚ, ³óÇÐ ÄÁ¼³ÅÏÆ®, Á¤Ã¥ Àü¹®°¡ µî ´Ù¾çÇÑ Âü¿©ÀÚµé°ú ´ëÈ­¸¦ ³ª´©¾ú½À´Ï´Ù. ÀÌ·¯ÇÑ 1:1 ¸é´ã°ú ÇöÀå ½ÃÂûÀ» ÅëÇØ ½ÇÁ¦ ³ó¾÷ ȯ°æ¿¡¼­ÀÇ ±â¼ú À¯È¿¼º, ¿î¿µ»óÀÇ °úÁ¦, Àü·«Àû ¿ì¼±¼øÀ§ÀÇ ÁøÀü¿¡ ´ëÇÑ ¹Ì¹¦ÇÑ °üÁ¡À» ¾òÀ» ¼ö ÀÖ¾ú½À´Ï´Ù.

Á¤¹Ð³ó¾÷ÀÇ ¼ºÀå°ú Áö¼Ó°¡´É¼ºÀ» ÃËÁøÇϱâ À§ÇÑ ±â¼ú Çõ½Å°ú Çù·ÂÀû °æ·ÎÀÇ Àü·«Àû Á߿伺À» °­Á¶ÇÏ´Â °á·ÐÀû ÅëÂû·Â Á¦°ø

Áö±Ý±îÁöÀÇ ºÐ¼®Àº Á¤¹Ð³ó¾÷ÀÌ º¸´Ù È¿À²ÀûÀ̰í Áö¼Ó°¡´ÉÇÏ¸ç °­°ÇÇÑ ³ó¾÷ ºÎ¹®À¸·ÎÀÇ ÀüȯÀ» À§ÇÑ Ã˸ÅÁ¦·Î¼­ Á¤¹Ð³ó¾÷ÀÇ ÀáÀç·ÂÀ» °­Á¶Çϰí ÀÖ½À´Ï´Ù. ÷´Ü ¼¾½Ì ±â¼ú, ÀΰøÁö´É, ÀÚÀ² ±â°è µîÀ» µµÀÔÇÔÀ¸·Î½á »ý»êÀÚ´Â ÅõÀÔ¹° Ȱ¿ëÀ» ÃÖÀûÈ­ÇÏ°í »ý»ê¼ºÀ» Çâ»ó½Ã۸ç ȯ°æÀû ¿µÇâÀ» ÁÙÀÏ ¼ö ÀÖ½À´Ï´Ù. µ¥ÀÌÅÍ ±â¹Ý ÀÇ»ç°áÁ¤ Áö¿ø ½Ã½ºÅÛ°ú Àç»ý °¡´ÉÇÑ °ü¸® ±â¹ýÀÇ À¶ÇÕÀ» ÅëÇØ Á¤¹Ð³ó¾÷Àº ¼¼°è ½Ä·® ¾Èº¸¿Í ÀÚ¿ø Á¦¾à¿¡ ´ëÀÀÇϱâ À§ÇÑ Àü·«Àû Çʼö ¿ä¼Ò·Î ÀÚ¸®¸Å±èÇϰí ÀÖ½À´Ï´Ù.

