May 5, 2021Summer Sanitation Is Important as Ever
To contact John Palumbo go to: jpalumbo@ag.Arizona.edu
When known weedy fields are ready to plant and labor is expected to be short, it is tempting to use all the preplant herbicides that are available. In lettuce, there are three preplant herbicides available and it is not uncommon to use 2 and occasionally all 3 on the same crop. All three of these herbicides use the same mode of action to kill weeds. There are slight differences between them but they all either stop or disrupt cell division in the roots and or stems of the weeds. They are normally safe to lettuce unless the crop is stressed or the rate, timing or placement are poor. The rationale for using multiple preplant herbicides in lettuce is often to broaden the weed control spectrum or guard against misses caused by misapplication or environmental conditions. There are some hazards, however, that sometimes outweigh the benefits. Potential crop injury is increased. All 3 use the same mode of action and the chance of injuring developing crop roots is compounded. Sometimes herbicides are added that contribute nothing but potential injury to the mix. If you look at the following chart you can see that many weeds are controlled by Kerb, for instance, that are not controlled by Balan or Prefar. Why add them? All three control grasses, goosefoot and purslane. If environmental conditions and applications are optimal it is often possible to use only one. Herbicides are much less expensive than labor, but it is possible to overdo it and cause more problems and expense.
Last year we had a lot of watermelon fields infected with Fusarium from Winterhaven to Yuma, Wellton, and Mohawk Valley. Rain, and overwatering of fields when plants set fruits might have contributed to the disease development.
Fusarium wilt of watermelon, caused by Fusarium oxysporum f. sp. niveum, is one of the oldest described Fusarium wilt diseases and the most economically important disease of watermelon worldwide. It occurs on every continent except Antarctica and new races of the pathogen continue to impact production in many areas around the world. Long-term survival of the pathogen in the soil and the evolution of new races make management of Fusarium wilt difficult.
Symptoms of Fusarium can sometimes be confused with water deficiency, even though there is plenty of water in the field. In Yuma valley we have seen fusarium problem in some overwatered fields.
Initial symptoms often include a dull, gray green appearance of leaves that precedes a loss of turgor pressure and wilting. Wilting is followed by a yellowing of the leaves and finally necrosis. The wilting generally starts with the older leaves and progresses to the younger foliage. Under conditions of high inoculum density or a very susceptible host, the entire plant may wilt and die within a short time. Affected plants that do not die are often stunted and have considerably reduced yields. Under high inoculum pressure, seedlings may damp off as they emerge from the soil.
Initial infection of seedlings usually occurs from chlamydospores (resting structure) that have overwintered in the soil. Chlamydospores germinate and produce infection hyphae that penetrate the root cortex, often where the lateral roots emerge. Infection may be enhanced by wounds or damage to the roots. The fungus colonizes the root cortex and soon invades the xylem tissue, where it produces more mycelia and microconidia. Consequently, the fungus becomes systemic and often can be isolated from tissue well away from the roots. The vascular damage we see in the roots is the defense mechanism of the plant to impede the movement of pathogen.
Disease management include planting clean seeds/transplants, use of resistant cultivars, crop rotation, soil fumigation, soil solarization, grafting, biological control. An integrated approach utilizing two or more methods is required for successful disease management.
Vol. 12, Issue 7, Published 4/7/2021
Over the last several years, there has been a tremendous amount of research activity towards the development of autonomous agriculture vehicles. A quick internet search will reveal over 50 companies or university research groups working in this space. A question I get often from groups developing such platforms is “What is a good agricultural application for our lightweight “robot”?”. It’s a great question, and for Arizona vegetable production, it’s also one that I’m not sure I have a satisfying answer for.
The calls I get regarding autonomous robots are mostly related to automated weeding applications. Automated weeding machines are commercially available, but their adoption has been limited not because of labor costs for tractor operation, rather it is the lack of the development of a functional and cost-effective means for identifying and removing weeds.
For decades, researchers have been attempting to develop sensing systems that are able to reliably detect weeds. Techniques such as 2-D and 3-D color imaging, x-rays, hyperspectral sensing and artificial intelligence have been tried (Slaughter, 2014; Bender et al., 2020). The best performing systems provide about 96% accuracy, meaning that 4% of the crops plants are identified as weeds and would be destroyed by the weeder. For high value vegetable crops like lettuce with gross revenues of roughly $10,000 per acre, killing 4% of the crop equates to $400 per acre of losses. Economically, this does not make sense as hand weeding labor costs are typically $300 per acre or less. The other main issue is that current automated weeding technologies are not highly precise and provide only partial control. Our studies with these types of machines have shown that these systems remove only about 1/3rd of the in-row weeds (Lati, et al., 2016) and a follow up hand weeding operation is often necessary. To be highly cost effective, elimination of the hand weeding step is needed.
In short, my recommendation to research groups asking about applications for autonomous robots is that their time and technical skills would best be served developing reliable crop/weed differentiation systems and a technique to remove a very high percentage of weeds.
Bender, A., Whelan, B. & Sukkarieh, S. 2020. A high‐resolution, multimodal data set for agricultural robotics: A Ladybird's‐eye view of Brassica. J. Field Robotics. 37(1): 73-96.
Lati, R.N, Siemens, M.C., Rachuy, J.S. & Fennimore, S.A. (2016). Intrarow Weed Removal in Broccoli and Transplanted Lettuce with an Intelligent Cultivator. Weed Technology, 30(3), 655-663.
Slaughter, D.C. The biological engineer: Sensing the difference between crops and weeds. Autonomous robotic weed control systems: A review. Computers and Electronics in Agriculture 61(2008): 63-78.