Yield and quality of potato tuber and its water productivity are influenced by alternate furrow irrigation in a raised bed system

Sarker, Khokan Kumer; Hossain, Akbar; Timsina, Jagadish; Biswas, Sujit K.; Kundu, B. C.; Barman, Alak; Murad, Khandakar Faisal Ibn; Akter, Farzana

doi:10.1016/j.agwat.2019.105750

Cited by 38 publications

(31 citation statements)

References 46 publications

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“…The results show a general increase in stomatal conductance after the application of irrigation treatments for both stress episodes. However, they suggest that the plants generally exhibit a lower ability to respond physiologically during the second stress (dotted line in general under solid line), an indication that stress history influences the plant's ability to extract water from the soil (Chaves et al, 2002;Sarker et al, 2019). These results could be explained by the natural effect of leaves aging (Vos and Oyarzún, 1987;Ahmadi et al, 2010) and the effect of previous stresses lead to possible modifications in the functioning of the plant (Bruce et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…However, the physiological characteristics, such as plant resilience to water stress and stress history, are rarely taken into account. This implies that the plant's ability to extract water from the soil, which depends on its physiological activity and the time spent under a certain stress level (Chaves et al, 2002;Sarker et al, 2019), is not considered. These important factors are also not incorporated in existing drought factor index (DFI; Oukarroum et al, 2007) and crop water deficit index (CWSI; Idso et al, 1981;Bijanzadeh et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Impacts of Water Stress Severity and Duration on Potato Photosynthetic Activity and Yields

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impacts of Water Stress Severity and Duration on Potato Photosynthetic Activity and Yields

et al. 2020

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“…So far, no tools have been available for the potato growers to predict their final production using in-season information that is easily collectable. Thus, timely estimation of tuber production during the growing season is necessary to improve irrigation efficiency, reduce the potential of yield loss caused by water stress, and minimize the impacts of irrigation on the groundwater table [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning

Sun

Liao

Zhang

et al. 2020

Sensors

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Potato is the largest non-cereal food crop in the world. Timely estimation of end-of-season tuber production using in-season information can inform sustainable agricultural management decisions that increase productivity while reducing impacts on the environment. Recently, unmanned aerial vehicles (UAVs) have become increasingly popular in precision agriculture due to their flexibility in data acquisition and improved spatial and spectral resolutions. In addition, compared with natural color and multispectral imagery, hyperspectral data can provide higher spectral fidelity which is important for modelling crop traits. In this study, we conducted end-of-season potato tuber yield and tuber set predictions using in-season UAV-based hyperspectral images and machine learning. Specifically, six mainstream machine learning models, i.e., ordinary least square (OLS), ridge regression, partial least square regression (PLSR), support vector regression (SVR), random forest (RF), and adaptive boosting (AdaBoost), were developed and compared across potato research plots with different irrigation rates at the University of Wisconsin Hancock Agricultural Research Station. Our results showed that the tuber set could be better predicted than the tuber yield, and using the multi-temporal hyperspectral data improved the model performance. Ridge achieved the best performance for predicting tuber yield (R2 = 0.63) while Ridge and PLSR had similar performance for predicting tuber set (R2 = 0.69). Our study demonstrated that hyperspectral imagery and machine learning have good potential to help potato growers efficiently manage their irrigation practices.

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“…In response to the wastage of the limited water resources, adoption of the most efficient methods such as drip and sprinkler irrigation systems is increasingly advocated for increasing yield and water use efficiency of different crops [11][12][13]. However, these methods have not yet been widely adopted among farmers due to their high cost of initial investments, installation, operation, maintenance, and demand for technical knowledge [14]. Such farmers, therefore, need low-cost, simple, easy to install and operate but more efficient and water-saving techniques such as alternate furrow irrigation (AFI) and deficit irrigation (DI).…”

Section: Introductionmentioning

confidence: 99%

Yield and Water Use Efficiency of Potato under Alternate Furrows and Deficit Irrigation

Kassaye

Yilma

Fisha

et al. 2020

International Journal of Agronomy

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The benefits of water-saving techniques such as alternate furrow and deficit irrigations need to be explored to ensure food security for the ever-increasing population within the context of declining availability of irrigation water. In this regard, field experiments were conducted for 2 consecutive dry seasons in the semiarid region of southwestern Ethiopia and investigated the influence of alternate furrow irrigation method with different irrigation levels on the yield, yield components, water use efficiency, and profitability of potato production. The experiment comprised of 3 irrigation methods: (i) conventional furrow irrigation (CFI), (ii) alternate furrow irrigation (AFI), and (iii) fixed furrow irrigation (FFI) combined factorially with 3 irrigation regimes: (i) 100%, (ii) 75%, and (iii) 50% of the potato water requirement (ETC). The experiment was laid out in randomized complete block design replicated thrice. Results revealed that seasonal irrigation water applied in alternate furrows was nearly half (170 mm) of the amount supplied in every furrow (331 mm). Despite the half reduction in the total amount of water, tuber (35.68 t ha−1) and total biomass (44.37 t ha−1) yields of potato in AFI did not significantly differ from CFI (34.84 and 45.35 t ha−1, respectively). Thus, AFI improved WUE by 49% compared to CFI. Irrigating potato using 75% of ETC produced tuber yield of 35.01 t ha−1, which was equivalent with 100% of ETC (35.18 t ha−1). Irrigating alternate furrows using 25% less ETC provided the highest net return of US$74.72 for every unit investment on labor for irrigating potato. In conclusion, irrigating alternate furrows using up to 25% less ETC saved water, provided comparable yield, and enhanced WUE and economic benefit. Therefore, farmers and experts are recommended to make change to AFI with 25% deficit irrigation in the study area and other regions with limited water for potato production to improve economic, environmental, and social performance of their irrigated systems.

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Yield and quality of potato tuber and its water productivity are influenced by alternate furrow irrigation in a raised bed system

Cited by 38 publications

References 46 publications

Impacts of Water Stress Severity and Duration on Potato Photosynthetic Activity and Yields

Impacts of Water Stress Severity and Duration on Potato Photosynthetic Activity and Yields

Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning

Yield and Water Use Efficiency of Potato under Alternate Furrows and Deficit Irrigation

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