¸ñÂ÷

Á¦1Àå ¼­¹®

Á¦2Àå Á¶»ç ¹æ¹ý

Á¦3Àå ÁÖ¿ä ¿ä¾à

Á¦4Àå ½ÃÀå °³¿ä

Á¦5Àå ½ÃÀå ¿ªÇÐ

Á¦6Àå ½ÃÀå ÀλçÀÌÆ®

  • Porter's Five Forces ºÐ¼®
  • PESTEL ºÐ¼®

Á¦7Àå ¹Ì±¹ °ü¼¼ÀÇ ´©Àû ¿µÇâ 2025

Á¦8Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ÄÄÆ÷³ÍÆ®º°

  • Çϵå¿þ¾î
  • ¼­ºñ½º
  • ¼ÒÇÁÆ®¿þ¾î

Á¦9Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ±â¼úº°

  • °¡ÀÌ´ø½º ±â¼ú
  • ¿ø°ÝŽ»ç ±â¼ú
  • °¡º¯ ·¹ÀÌÆ® ±â¼ú

Á¦10Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ³óÀå ±Ô¸ðº°

  • 100-500¿¡ÀÌÄ¿
  • 100¿¡ÀÌÄ¿ ¹Ì¸¸
  • 500¿¡ÀÌÄ¿ ÀÌ»ó

Á¦11Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ÀÛ¹° À¯Çüº°

  • °î¹°
    • ¿Á¼ö¼ö
    • ½Ò
    • ¹Ð
  • °úÀÏ ¹× ä¼Ò
  • Áö¹æÁ¾ÀÚ ¹× Äá·ù
    • Ä«³î¶ó
    • ´ëµÎ
  • Ç÷£Å×ÀÌ¼Ç ÀÛ¹°

Á¦12Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ¿ëµµº°

  • ÀÛ¹° Á¤Âû
  • ³óÀå ³ëµ¿ °ü¸®
  • ÇÊµå ¸ÅÇÎ
  • À繫 °ü¸®
  • Àç°í °ü¸®
  • °¡º¯À² ½Ã¿ë
  • ³¯¾¾ ÃßÀû ¹× ¿¹º¸
  • ¼öÈ®·® ¸ð´ÏÅ͸µ

Á¦13Àå Á¤¹Ð³ó¾÷ ½ÃÀå : ÃÖÁ¾ ¿ëµµº°

  • ±â¾÷ ¼ÒÀ¯ ³óÀå
  • °¡Á· °æ¿µ ³óÀå

Á¦14Àå ¾Æ¸Þ¸®Ä«ÀÇ Á¤¹Ð³ó¾÷ ½ÃÀå

  • ¹Ì±¹
  • ij³ª´Ù
  • ¸ß½ÃÄÚ
  • ºê¶óÁú
  • ¾Æ¸£ÇîÆ¼³ª

Á¦15Àå À¯·´, Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«ÀÇ Á¤¹Ð³ó¾÷ ½ÃÀå

  • ¿µ±¹
  • µ¶ÀÏ
  • ÇÁ¶û½º
  • ·¯½Ã¾Æ
  • ÀÌÅ»¸®¾Æ
  • ½ºÆäÀÎ
  • ¾Æ¶ø¿¡¹Ì¸®Æ®(UAE)
  • »ç¿ìµð¾Æ¶óºñ¾Æ
  • ³²¾ÆÇÁ¸®Ä«°øÈ­±¹
  • µ§¸¶Å©
  • ³×´ú¶õµå
  • īŸ¸£
  • Çɶõµå
  • ½º¿þµ§
  • ³ªÀÌÁö¸®¾Æ
  • ÀÌÁýÆ®
  • Æ¢¸£Å°¿¹
  • À̽º¶ó¿¤
  • ³ë¸£¿þÀÌ
  • Æú¶õµå
  • ½ºÀ§½º

Á¦16Àå ¾Æ½Ã¾ÆÅÂÆò¾çÀÇ Á¤¹Ð³ó¾÷ ½ÃÀå

  • Áß±¹
  • Àεµ
  • ÀϺ»
  • È£ÁÖ
  • Çѱ¹
  • Àεµ³×½Ã¾Æ
  • ű¹
  • Çʸ®ÇÉ
  • ¸»·¹À̽þÆ
  • ½Ì°¡Æ÷¸£
  • º£Æ®³²
  • ´ë¸¸

Á¦17Àå °æÀï ±¸µµ

  • ½ÃÀå Á¡À¯À² ºÐ¼®, 2024
  • FPNV Æ÷Áö¼Å´× ¸ÅÆ®¸¯½º, 2024
  • °æÀï ºÐ¼®
    • AG Leader Technology
    • AGCO Corporation
    • Bayer CropScience Limited
    • Cargill Incorporated
    • Climate LLC
    • CNH Industrial N.V
    • Corteva Agriscience
    • CropX Technologies Ltd.
    • Dickey-John Corporation
    • Farmers Edge Inc.
    • Grownetics, Inc.
    • Hexagon AB
    • John Deere Group
    • Lindsay Corporation
    • METER Group Inc.
    • Sencrop
    • Topcon Positioning Systems, Inc.
    • Trimble Inc.
    • Yara International ASA

Á¦18Àå ¸®¼­Ä¡ AI

Á¦19Àå ¸®¼­Ä¡ Åë°è

Á¦20Àå ¸®¼­Ä¡ ÄÁÅÃÆ®

Á¦21Àå ¸®¼­Ä¡ ±â»ç

Á¦22Àå ºÎ·Ï

LSH

The Precision Farming Market was valued at USD 10.41 billion in 2024 and is projected to grow to USD 11.49 billion in 2025, with a CAGR of 10.67%, reaching USD 19.13 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 10.41 billion
Estimated Year [2025] USD 11.49 billion
Forecast Year [2030] USD 19.13 billion
CAGR (%) 10.67%

Unlocking the Potential of Digital Agriculture Through Precision Farming Strategies That Revolutionize Crop Management and Optimize Resource Utilization

Precision farming represents a seismic shift in agricultural practices, harnessing data-driven technologies to enhance the efficiency and sustainability of crop production. By integrating Internet of Things sensors, satellite and drone imagery, artificial intelligence algorithms, and advanced analytics platforms, growers can monitor and manage fields with unprecedented precision. This convergence of hardware, software, and services transforms traditional agricultural workflows into interconnected ecosystems, enabling real-time decision making and refined resource allocation.

Through the adoption of precision agriculture, farm managers achieve optimized input utilization by tailoring irrigation, fertilization, and pest control strategies to localized field conditions. Such targeted interventions reduce waste, lower operational expenses, and conserve natural resources, while simultaneously supporting environmental stewardship goals. Moreover, the ability to track yield variations and soil health metrics over time empowers agronomists to refine management plans, drive continuous improvement, and mitigate risks associated with climate variability and market volatility.

Looking ahead, the expansion of connectivity infrastructures and the proliferation of affordable sensor networks will further democratize access to precision farming solutions. Collaboration between technology providers, agribusiness stakeholders, and policy makers is critical to unlock the full potential of this digital transformation. As research initiatives and public-private partnerships continue to evolve, precision agriculture is poised to redefine the contours of modern farming, charting a path toward sustainable, scalable, and resilient food systems across diverse agricultural landscapes.

Mapping the Convergence of Advanced Technologies Sustainability Practices and Evolving Market Dynamics Reshaping the Future of Precision Farming Ecosystems

Precision farming is experiencing a wave of transformative shifts driven by technological breakthroughs, heightened sustainability imperatives, and evolving market dynamics. Innovations in artificial intelligence and machine learning have enabled predictive analytics engines that forecast crop stress and detect anomalies in real time. Autonomous vehicles and robotic platforms are performing routine tasks with surgical accuracy, while high-resolution remote sensing systems capture multispectral and thermal data to inform precise agronomic interventions. Simultaneously, blockchain-enabled traceability solutions are strengthening supply chain transparency, building trust among stakeholders from farm to fork.

On the sustainability front, precision agriculture is converging with regenerative practices to reduce carbon footprints and enhance soil health. Variable rate application techniques deliver inputs only where needed, minimizing environmental impact and optimizing resource use. Water-conserving irrigation strategies leverage sensor-driven feedback loops to maintain optimal moisture levels without overapplication. Circular economy principles are also gaining traction as nutrient recycling and waste reduction become integral to long-term land stewardship. These practices not only address regulatory pressures and consumer demands for eco-friendly products but also foster resilient agroecosystems that can adapt to climatic stressors.

Market dynamics are shifting toward service-oriented delivery models and strategic partnerships that accelerate solution deployment. Equipment manufacturers are integrating software-as-a-service offerings, enabling subscription-based access to analytics and support services. Collaboration between agtech startups and established agribusinesses is driving co-innovation in end-to-end platforms, while regional consortia facilitate knowledge sharing and standardization efforts. Moreover, financing mechanisms tailored to technology investments are emerging, lowering barriers to adoption. As these convergent trends gain momentum, the precision farming landscape is being reshaped by a complex interplay of innovation, sustainability, and market forces that promise to define the agriculture of tomorrow.

Evaluating the Cumulative Impact of 2025 U.S. Agricultural Tariffs on Supply Chains Technology Adoption and Cost Structures Within Precision Farming Operations

In 2025, a series of agricultural tariffs enacted by the United States have exerted far-reaching effects on the precision farming sector, altering supply chain configurations and influencing adoption patterns. These measures, targeting imported components such as high-precision guidance systems, sensor arrays, drone platforms, and associated firmware, have introduced additional duties that elevate procurement costs and extend lead times. As a result, equipment manufacturers and technology integrators are reevaluating sourcing strategies to manage new pricing pressures while maintaining service level commitments to growers.

Rising import duties have prompted a notable recalibration in the cost structure of precision farming deployments. Hardware providers have been compelled to absorb a portion of the incremental charges or pass them through to end users, leading some farm operators to postpone or scale back planned implementations. Software vendors, facing indirect cost impacts, have revised licensing frameworks and explored alternative revenue models, including bundled service offerings and tiered subscription schemes. This environment has simultaneously created opportunities for domestic component suppliers and contract manufacturers to capture market share, fueling efforts to localize production and reduce dependency on overseas supply nodes.

In response to these evolving trade dynamics, ecosystem participants are prioritizing strategic resilience and flexibility. Collaborative agreements between technology vendors and regional assemblers are accelerating, while nearshoring initiatives aim to decrease logistical complexity. Forward-looking organizations are engaging in dual-sourcing plans to ensure continuity and negotiating volume commitments that secure favorable tariff treatments. By proactively adapting procurement and partnership strategies, the precision farming community is navigating the cumulative impact of these policy changes and laying the groundwork for sustained growth in a more self-reliant marketplace.

Unveiling Critical Segment-Specific Insights Across Component Technology Farm Size Crop Type Application and End-Use Dimensions in Precision Farming Strategies

Segment analysis across multiple dimensions reveals differentiated adoption trends and investment priorities. At the component level, hardware offerings such as precision sensors, autonomous vehicles, and guidance modules form the backbone of field operations, while software solutions encompassing data management platforms and analytical engines unlock actionable insights. Complementary service portfolios provide critical support through deployment assistance, customized training programs, and ongoing maintenance, ensuring seamless integration and optimal performance.

Within the realm of technology, guidance systems enable automated steering and precise implement control, remote sensing tools deliver high-resolution imagery for crop health assessment, and variable rate mechanisms adjust inputs in real time to match soil variability. These capabilities, when combined, create a multi-layered decision framework that elevates agronomic efficiency and minimizes resource wastage.

Farm size also shapes technology selection and roll-out strategies. Smaller cultivated plots tend to favor modular and scalable systems that align with budget constraints, whereas mid-tier operations commonly adopt integrated platforms that balance cost and capability. Large-scale producers leverage comprehensive, full-featured deployments capable of orchestrating complex workflows across expansive acreages.

Crop-specific requirements further influence solution design. Cereal and grain producers, especially in corn, rice, and wheat sectors, rely heavily on yield monitoring and guidance precision to maximize output, while oilseed and pulse growers focused on canola and soybean varieties benefit from fine-tuned variable rate applications. Specialty operations cultivating fruits, vegetables, or plantation crops prioritize field mapping and scouting tools to support crop protection and quality management.

Across a spectrum of use cases-from crop scouting and labor management to financial and inventory oversight, weather tracking, and yield analytics-operators seek holistic platforms that tie performance metrics to agronomic outcomes. Finally, end-use distinctions reveal that corporate-owned enterprises often invest in capital-intensive, in-house solutions, while family-operated farms gravitate toward collaborative service models and entry-level digital offerings that scale in step with growth objectives.

Analyzing Regional Dynamics Shaping Precision Farming Adoption Trends and Challenges Across the Americas Europe Middle East Africa and Asia-Pacific Markets

Across global landscapes, the Americas exhibit some of the most mature precision farming ecosystems. In North America, robust fiber and satellite connectivity, coupled with supportive policy frameworks, enable widespread implementation of advanced guidance and variable rate technologies. Large-scale producers leverage integrated platforms to orchestrate complex cropping operations, while agronomic service providers facilitate knowledge transfer and localized customization. In South America, emerging pilot initiatives and cooperative models are catalyzing technology uptake, particularly in Brazil's expansive row crop regions, where operators seek to balance yield enhancement with environmental stewardship.

In the Europe, Middle East & Africa region, adoption patterns reflect a mosaic of regulatory priorities and resource constraints. European growers benefit from stringent sustainability mandates and well-developed advisory networks, prompting investments in remote sensing and nutrient management solutions. In Middle Eastern agricultural zones, water scarcity challenges drive precision irrigation and moisture monitoring applications, fostering collaborations with technology vendors that specialize in arid-land adaptation. Africa's nascent precision farming projects, frequently supported by development agencies and research institutions, demonstrate the potential to boost productivity while addressing food security imperatives, although infrastructure limitations remain a hurdle.

Asia-Pacific markets present a blend of large-scale commercial operations and dense smallholder environments. Australia's broadacre farms apply aerial drone surveys and automated steering systems to optimize labor efficiency, whereas China's consolidation of precision agriculture pilots underscores a national push toward digital modernization. In India and Southeast Asia, small-scale growers increasingly access mobile-enabled platforms for field mapping and yield estimation, supported by government subsidies and local service providers. Across Japan and South Korea, agricultural cooperatives integrate data-driven crop scouting and weather forecasting solutions to refine production cycles. As connectivity expands and ecosystem partnerships deepen, Asia-Pacific stands poised to drive the next wave of precision farming innovation.

Exploring Leading Industry Players' Innovations Strategic Partnerships and Technology Focus Areas Driving Competitive Advantage in Precision Farming Solutions

In the competitive landscape of precision farming, leading industry participants are advancing their offerings through targeted investments in next-generation sensor technologies, artificial intelligence algorithms, and autonomous robotics. Engineers and product teams are collaborating to refine multispectral imaging sensors, enhance AI-driven anomaly detection, and develop self-guided machinery capable of executing complex field tasks with minimal human intervention. This technology-centric focus underscores a commitment to delivering solutions that address both operational efficiency and environmental sustainability.

Strategic partnerships and acquisitions are playing a pivotal role in broadening solution portfolios and accelerating time to market. Through alliance agreements with academic research institutions and joint development initiatives, companies are co-creating integrated technology stacks that seamlessly connect hardware, software, and service elements. Open-architecture platforms are gaining traction, enabling third-party developers to contribute specialized modules and fostering an ecosystem of interoperable tools that reduce integration friction for end users.

A shift toward software-as-a-service models and subscription-based access is reshaping commercial strategies. Rather than one-off sales, technology providers are offering tiered service plans that bundle predictive analytics, remote support, and regular updates. This approach not only generates recurring revenue streams but also aligns incentives to maintain long-term customer engagement and satisfaction. Enhanced after-sales support networks, including regional service centers and virtual diagnostic platforms, are ensuring that operators can rapidly troubleshoot issues and maximize uptime.

Region-specific solution adaptations are also emerging as companies tailor products to local agronomic conditions and regulatory contexts. Pilot programs in diverse geographies, from temperate broadacre zones to tropical smallholder landscapes, validate performance across varying crop types and field sizes. User interface advancements, mobile application enhancements, and multilingual support features emphasize customer experience, ensuring that growers of all scales can readily adopt and benefit from precision farming innovations. This holistic competitive posture underscores the dynamic nature of the sector and signals an ongoing commitment to elevating agricultural productivity worldwide.

Strategic Imperatives and Actionable Recommendations for Industry Leaders to Accelerate Precision Farming Adoption and Optimize Operations

To establish a leadership position in precision agriculture, industry stakeholders should prioritize the adoption of modular, scalable technology platforms that can be tailored to diverse operational contexts. By engaging with emerging technology providers and integrating open-architecture APIs, organizations can assemble best-in-class solutions that evolve alongside agronomic requirements. Strategic alliances and co-innovation partnerships with research institutions or specialized startups will cultivate a pipeline of advanced capabilities, from edge computing sensor networks to machine learning-based decision support systems.

Recognizing the heterogeneity of farm operations, solution providers and implementers must develop differentiated packages that address specific crop types and field sizes. Smaller enterprises will benefit from entry-level bundles offering essential functionalities at an accessible price point, while larger producers require comprehensive suites that orchestrate end-to-end workflows. Investing in comprehensive training programs and on-the-ground advisory services will accelerate adoption rates, reduce implementation risks, and build operator confidence in data-driven management processes.

In light of evolving trade policies and tariff headwinds, leaders should pursue diversified supply chain strategies, including nearshoring initiatives and strategic inventory planning. Establishing regional assembly hubs or contract manufacturing partnerships can insulate against import duties and logistical disruptions. Concurrently, exploring alternative component sources and negotiating volume commitments can secure favorable terms and ensure continuity of critical hardware components.

Integrating environmental performance indicators into precision farming platforms will resonate with stakeholders focused on sustainability and regulatory compliance. Embedding carbon accounting modules, soil health tracking metrics, and water usage dashboards into software interfaces not only supports compliance objectives but also positions adopters as stewards of ecological resilience.

Finally, fostering data ecosystems through collaborative consortiums and shared research initiatives will spur continuous innovation. By participating in cross-industry forums and contributing anonymized field data to collective analysis efforts, technology firms and growers alike can accelerate the development of novel agronomic insights, driving sustained competitive advantage and cultivating a robust future for precision agriculture.

Detailing the Mixed-Methods Research Approach Combining Primary Stakeholder Input with Secondary Data to Deliver Comprehensive Precision Farming Insights

A rigorous mixed-methods approach underpins this in-depth analysis of precision farming, combining primary stakeholder engagement with comprehensive secondary data review to deliver robust market insights. Primary research activities encompassed dialogues with a diverse array of participants, including leading farm managers, agricultural machinery engineers, software architects, agronomic consultants, and policy experts. These one-on-one interviews and immersive field visits provided nuanced perspectives on technology efficacy, operational challenges, and evolving strategic priorities in real-world farming environments.

To complement firsthand observations, structured surveys captured qualitative feedback on user experiences, deployment hurdles, and service provider performance. The survey design facilitated cross-comparative assessments across distinct farm sizes and crop types, ensuring that solution viability could be evaluated within appropriate contextual frameworks. Workshop sessions with key opinion leaders and roundtable discussions further explored emerging trends, such as the integration of circular economy practices and data monetization pathways.

Secondary research involved a thorough review of academic journals, industry white papers, government policy documents, patent filings, and association publications. This analysis furnished historical context, regulatory insights, and technology roadmaps, enriching the understanding of long-term innovation trajectories. By synthesizing these varied sources, underlying patterns in adoption dynamics and competitive positioning were identified.

Data triangulation and iterative validation processes ensured the integrity of findings. Insights derived from primary interviews were cross-verified against secondary evidence, while draft conclusions underwent peer review with subject matter experts to refine interpretations. Confidentiality protocols safeguarded sensitive contributions, enabling candid discourse and reinforcing the credibility of the overall research. This methodical approach delivers a balanced, well-substantiated perspective on the current state and future potential of precision agriculture.

Concluding Insights Highlighting the Strategic Imperatives Technological Innovations and Collaborative Pathways Poised to Drive Growth and Sustainability in Precision Farming

The preceding analysis underscores the transformative potential of precision farming as a catalyst for a more efficient, sustainable, and resilient agricultural sector. By embracing advanced sensing technologies, artificial intelligence, and autonomous machinery, growers can optimize input utilization, enhance productivity, and reduce environmental footprints. The convergence of data-driven decision support systems and regenerative management practices positions precision agriculture as a strategic imperative for addressing global food security and resource constraints.

Trade policy shifts, particularly the 2025 U.S. tariffs on key technology components, have reshaped supply chains and cost structures, prompting ecosystem participants to pursue localized manufacturing and diversified sourcing strategies. These developments highlight the importance of adaptive procurement models and collaboration frameworks that mitigate risk while fostering innovation.

A multifaceted segmentation analysis reveals distinct adoption patterns across component categories, technology types, farm sizes, crop portfolios, application areas, and ownership models. This nuanced understanding enables stakeholders to tailor solution portfolios and service offerings to specific operational contexts, driving higher value capture and user satisfaction.

Regional insights expose varying maturity levels, from highly mechanized operations in the Americas and Europe to nascent pilot programs in Africa and widespread smallholder engagement in Asia-Pacific. Recognizing these differences is critical for designing market entry strategies and forging impactful partnerships.

Competitive dynamics in the sector are characterized by a blend of proprietary innovations, strategic partnerships, and open-architecture platforms. Leading actors are adopting subscription-based commercial models, augmenting after-sales support networks, and investing in user-centric software features to differentiate their offerings.

Armed with these comprehensive findings, industry leaders are equipped to implement strategic recommendations-from scalable technology deployment and targeted training initiatives to supply chain resilience measures and sustainability metrics integration. By leveraging this insight, stakeholders can accelerate precision farming adoption and secure long-term competitive advantage in an evolving agricultural landscape.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

  • 4.1. Introduction
  • 4.2. Market Sizing & Forecasting

5. Market Dynamics

  • 5.1. Integration of AI-driven decision support systems in precision farming operations boosts yield optimization and resource efficiency
  • 5.2. Precision sprayer drones with real-time multispectral imaging transform crop management strategies
  • 5.3. Utilization of digital twin crop modeling platforms for predictive yield forecasting and risk management in smart farming
  • 5.4. Integration of robotics for automated weeding and targeted pest control to reduce chemical usage in precision agriculture
  • 5.5. Implementation of blockchain-enabled supply chain tracking for enhanced transparency in precision produce distribution
  • 5.6. Development of carbon credit trading platforms linked to precision farming data for incentivizing sustainable agricultural practices
  • 5.7. Deployment of autonomous field robots for precision weeding and targeted pesticide application
  • 5.8. Implementation of blockchain-enabled supply chain tracking for agricultural data transparency
  • 5.9. Expansion of edge computing solutions in farm machinery for low-latency decision-making at field level
  • 5.10. Adoption of AI-driven predictive analytics for real-time crop disease management

6. Market Insights

  • 6.1. Porter's Five Forces Analysis
  • 6.2. PESTLE Analysis

7. Cumulative Impact of United States Tariffs 2025

8. Precision Farming Market, by Component

  • 8.1. Introduction
  • 8.2. Hardware
  • 8.3. Services
  • 8.4. Software

9. Precision Farming Market, by Technology

  • 9.1. Introduction
  • 9.2. Guidance Technology
  • 9.3. Remote Sensing Technology
  • 9.4. Variable Rate Technology

10. Precision Farming Market, by Farm Size

  • 10.1. Introduction
  • 10.2. 100-500 Acres
  • 10.3. Less than 100 Acres
  • 10.4. More than 500 Acres

11. Precision Farming Market, by Crop Type

  • 11.1. Introduction
  • 11.2. Cereals & Grains
    • 11.2.1. Corn
    • 11.2.2. Rice
    • 11.2.3. Wheat
  • 11.3. Fruits & Vegetables
  • 11.4. Oilseeds & Pulses
    • 11.4.1. Canola
    • 11.4.2. Soybean
  • 11.5. Plantation Crops

12. Precision Farming Market, by Application

  • 12.1. Introduction
  • 12.2. Crop Scouting
  • 12.3. Farm Labor Management
  • 12.4. Field Mapping
  • 12.5. Financial Management
  • 12.6. Inventory Management
  • 12.7. Variable Rate Application
  • 12.8. Weather Tracking and Forecasting
  • 12.9. Yield Monitoring

13. Precision Farming Market, by End-use

  • 13.1. Introduction
  • 13.2. Corporate-Owned Farms
  • 13.3. Family-Owned Farms

14. Americas Precision Farming Market

  • 14.1. Introduction
  • 14.2. United States
  • 14.3. Canada
  • 14.4. Mexico
  • 14.5. Brazil
  • 14.6. Argentina

15. Europe, Middle East & Africa Precision Farming Market

  • 15.1. Introduction
  • 15.2. United Kingdom
  • 15.3. Germany
  • 15.4. France
  • 15.5. Russia
  • 15.6. Italy
  • 15.7. Spain
  • 15.8. United Arab Emirates
  • 15.9. Saudi Arabia
  • 15.10. South Africa
  • 15.11. Denmark
  • 15.12. Netherlands
  • 15.13. Qatar
  • 15.14. Finland
  • 15.15. Sweden
  • 15.16. Nigeria
  • 15.17. Egypt
  • 15.18. Turkey
  • 15.19. Israel
  • 15.20. Norway
  • 15.21. Poland
  • 15.22. Switzerland

16. Asia-Pacific Precision Farming Market

  • 16.1. Introduction
  • 16.2. China
  • 16.3. India
  • 16.4. Japan
  • 16.5. Australia
  • 16.6. South Korea
  • 16.7. Indonesia
  • 16.8. Thailand
  • 16.9. Philippines
  • 16.10. Malaysia
  • 16.11. Singapore
  • 16.12. Vietnam
  • 16.13. Taiwan

17. Competitive Landscape

  • 17.1. Market Share Analysis, 2024
  • 17.2. FPNV Positioning Matrix, 2024
  • 17.3. Competitive Analysis
    • 17.3.1. AG Leader Technology
    • 17.3.2. AGCO Corporation
    • 17.3.3. Bayer CropScience Limited
    • 17.3.4. Cargill Incorporated
    • 17.3.5. Climate LLC
    • 17.3.6. CNH Industrial N.V
    • 17.3.7. Corteva Agriscience
    • 17.3.8. CropX Technologies Ltd.
    • 17.3.9. Dickey-John Corporation
    • 17.3.10. Farmers Edge Inc.
    • 17.3.11. Grownetics, Inc.
    • 17.3.12. Hexagon AB
    • 17.3.13. John Deere Group
    • 17.3.14. Lindsay Corporation
    • 17.3.15. METER Group Inc.
    • 17.3.16. Sencrop
    • 17.3.17. Topcon Positioning Systems, Inc.
    • 17.3.18. Trimble Inc.
    • 17.3.19. Yara International ASA

18. ResearchAI

19. ResearchStatistics

20. ResearchContacts

21. ResearchArticles

22. Appendix

»ùÇà ¿äû ¸ñ·Ï
0 °ÇÀÇ »óǰÀ» ¼±Åà Áß
¸ñ·Ï º¸±â
Àüü»èÁ¦